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Disentangling the contributions of water vapor, albedo and evapotranspiration variations to the temperature effect of vegetation greening over the Arctic

Author(s):
Yu, Linfei; Leng, Guoyong; Yao, Lei; Lu, Chenxi; Han, Siqi; Fan, Shunxiang
Publication title: Journal of Hydrology
2025
 | Volume: 646
2025
DOI: 10.1016/j.jhydrol.2024.132331
Abstract:
Vegetation greening is observed over the Arctic, and its feedback to Arctic amplification has attracted increasing attention. Previous studies have pr… Vegetation greening is observed over the Arctic, and its feedback to Arctic amplification has attracted increasing attention. Previous studies have primarily focused on the temperature effect of a single environmental variable (e.g., albedo), while the separate contributions of land surface albedo, evapotranspiration (ET) and water vapor remain underexamined. In this study, we develop knowledge-based data-driven models (i.e., path analysis and machine learning) to estimate the temperature effect of vegetation greening and quantify the separate contributions of albedo, ET and water vapor in July and August from 1982 to 2015. The results show a wide range of temperature sensitivity to the NDVI (Normalized Difference Vegetation Index), and vegetation greening has led to Arctic warming of 0.76 °C, 0.68 °C, 0.83 °C in July and August and the average of the two months, respectively. Path analysis suggested that vegetation greening affects Arctic air temperature mainly by regulating albedo and water vapor. In July, changes in water vapor contributed the most to the temperature effect of vegetation greening with a contribution of 0.25 ± 0.08 °C, while in August, changes in albedo and water vapor had similar effects with a contribution of 0.21 ± 0.08 °C. In contrast, changes in ET have generated a negligible cooling effect due to small changes in ET. Further analysis shows similar positive contributions of albedo and water vapor in barren, graminoid tundra, prostrate-shrub tundra and erect-shrub, with contributions ranging from 0.18 ± 0.05°C to 0.30 ± 0.11°C, while changes in water vapor dominate vegetation’s temperature effect in wetlands, with contributions ranging from 0.26 ± 0.11°C to 0.32 ± 0.16°C. This study emphasizes the importance of considering multiple driving factors to assess the temperature effect of vegetation greening in a consistent framework and highlights the critical role of water vapor change in addition to the widely examined albedo in explaining Arctic warming. more
Application Atmosphere CDR CM-SAF Climate Data Records Terrestrial

Validation of Aeolus L2B products over the tropical Atlantic using radiosondes

Author(s):
Borne, M.; Knippertz, P.; Weissmann, M.; Witschas, B.; Flamant, C.; Rios-Berrios, R.; Veals, P.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 2
2024
DOI: 10.5194/amt-17-561-2024
Abstract:
Since its launch by the European Space Agency in 2018, the Aeolus satellite has been using the first Doppler wind lidar in space to acquire three-dime… Since its launch by the European Space Agency in 2018, the Aeolus satellite has been using the first Doppler wind lidar in space to acquire three-dimensional atmospheric wind profiles around the globe. Especially in the tropics, these observations compensate for the currently limited number of other wind observations, making an assessment of the quality of Aeolus wind products in this region crucial for numerical weather prediction. To evaluate the quality of the Aeolus L2B wind products across the tropical Atlantic Ocean, 20 radiosondes corresponding to Aeolus overpasses were launched from the islands of Sal, Saint Croix, and Puerto Rico during August-September 2021 as part of the Joint Aeolus Tropical Atlantic Campaign. During this period, Aeolus sampled winds within a complex environment with a variety of cloud types in the vicinity of the Intertropical Convergence Zone and aerosol particles from Saharan dust outbreaks. On average, the validation for Aeolus Rayleigh-clear revealed a random error of 3.8-4.3ms-1 between 2 and 16km, and 4.3-4.8ms-1 between 16 and 20km, with a systematic error of -0.5±0.2ms-1. For Mie-cloudy, the random error between 2 and 16km is 1.1-2.3ms-1 and the systematic error is -0.9±0.3ms-1. It is therefore concluded that Rayleigh-clear winds do not meet the mission's random error requirement, while Mie winds most likely do not fulfil the mission bias requirement. Below clouds or within dust layers, the quality of Rayleigh-clear observations are degraded when the useful signal is reduced. In these conditions, we also noticed an underestimation of the L2B estimated error. Gross outliers, defined as large deviations from the radiosonde data, but with low error estimates, account for less than 5% of the data. These outliers appear at all altitudes and under all environmental conditions; however, their root cause remains unknown. Finally, we confirm the presence of an orbital-dependent bias observed with both radiosondes and European Centre for Medium-Range Weather Forecasts model equivalents. The results of this study contribute to a better characterisation of the Aeolus wind product in different atmospheric conditions and provide valuable information for further improvement of the wind retrieval algorithm. © 2024 Maurus Borne et al. more
Atmosphere NWC-SAF Software for CDR development

Utility of thermal remote sensing for evaluationof a high-resolution weather model in a city

Author(s):
Hall, T.W.; Blunn, L.; Grimmond, S.; McCarroll, N.; Merchant, C.J.; Morrison, W.; Shonk, J.K.P.; Lean, H.; Best, M.
Publication title: Quarterly Journal of the Royal Meteorological Society
2024
 | Volume: 150 | Issue: 760
2024
DOI: 10.1002/qj.4669
Abstract:
Progress in high-resolution numerical weather prediction (NWP) for urban areas will require new modelling approaches and extensive evaluation. Here, w… Progress in high-resolution numerical weather prediction (NWP) for urban areas will require new modelling approaches and extensive evaluation. Here, we exploit land surface temperature (LST) data from Landsat-8 to assess 100 m resolution NWP for London (UK) on four cloud-free days. The LST observations are directional radiometric temperatures with non-negligible uncertainties. We consider the challenges of informative comparison between the Landsat LST and the NWP scheme's internal characterisation of the complete surface temperature. The LST spatial coverage allows large-scale observation–model differences to be explored. In one case, obvious spatial artifacts in the NWP surface temperature are observed relative to the Landsat LST. These are found to be related to the NWP's initial method of downscaling of soil moisture using soil properties. Updated model runs have higher spatial correlation between model and Landsat LST. In cases where meteorological conditions favour the formation of horizontal convective rolls, warmer air temperatures associated with updraughts in the mixed layer extend inappropriately to the urban surface. This manifests as warm stripes in the model surface temperature that are not present in the Landsat LST. NWP–Landsat LST differences are larger in more built-up areas on days nearer summer solstice. This is largely attributed to urban thermal anisotropy, as Landsat preferentially views warmer urban surfaces, whereas the model LST represents all surfaces. We evaluate two approaches to quantify this sampling effect, but further work is needed to fully constrain it and facilitate more informative model evaluation. © 2024 Crown copyright and The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society. This article is published with the permission of the Controller of HMSO and the King's Printer for Scotland. more
Application Atmosphere Method NWP-SAF Software for CDR development

Using Simulated Radiances to Understand the Limitations of Satellite-Retrieved Volcanic Ash Data and the Implications for Volcanic Ash Cloud Forecasting

Author(s):
Saint, C.; Beckett, F.M.; Dioguardi, F.; Kristiansen, N.; Tubbs, R.N.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 23
2024
DOI: 10.1029/2024JD041112
Abstract:
Volcanic Ash Advisory Centers (VAACs) have generated volcanic ash forecasts for the aviation industry since the mid-1990s. The excellent spatial and t… Volcanic Ash Advisory Centers (VAACs) have generated volcanic ash forecasts for the aviation industry since the mid-1990s. The excellent spatial and temporal coverage of satellite data makes them critical to the validation of ash dispersion model forecasts. This study investigates the limitations of satellite-retrieved volcanic ash data through the production of simulated radiances for a range of ash cloud properties encompassing the satellite retrieval's sensitivity. We run a detection and retrieval algorithm (Francis et al., 2012, https://doi.org/10.1029/2011JD016788) on these simulated ash clouds and assess the sensitivity and performance of the algorithms. Expected limitations are highlighted, including a lack of sensitivity to particles larger than ∼10 μm in radius and challenges in accurately retrieving heights in the stratosphere. However, other previously poorly defined limitations are also constrained, such as the reduction in sensitivity as ash column loading increases in optically thick ash clouds and increasingly underestimated column loading when column loadings are >∼7 g m−2. We consider the implications of the identified limitations when using satellite-retrieved ash column loadings to verify dispersion model output. We show that, accounting for the limitations of the satellite retrieval, a significant proportion of mass in the model output can lie outside the sensitivity range of the satellite detection and retrieval. This demonstrates the importance of understanding observations' limitations when comparing to model output. This knowledge should be used when verifying operational volcanic ash cloud forecasts. © 2024 Crown copyright and British Geological Survey (C) UKRI. This article is published with the permission of the Controller of HMSO and the King's Printer for Scotland. more
Application Atmosphere NWP-SAF Software for CDR development

Updated OMI Glyoxal Column Measurements Using Collection 4 Level 1B Radiances

Author(s):
Kwon, H.-A.; González Abad, G.; Chan Miller, C.; Hall, K.R.; Nowlan, C.R.; O’Sullivan, E.; Wang, H.; Chong, H.; Ayazpour, Z.; Liu, X.; Chance, K.
Publication title: Earth and Space Science
2024
 | Volume: 11 | Issue: 9
2024
DOI: 10.1029/2024EA003705
Abstract:
This study presents new glyoxal (CHOCHO) products from the Ozone Monitoring Instrument (OMI) by utilizing updated level 1B irradiance/radiance data (C… This study presents new glyoxal (CHOCHO) products from the Ozone Monitoring Instrument (OMI) by utilizing updated level 1B irradiance/radiance data (Collection 4) and an updated glyoxal retrieval algorithm. The adoption of Collection 4 contributes to the reduction of artificial signals in differential glyoxal slant column densities (dSCDs) and improved fitting root mean square, and the updated retrieval settings result in fewer negative values of glyoxal dSCDs over oceans and less noisy dSCDs in the South Atlantic Anomaly. On-line calculations of air mass factors consider interactive physical processes between input parameters. To address persistent trends in glyoxal SCDs over the Pacific Ocean that remain despite these updates, a trend correction is implemented. We evaluate the updated OMI glyoxal products using inter-comparisons with GOME-2A/2B glyoxal products. OMI glyoxal products exhibit good spatial and temporal agreement with GOME-2A/2B, with correlation coefficients of 0.75–0.78 globally and 0.84–0.85 over source regions. Small biases are observed in OMI glyoxal vertical column densities, ranging from −0.2 ± 5.7% to 9 ± 3% in low and high glyoxal conditions, respectively, against GOME-2A/2B. These advancements contribute to the reliability and accuracy of OMI glyoxal products, enhancing their utility for atmospheric studies and enabling a 20-year-long data record suitable for climate studies. © 2024. The Author(s). more
AC-SAF Atmosphere Climate Data Records Validation

Uncertainty in simulated brightness temperature due to sensitivity to atmospheric gas spectroscopic parameters from the centimeter- to submillimeter-wave range

Author(s):
Gallucci, D.; Cimini, D.; Turner, E.; Fox, S.; Rosenkranz, P.W.; Tretyakov, M.Y.; Mattioli, V.; Larosa, S.; Romano, F.
Publication title: Atmospheric Chemistry and Physics
2024
 | Volume: 24 | Issue: 12
2024
DOI: 10.5194/acp-24-7283-2024
Abstract:
Atmospheric radiative transfer models are extensively used in Earth observation to simulate radiative processes occurring in the atmosphere and to pro… Atmospheric radiative transfer models are extensively used in Earth observation to simulate radiative processes occurring in the atmosphere and to provide both upwelling and downwelling synthetic brightness temperatures for ground-based, airborne, and satellite radiometric sensors. For a meaningful comparison between simulated and observed radiances, it is crucial to characterize the uncertainty in such models. The purpose of this work is to quantify the uncertainty in radiative transfer models due to uncertainty in the associated spectroscopic parameters and to compute simulated brightness temperature uncertainties for millimeter- and submillimeter-wave channels of downward-looking satellite radiometric sensors (MicroWave Imager, MWI; Ice Cloud Imager, ICI; MicroWave Sounder, MWS; and Advanced Technology Microwave Sounder, ATMS) as well as upward-looking airborne radiometers (International Submillimetre Airborne Radiometer, ISMAR, and Microwave Airborne Radiometer Scanning System, MARSS). The approach adopted here is firstly to study the sensitivity of brightness temperature calculations to each spectroscopic parameter separately, then to identify the dominant parameters and investigate their uncertainty covariance, and finally to compute the total brightness temperature uncertainty due to the full uncertainty covariance matrix for the identified set of relevant spectroscopic parameters. The approach is applied to a recent version of the Millimeter-wave Propagation Model, taking into account water vapor, oxygen, and ozone spectroscopic parameters, though the approach is general and can be applied to any radiative transfer code. A set of 135 spectroscopic parameters were identified as dominant for the uncertainty in simulated brightness temperatures (26 for water vapor, 109 for oxygen, none for ozone). The uncertainty in simulated brightness temperatures is computed for six climatology conditions (ranging from sub-Arctic winter to tropical) and all instrument channels. Uncertainty is found to be up to few kelvins [K] in the millimeter-wave range, whereas it is considerably lower in the submillimeter-wave range (less than 1 K). © Author(s) 2024. more
Atmosphere Climate Data Records NWP-SAF Software for CDR development Validation

Twenty-Year Climatology of Solar UV and PAR in Cyprus: Integrating Satellite Earth Observations with Radiative Transfer Modeling

Author(s):
Fragkos, Konstantinos; Fountoulakis, Ilias; Charalampous, Georgia; Papachristopoulou, Kyriakoula; Nisantzi, Argyro; Hadjimitsis, Diofantos; Kazadzis, Stelios
Publication title: Remote Sensing
2024
 | Volume: 16 | Issue: 11
2024
DOI: 10.3390/rs16111878
Abstract:
In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cypr… In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and reanalysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, captures the nuanced dynamics of Cyprus’s atmospheric conditions. With a temporal resolution of 15 min and a spatial of 0.05° × 0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models’ accuracy but also highlights its proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), ranging from −2 to −4% per decade, have been found in autumn, especially marked in the island’s northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of −2 to −3% per decade, which were found in spring, do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the day light integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data. more
CM-SAF Climate Data Records Terrestrial Validation

Trends in observed surface solar radiation and their causes in Brazil in the first 2 decades of the 21st century

Author(s):
Ferreira Correa, L.; Folini, D.; Chtirkova, B.; Wild, M.
Publication title: Atmospheric Chemistry and Physics
2024
 | Volume: 24 | Issue: 15
2024
DOI: 10.5194/acp-24-8797-2024
Abstract:
Numerous studies have investigated the long-term variability in surface solar radiation (SSR) around the world. However, the large disparity in the av… Numerous studies have investigated the long-term variability in surface solar radiation (SSR) around the world. However, the large disparity in the availability of observational data between developed and less developed/developing countries leads to an under-representation of studies on SSR changes in the latter. This is especially true for South America, where few observational studies have investigated the SSR trends and usually only at a local or regional scale. In this study we use data from 34 stations distributed throughout all of the regions of Brazil to present the SSR trends in the first 2 decades of the 21st century and investigate their associated causes. The stations were grouped into eight composites according to their proximity. Our results show that in north and northeast Brazil a strong dimming occurred, with significant contributions from increasing atmospheric absorption, most likely due to anthropogenic emissions, and increasing cloud cover. In the southeast and midwest regions of Brazil, near-zero trends resulted from competing effects of clear-sky processes (attenuation of solar radiation under cloudless conditions) and strong negative trends in cloud cover. In the southern part of the Amazon and in south Brazil a statistically insignificant brightening was observed, with significant contributions from decreasing biomass burning emissions in the former and competing minor contributions in the latter. These results can help deepen our knowledge and understanding of SSR long-term trends and their causes in South America, reducing the under-representation of this continent when compared with regions like Europe. © Copyright: 2024 Lucas Ferreira Correa et al. more
Application Atmosphere CM-SAF Climate Data Records

Toward a US Framework for Continuity of Satellite Observations of Earth's Climate and for Supporting Societal Resilience

Author(s):
Publication title: Earth's Future
2024
 | Volume: 12 | Issue: 2
2024
DOI: 10.1029/2023EF003757
Abstract:
Abstract There is growing urgency for improved public and commercial services to support a resilient, secure, and thriving United States (… Abstract There is growing urgency for improved public and commercial services to support a resilient, secure, and thriving United States (US) in the face of mounting decision‐support needs for environmental stewardship and hazard response, as well as for climate change adaptation and mitigation. Sustained space‐based Earth observations are critical infrastructure to support the delivery of science and decision‐support information with local, national, and global utility. This is reflected in part through the United States' sustained support of a suite of weather and land‐imaging satellites. However, outside of these two areas, the US lacks an overarching, systematic plan or framework to identify, prioritize, fund, and implement sustained space‐based Earth observations to meet the Nation's full range of needs for science, government policy, and societal support. To aid and accelerate the discussion on our nation's needs, challenges and opportunities associated with sustained critical space‐based Earth observations, the Keck Institute for Space Studies (KISS) sponsored a multi‐week think‐tank study to offer ways forward. Based on this study, the KISS study team suggests the establishment of a robust coordination framework to help address US needs for sustained Earth observations. This coordination framework could account for: (a) approaches to identify and prioritize satellite observations needed to meet US needs for science and services, (b) the rapidly evolving landscape of space‐based Earth viewing architecture options and technology improvements with increasing opportunities and lower cost access to space, and (c) the technical and programmatic underpinnings required for proper and comprehensive data stewardship to support a wide range of research and public services. , Plain Language Summary The Keck Institute of Space Studies has carried out a think tank study to codify best practices, articulate successes, and identify challenges and opportunities in the prioritization, acquisition, curation, and stewardship of sustained space‐based Earth observations. The goal of the study is to accelerate discussion and plans for a greater and more impactful US contribution to the global satellite observing system that will support decision‐making regarding climate change, environmental hazards, and national security. Based on this study, the KISS study team suggests the establishment of a nimble and responsive coordination framework to help guide and shepherd US concerns regarding sustained Earth observations. This coordination framework should account for: (a) approaches to identify and prioritize satellite observations needed to meet US needs for science and services, (b) the rapidly evolving landscape of space‐based Earth viewing architecture options and technology improvements with increasing opportunities and lower cost access to space and (c) the technical and programmatic underpinnings required for proper and comprehensive data stewardship with a broad science and services user base in mind. , Key Points There is growing urgency for improved public and commercial services to support a resilient, secure, and thriving US Space‐based Earth observations represent an essential component of the infrastructure needed to support the delivery of needed information The US would benefit from an overarching plan for sustained Earth observations to support our science, policy, and resilience goals more
Atmosphere EUM-Secr International cooperation

Thermodynamics Drive Post-2016 Changes in the Antarctic Sea Ice Seasonal Cycle

Author(s):
Himmich, K.; Vancoppenolle, M.; Stammerjohn, S.; Bocquet, M.; Madec, G.; Sallée, J.-B.; Fleury, S.
Publication title: Journal of Geophysical Research: Oceans
2024
 | Volume: 129 | Issue: 8
2024
DOI: 10.1029/2024JC021112
Abstract:
Antarctic sea ice extent has been persistently low since late 2016, possibly owing to changes in atmospheric and oceanic conditions. However, the rela… Antarctic sea ice extent has been persistently low since late 2016, possibly owing to changes in atmospheric and oceanic conditions. However, the relative contributions of the ocean, the atmosphere and the underlying mechanisms by which they have affected sea ice remain uncertain. To investigate possible causes for this sea-ice decrease, we establish a seasonal timeline of sea ice changes following 2016, using remote sensing observations. Anomalies in the timing of sea ice retreat and advance are examined along with their spatial and interannual relations with various indicators of seasonal sea ice and oceanic changes. They include anomalies in winter ice thickness, spring ice removal rate due to ice melt and transport, and summer sea surface temperature. We find that the ice season has shortened at an unprecedented rate and magnitude, due to earlier retreat and later advance. We attribute this shortening to a winter ice thinning, in line with ice-albedo feedback processes, with ice transport playing a smaller role. Reduced ice thickness has accelerated spring ice area removal as thinner sea ice requires less time to melt. The consequent earlier sea ice retreat has in turn increased ocean solar heat uptake in summer, ultimately delaying sea ice advance. We speculate that the observed winter sea ice thinning is consistent with previous evidence of subsurface warming of the Southern Ocean. © 2024. The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF

The severity of dry and hot climate extremes and their related impacts on vegetation in Madagascar

Author(s):
Gouveia, C.M.; Silva, M.; Russo, A.
Publication title: iScience
2024
 | Volume: 27 | Issue: 1
2024
DOI: 10.1016/j.isci.2023.108658
Abstract:
Madagascar is a low-income country, highly vulnerable to natural disasters affecting the small-scale subsistence farming system. Recently, climate cha… Madagascar is a low-income country, highly vulnerable to natural disasters affecting the small-scale subsistence farming system. Recently, climate change and environmental degradation have contributed to an intensification of food insecurity. We aim to monitor the link between dry and hot extremes on vegetation conditions, separated or concurrently, using satellite data, such as LST, ET, ET0, and FAPAR products from SEVIRI/MSG disseminated by LSASAF-EUMETSAT. The analysis was made for a long record from 2004 to 2021, focusing on the extreme seasons of 2020 and 2021. Results highlight the higher impact of combined dry and hot events when compared with isolated events, with a strong response of vegetation in the southern part of Madagascar. Results point to the added value of using the recent data records from geostationary satellites with high temporal resolution and updated in near real-time, to early detect, monitor, and characterize the impact of climate extremes on vegetation dynamics. © 2023 The Authors more
Application Atmosphere LSA-SAF Terrestrial

The role of atmospheric conditions in the Antarctic sea ice extent summer minima

Author(s):
Mezzina, B.; Goosse, H.; Klein, F.; Barthélemy, A.; Massonnet, F.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 8
2024
DOI: 10.5194/tc-18-3825-2024
Abstract:
Understanding the variability of Antarctic sea ice is still a challenge. After decades of modest growth, an unprecedented minimum in the sea ice exten… Understanding the variability of Antarctic sea ice is still a challenge. After decades of modest growth, an unprecedented minimum in the sea ice extent (SIE) was registered in summer 2017, and, following years of anomalously low SIE, a new record was established in early 2022. These two memorable minima have received great attention as single cases, but a comprehensive analysis of summer SIE minima is currently lacking. Indeed, other similar events are present in the observational record, although they are minor compared to the most recent ones, and a full analysis of all summer SIE minima is essential to separate potential common drivers from event-specific dynamics in order to ultimately improve our understanding of the Antarctic sea ice and climate variability. In this work, we examine sea ice and atmospheric conditions during and before all summer SIE minima over the satellite period up to 2022. We use observations and reanalysis data and compare our main findings with results from an ocean-sea ice model (NEMO-LIM) driven by prescribed atmospheric fields from ERA5. Examining SIE and sea ice concentration (SIC) anomalies, we find that the main contributors to the summer minima are the Ross and Weddell sectors. However, the two regions play different roles, and the variability of the Ross Sea explains most of the minima, with typical negative SIE anomalies about twice as large as the ones in the Weddell Sea. Furthermore, the distribution of SIC anomalies is also different: in the Weddell Sea, they exhibit a dipolar structure, with increased SIC next to the continent and decreased SIC at the sea ice margin, while the Ross Sea displays a more homogenous decrease. We also examine the role of wintertime sea ice conditions before the summer SIE minima and find mixed results depending on the period: the winter conditions are relevant in the most recent events, after 2017, but they are marginal for previous years. Next, we consider the influence of the atmosphere on the SIE minima, which is shown to play a major role: after analyzing the anomalous atmospheric circulation during the preceding spring, we find that different large-scale anomalies can lead to similar regional prevailing winds that drive the summer minima. Specifically, the SIE minima are generally associated with dominant northwesterly anomalous winds in the Weddell Sea, while a southwesterly anomalous flow prevails in the Ross Sea. Finally, we investigate the relative contribution of dynamic (e.g., ice transport) and thermodynamic (e.g., local melting) processes to the summer minima. Our results indicate that the exceptional sea ice loss in both the Ross and Weddell sectors is dominated at the large scale by thermodynamic processes, while dynamics are also present but with a minor role. © Author(s) 2024. more
Application Climate Data Records Cryosphere OSI-SAF

The Polar Front in the northwestern Barents Sea: structure, variability and mixing

Author(s):
Kolås, E.H.; Fer, I.; Baumann, T.M.
Publication title: Ocean Science
2024
 | Volume: 20 | Issue: 4
2024
DOI: 10.5194/os-20-895-2024
Abstract:
In the northwestern Barents Sea the warm and salty Atlantic Water meets the cold and fresh Polar Water, forming a distinct thermohaline front, the Bar… In the northwestern Barents Sea the warm and salty Atlantic Water meets the cold and fresh Polar Water, forming a distinct thermohaline front, the Barents Sea Polar Front. Here we present the structure of the front, its variability and associated mixing using observations from two cruises conducted in October 2020 and February 2021 during the Nansen Legacy project in the region between the Hopen Trench and the Olga Basin. Ocean stratification, currents and turbulence data were obtained during seven ship transects across the Polar Front near 77°N, 30°E. These transects are complemented by four missions using ocean gliders, one of which was equipped with microstructure sensors to measure turbulence. Across the front, we observe warm (>1°C) and salty (>35.0gkg-1) Atlantic Water intruding below the colder ( more
Application Atmosphere Climate Data Records Cryosphere OSI-SAF

The Performance of Downward Shortwave Radiation Products from Satellite and Reanalysis over the Transect of Zhongshan Station to Dome A, East Antarctica

Author(s):
Jia, Jiajia; Zeng, Zhaoliang; Zhang, Wenqian; Zheng, Xiangdong; Wang, Yaqiang; Ding, Minghu
Publication title: Advances in Atmospheric Sciences
2024
 | Volume: 41 | Issue: 8
2024
DOI: 10.1007/s00376-023-3136-0
Abstract:
The downward shortwave radiation (DSR) is an important part of the Earth’s energy balance, driving Earth’s system’s energy, water, and carbon cycles. … The downward shortwave radiation (DSR) is an important part of the Earth’s energy balance, driving Earth’s system’s energy, water, and carbon cycles. Due to the harsh Antarctic environment, the accuracy of DSR derived from satellite and reanalysis has not been systematically evaluated over the transect of Zhongshan station to Dome A, East Antarctica. Therefore, this study aims to evaluate DSR reanalysis products (ERA5-Land, ERA5, MERRA-2) and satellite products (CERES and ICDR) in this area. The results indicate that DSR exhibits obvious monthly and seasonal variations, with higher values in summer than in winter. The ERA5-Land (ICDR) DSR product demonstrated the highest (lowest) accuracy, as evidenced by a correlation coefficient of 0.988 (0.918), a root-mean-square error of 23.919 (69.383) W m−2, a mean bias of −1.667 (−28.223) W m−2 and a mean absolute error of 13.37 (58.99) W m−2. The RMSE values for the ERA5-Land reanalysis product at seven stations, namely Zhongshan, Panda 100, Panda 300, Panda 400, Taishan, Panda 1100, and Kunlun, were 30.938, 29.447, 34.507, 29.110, 20.339, 17.267, and 14.700 W m−2, respectively; with corresponding bias values of 9.887, −12.159, −19.181, −15.519, −8.118, 6.297, and 3.482 W m−2. Regarding seasonality, ERA5-Land, ERA5, and MERRA-2 reanalysis products demonstrate higher accuracies during spring and summer, while ICDR products are least accurate in autumn. Cloud cover, water vapor, total ozone, and severe weather are the main factors affecting DSR. The error of DSR products is greatest in coastal areas (particularly at the Zhongshan station) and decreases towards the inland areas of Antarctica. more
Atmosphere CM-SAF Climate Data Records Validation

The jra-3q reanalysis

Author(s):
Kosaka, Y.; Kobayashi, S.; Harada, Y.; Kobayashi, C.; Naoe, H.; Yoshimoto, K.; Harada, M.; Goto, N.; Chiba, J.; Miyaoka, K.; Sekiguchi, R.; Deushi, M.; Kamahori, H.; Nakaegawa, T.; Tanaka, T.Y.; Tokuhiro, T.; Sato, Y.; Matsushita, Y.; Onogi, K.
Publication title: Journal of the Meteorological Society of Japan
2024
 | Volume: 102 | Issue: 1
2024
DOI: 10.2151/jmsj.2024-004
Abstract:
The Japan Meteorological Agency (JMA) has developed the third Japanese global atmospheric reanalysis, the Japanese Reanalysis for Three Quarters of a … The Japan Meteorological Agency (JMA) has developed the third Japanese global atmospheric reanalysis, the Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). The objective of JRA-3Q is to improve quality in terms of issues identified in the previous Japanese 55-year Reanalysis (JRA-55) and to extend the reanalysis period further into the past. JRA-3Q is based on the TL479 version of the JMA global Numerical Weather Prediction (NWP) system as of December 2018 and uses results of developments in the operational NWP system, boundary conditions, and forcing fields achieved at JMA since JRA-55. It covers the period from September 1947, when Typhoon Kathleen brought severe flood damage to Japan, and uses rescued historical observations to extend its analyses backwards in time about 10 years earlier than JRA-55. This paper describes the data assimilation system, forecast model, observations, boundary conditions, and forcing fields used to produce JRA-3Q as well as the basic characteristics of the JRA-3Q product. The initial quality evaluation revealed major improvements from JRA-55 in the global energy budget and representation of tropical cyclones (TCs). One of the major problems in JRA-55—global energy imbalance with excess upward net energy flux at the top of the atmosphere and at the surface—has been significantly reduced in JRA-3Q. Another problem—a trend of artificial weakening of TCs—has been resolved through the use of a method that generates TC bogus based on the JMA operational system. There remain several problems such that the volcanic-induced stratospheric warming is smaller than expected. This paper discusses the causes of such problems and possible solutions in future reanalyses. © 2024, Meteorological Society of Japan. All rights reserved. more
Application Atmosphere Climate Data Records NWP-SAF Software for CDR development

The Ice Cloud Imager: retrieval of frozen water column properties

Author(s):
May, E.; Rydberg, B.; Kaur, I.; Mattioli, V.; Hallborn, H.; Eriksson, P.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 19
2024
DOI: 10.5194/amt-17-5957-2024
Abstract:
The Ice Cloud Imager (ICI) aboard the second generation of the EUMETSAT Polar System (EPS-SG) will provide novel measurements of ice hydrometeors. ICI… The Ice Cloud Imager (ICI) aboard the second generation of the EUMETSAT Polar System (EPS-SG) will provide novel measurements of ice hydrometeors. ICI is a passive conically scanning radiometer that will operate within a frequency range of 183 to 664 GHz, helping to cover the present wavelength gap between microwave and infrared observations. Reliable global data will be produced on a daily basis. This paper presents the retrieval database to be used operationally and performs a final pre-launch assessment of ICI retrievals. Simulations are performed within atmospheric states that are consistent with radar reflectivities and represent the three-dimensional (3D) variability of clouds. The radiative transfer calculations use empirically based hydrometeor models. Azimuthal orientation of particles is mimicked, allowing for the consideration of polarisation. The degrees of freedom (DoFs) of the ICI retrieval database are shown to vary according to cloud type. The simulations are considered to be the most detailed performed to this date. Simulated radiances are shown to be statistically consistent with real observations. Machine learning is applied to perform inversions of the simulated ICI observations. The method used allows for the estimation of non-Gaussian uncertainties for each retrieved case. Retrievals of ice water path (IWP), mean mass height (Zm), and mean mass diameter (Dm) are presented. Distributions and zonal means of both database and retrieved IWP show agreement with DARDAR. Retrieval tests indicate that ICI will be sensitive to IWP between 10−2 and 101 kg m−2. Retrieval performance is shown to vary with climatic region and surface type, with the best performance achieved over tropical regions and over ocean. As a consequence of this study, retrievals from real observations will be possible from day one of the ICI operational phase. © 2024 Eleanor May et al. more
Application Atmosphere Climate Data Records NWP-SAF Software for CDR development

The impacts of incentive policies on improving private investment for rural electrification in Nigeria – A geospatial study

Author(s):
Husein, Munir; Moner-Girona, Magda; Falchetta, Giacomo; Stevanato, Nicolò; Fahl, Fernando; Szabó, Sandor
Publication title: Heliyon
2024
 | Volume: 10 | Issue: 5
2024
DOI: 10.1016/j.heliyon.2024.e27440
Abstract:
In Nigeria, 86 million people lack electricity access, the highest number worldwide, predominantly in rural areas. Despite government efforts, constra… In Nigeria, 86 million people lack electricity access, the highest number worldwide, predominantly in rural areas. Despite government efforts, constrained budgets necessitate private investors, who, without adequate incentives, are hesitant to commit capital due to perceived high risks. This study identifies three existing incentive policies—concessionary loans, capital subsidy, and financing productive use equipment—aimed at promoting rural electrification in Nigeria. Employing geospatial and regulatory analyses, we evaluate their impact on electrification planning across 22,696 population clusters. While all incentives encourage mini-grids and stand-alone systems, results show varied impacts, predominantly favouring mini-grids. Under the baseline, grid extension is optimal for 66% of clusters, followed by mini-grids (27%) and stand-alone systems (7%). Concessionary loans boost mini-grid and Stand-Alone Systems shares by 10% and 5%, respectively. Capital subsidies increase the mini-grid share to 41%, surpassing concessional loans (37%). Financing productive equipment enhances Stand-Alone Systems and mini-grid shares to 15% and 43%. Incentives impact LCOE, CAPEX, and OPEX, with average LCOE reducing to 0.31 EUR/kWh (concessionary loans), 0.30 EUR/kWh (capital subsidy), and 0.27 EUR/kWh (financing productive use). Financing productive uses proves decisively more effective in lowering costs for mini-grids and stand-alone systems than loans or capital subsidies. The important policy implications of this study reinforce the need for tailored incentives for distinct electrification options. more
Atmosphere CM-SAF Climate Data Records Validation

The Cold Bias in the Surface Air Temperature Simulations Over the Tibetan Plateau of RegCM4 Reduced by Adopting the 3D Sub-Grid Terrain Longwave Radiative Effect Scheme

Author(s):
Gu, C.; Huang, A.; Li, X.; Wu, Y.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 23
2024
DOI: 10.1029/2024JD042102
Abstract:
The 3D sub-grid terrain longwave radiative effects (3DSTLRE), which significantly regulate the surface downward longwave radiation (SDLR) in the mount… The 3D sub-grid terrain longwave radiative effects (3DSTLRE), which significantly regulate the surface downward longwave radiation (SDLR) in the mountainous regions, are not described in current numerical models. We incorporated a 3DSTLRE scheme into RegCM4 to assess its influence on modeling the surface air temperature (SAT) across the Tibetan Plateau (TP). Results show that the RegCM4 adopting the parallel-plane longwave radiative scheme significantly underestimates the SAT over TP, this underestimation of SAT is clearly mitigated by considering 3DSTLRE, with the root mean square error (RMSE) decreased by 9%. The SAT simulations are improved more noticeable over western TP than entire TP and more evident at nighttime than at daytime in different seasons. Further analysis indicates that the improvement of SAT simulations over the rugged areas of TP is primarily benefited from the improved SDLR simulations. In the absence of the 3DSTLRE scheme, RegCM4 markedly underestimates SDLR by 20 W·m−2 over the entire TP, this underestimation can be greatly reduced by 15 W·m−2 through adopting the 3DSTLRE scheme, with the RMSE reduced by more than 40% over the rugged edges of TP. The increased SDLR induced by the 3DSTLRE is mainly transformed into sensible heat flux to warm the near surface air, further leading to reduced cold bias of SAT produced by the RegCM4 without 3DSTLRE. Better representing the TP thermal condition can enhance the simulation of East Asian monsoon. Therefore, incorporating the 3DSTLRE scheme in numerical models can potentially improve the ability in simulating and predicting the East Asian monsoon. © 2024. American Geophysical Union. All Rights Reserved. more
Application Atmosphere CM-SAF Climate Data Records Validation

The Contribution of Aeolus Wind Observations to ECMWF Sea Surface Wind Forecasts

Author(s):
Zuo, H.; Stoffelen, A.; Rennie, M.; Hasager, C.B.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 6
2024
DOI: 10.1029/2023JD039555
Abstract:
Aeolus is the first satellite mission focusing on wind profile detection from near the surface to about 30 km in height on a global scale. This study … Aeolus is the first satellite mission focusing on wind profile detection from near the surface to about 30 km in height on a global scale. This study evaluates the contribution of Aeolus winds to sea surface wind forecasts geographically by further analyzing the Observing System Experiments from the European Centre for Medium-Range Weather Forecasts (ECMWF) with scatterometer winds from the meteorological operational satellites (assimilated into the model) and the Haiyang-2B satellite (not assimilated into the model). The findings indicate that Aeolus has the ability to reduce the root-mean-square difference between scatterometer winds and background forecasts (short-range) by about 0.05%–0.16% on average for climatic regions, except for the meridional wind component in the tropics. Also, Aeolus can generally reduce zonal biases of the background forecasts, while its beneficial impact on meridional biases mainly occurs in the Northern Hemisphere extratropics and tropics. For medium-range forecast assessments, as the forecast step extends up to day 5, the positive impact of Aeolus on sea surface wind forecasts becomes more evident and is even greater than 3%, especially for extratropical ocean regions in the Southern Hemisphere. Furthermore, the impact of Aeolus shows seasonal variation, with a substantial positive impact from September 2019 to February 2020 and a negative impact mainly in March, April, and May 2020. © 2024 The Authors. more
Atmosphere OSI-SAF Ocean Validation

The Classification of Tropical Storm Systems in Infrared Geostationary Weather Satellite Images Using Transfer Learning

Author(s):
Senior-Williams, Jacob; Hogervorst, Frank; Platen, Erwin; Kuijt, Arie; Onderwaater, Jacobus; Tervo, Roope; John, Viju O.; Okuyama, Arata
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2024
 | Volume: 17
2024
DOI: 10.1109/JSTARS.2024.3365852
Abstract:
The work performed in this study evaluated the application of generalized pretrained object detection models for the identification and classification… The work performed in this study evaluated the application of generalized pretrained object detection models for the identification and classification of tropical storm (TS) systems through transfer learning. While the majority of literature focuses on developing bespoke models for this application, these typically require significantly more training data, compute resources, and time to train the models due to the large number of parameters the model has to tune to achieve similar results. These models also required additional preprocessing steps, such as extracting the storm from the image, and used a limited number of classes to describe the intensity of the storms. The approach presented here used considerably less data than the majority of other work (2–10x fewer input images) and a larger number of classes. The accuracies of the produced models trained on four different experimental datasets (varying the amount of data and number of classes) through this approach were 75%, 82%, 69%, and 89%. Overall, the models produced promising results, performing approximately equal to the bespoke models with scope to improve the performance of the model. more
Atmosphere Climate Data Records EUM-Secr Method

Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region

Author(s):
Dupuis, S.; Göttsche, F.-M.; Wunderle, S.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 12
2024
DOI: 10.5194/tc-18-6027-2024
Abstract:
Land surface temperature (LST) has gained increased attention in cryospheric research. While various global satellite LST products are available, none… Land surface temperature (LST) has gained increased attention in cryospheric research. While various global satellite LST products are available, none of them is specially designed for the pan-Arctic region. Based on the recently published EUMETSAT Advanced Very High Resolution Radiometer (AVHRR) fundamental data record (FDR), a new LST product (1981-2021) with daily resolution is developed for the pan-Arctic region. Validation shows good accuracy with an average mean absolute error (MAE) of 1.71 K and a MAE range of 0.62-3.07 K against in situ LST data from the Surface Radiation Budget (SURFRAD) network and Karlsruhe Institute of Technology (KIT) sites. Long-term stability, a strong requirement for trend analysis, is assessed by comparing LST with air temperatures from ERA5-Land (T2M) and air temperature data from the EUSTACE (https://www.eustaceproject.org, last access: 17 December 2024) global station dataset. Long-term stability might not be fulfilled mainly due to the orbit drift of the NOAA satellites. Therefore, the analysis is split into two periods: the arctic winter months, which are unaffected by solar illumination and, therefore, orbital drift, and the summer months. The analysis for the winter months results in correlation values (r) of 0.44-0.83, whereas for the summer months (r) values range between 0.37-0.84. Analysis of anomaly differences revealed instabilities for the summer months at a few stations. The same stability analysis for the winter months revealed only one station with instabilities in comparison to station air temperature. Discrepancies between the temperature anomalies recorded at the stations and ERA5-Land T2M were also found. This highlights the limited influence of orbital drift on the LST product, with the winter months presenting good stability across all stations, which makes these data a valuable source for studying LST changes in the pan-Arctic region over the last 40 years. This study concludes by presenting LST trend maps (1981-2021) for the entire region, revealing distinct warming and cooling patterns. © 2024 Sonia Dupuis et al. more
Application Atmosphere CM-SAF Climate Data Records EUM-Secr Land NWP-SAF

Synergistic approach of frozen hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework

Author(s):
Villeneuve, E.; Chambon, P.; Fourrié, N.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 11
2024
DOI: 10.5194/amt-17-3567-2024
Abstract:
In cloudy situations, infrared (IR) and microwave (MW) observations are complementary, with infrared observations being sensitive to small cloud dropl… In cloudy situations, infrared (IR) and microwave (MW) observations are complementary, with infrared observations being sensitive to small cloud droplets and ice particles and with microwave observations being sensitive to precipitation. This complementarity can lead to fruitful synergies in precipitation science (e.g., ). However, several sources of errors do exist in the treatment of infrared and microwave data that could prevent such synergy. This paper studies several of these sources to estimate their impact on retrievals. To do so, simulations from the radiative transfer (RT) for TIROS Operational Vertical Sounder (RTTOV v13) are used to build simulated observations. Indeed, we make use of a fully simulated framework to explain the impacts of the identified errors. A combination of infrared and microwave frequencies is built within a Bayesian inversion framework. Synergy is studied using different experiments: (i) with several sources of errors eliminated, (ii) with only one source of errors considered at a time and (iii) with all sources of errors together. The derived retrievals of frozen hydrometeors for each experiment are examined in a statistical study of 15g d in summer and 15 d in winter over the Atlantic Ocean. One of the main outcomes of the study is that the combination of infrared and microwave frequencies takes advantage of the strengths of both spectral ranges, leading to more accurate retrievals. Each source of error has more or less impact depending on the type of hydrometeor. Another outcome of the study is that, in all cases explored, even though the radiative transfer and numerical modeling errors may decrease the magnitude of benefits generated by the combination of infrared and microwave frequencies, the compromise remains positive. © 2024 Copernicus Publications. All rights reserved. more
Application Atmosphere NWP-SAF Software for CDR development Validation

Summer snow on Arctic sea ice modulated by the Arctic Oscillation

Author(s):
Webster, M.A.; Riihelä, A.; Kacimi, S.; Ballinger, T.J.; Blanchard-Wrigglesworth, E.; Parker, C.L.; Boisvert, L.
Publication title: Nature Geoscience
2024
 | Volume: 17 | Issue: 10
2024
DOI: 10.1038/s41561-024-01525-y
Abstract:
Since the 1970s, Arctic sea ice has undergone unprecedented change, becoming thinner, less extensive and less resilient to summer melt. Snow’s high al… Since the 1970s, Arctic sea ice has undergone unprecedented change, becoming thinner, less extensive and less resilient to summer melt. Snow’s high albedo greatly reduces solar absorption in sea ice and the upper ocean, which mitigates sea–ice melt and ocean warming. However, the drivers of summertime snow depth variability are unknown. The Arctic Oscillation is a mode of natural climate variability, influencing Arctic snowfall and air temperatures. Thus, it may affect summertime snow conditions on Arctic sea ice. Here we examine the role of the Arctic Oscillation in summer snow depth variability on Arctic sea ice in 1980–2020 using atmospheric reanalysis, snow modelling and satellite data. The positive phase leads to greater snow accumulation, ranging up to ~4.5 cm near the North Pole, and higher surface albedo in summer. There are more intense, frequent Arctic cyclones, cooler temperatures aloft and greater snowfall relative to negative and neutral phases; these conditions facilitate a more persistent summer snow cover, which may lessen sea-ice melt and ocean warming. The Arctic Oscillation influence on summertime snow weakens after 2007, which suggests that future warming and Arctic sea-ice loss might modify the relationship between the Arctic Oscillation and snow on Arctic sea ice. © The Author(s) 2024. more
Application Climate Data Records Cryosphere OSI-SAF

Strong persistent cooling of the stratosphere after the Hunga eruption

Author(s):
Stocker, Matthias; Steiner, Andrea K.; Ladstädter, Florian; Foelsche, Ulrich; Randel, William J.
Publication title: Communications Earth & Environment
2024
 | Volume: 5 | Issue: 1
2024
DOI: 10.1038/s43247-024-01620-3
Abstract:
The 2022 eruption of the Hunga volcano was a major event that propelled aerosols and water vapor up to an altitude of 53–57 km. It caused an unprecede… The 2022 eruption of the Hunga volcano was a major event that propelled aerosols and water vapor up to an altitude of 53–57 km. It caused an unprecedented stratospheric hydration that is expected to affect composition, thermal structure, circulation and dynamics for years. Using vertically high resolved satellite observations from radio occultation, we focus on the temperature impact in the stratosphere from the eruption in January 2022 until December 2023. Separating the signals of the Hunga eruption from the broader stratospheric variability reveals a strong persistent radiative cooling of up to –4 K in the tropical and subtropical middle stratosphere from early after the eruption until mid-2023, clearly corresponding to the water vapor distribution. Our results provide new insights from observations into both the localized temperature changes and the persistent stratospheric cooling caused by the Hunga eruption and document this exceptional climatic effect not seen for previous volcanic eruptions. more
Application Atmosphere Climate Data Records ROM-SAF

Stepwise Subduction Observed at a Front in the Marginal Ice Zone in Fram Strait

Author(s):
Hofmann, Z.; von Appen, W.-J.; Kanzow, T.; Becker, H.; Hagemann, J.; Hufnagel, L.; Iversen, M.H.
Publication title: Journal of Geophysical Research: Oceans
2024
 | Volume: 129 | Issue: 5
2024
DOI: 10.1029/2023JC020641
Abstract:
At high latitudes, submesoscale dynamics act on scales of (Formula presented.) (100 m–1 km) and are associated with the breakdown of geostrophic balan… At high latitudes, submesoscale dynamics act on scales of (Formula presented.) (100 m–1 km) and are associated with the breakdown of geostrophic balance, vertical velocities, and energy cascading to small scales. Submesoscale features such as fronts, filaments, and eddies are ubiquitous in marginal ice zones forced by the large horizontal density gradients. In July 2020, we identified multiple fronts and filaments using a towed undulating vehicle near the sea ice edge in central Fram Strait, the oceanic gateway to the Arctic Ocean between Greenland and Svalbard. Sea ice covered the entire study region 1–2 weeks earlier, and a stratified meltwater layer was present. We observed a front between warm and saline Atlantic Water (AW) and cold and fresh Polar Water (PW) at 30–85 m depth, where we identified a subsurface maximum in chlorophyll fluorescence and other biogeochemical properties extending along the tilted isopycnals down to 75 m, indicating subduction of AW (mixed with meltwater) that had previously occurred. The meltwater layer also featured multiple shallow fronts, one of which exhibited high velocities and a subsurface maximum in chlorophyll fluorescence, possibly indicating subduction of PW below the meltwater layer. The fronts at different depth levels suggest a stepwise subduction process near the ice edge, where water subducts from the surface below the meltwater and then further down along subsurface fronts. The submesoscale features were part of a larger-scale mesoscale pattern in the marginal ice zone. As sea ice continuously retreats, such features may become more common in the Arctic Ocean. © 2024. The Authors. more
Application Climate Data Records Cryosphere OSI-SAF

State of the Climate in 2023

Author(s):
Blunden, J.; Boyer, T.
Publication title: Bulletin of the American Meteorological Society
2024
 | Volume: 105 | Issue: 8
2024
DOI: 10.1175/2024BAMSStateoftheClimate.1
Abstract:
Abstract Editors note: For easy download the posted pdf of the State of the Climate in 2023 is a low-resolution file. A hig… Abstract Editors note: For easy download the posted pdf of the State of the Climate in 2023 is a low-resolution file. A high-resolution copy of the report is available by clicking here . Please be patient as it may take a few minutes for the high-resolution file to download. more
Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts

Author(s):
Zhao, F.; Liang, X.; Tian, Z.; Li, M.; Liu, N.; Liu, C.
Publication title: Geoscientific Model Development
2024
 | Volume: 17 | Issue: 17
2024
DOI: 10.5194/gmd-17-6867-2024
Abstract:
An operational synoptic-scale sea ice forecasting system for the Southern Ocean, namely the Southern Ocean Ice Prediction System (SOIPS), has been dev… An operational synoptic-scale sea ice forecasting system for the Southern Ocean, namely the Southern Ocean Ice Prediction System (SOIPS), has been developed to support ship navigation in the Antarctic sea ice zone. Practical application of the SOIPS forecasts had been implemented for the 38th Chinese National Antarctic Research Expedition for the first time. The SOIPS is configured on an Antarctic regional sea ice–ocean–ice shelf coupled model and an ensemble-based localized error subspace transform Kalman filter data assimilation model. Daily near-real-time satellite sea ice concentration observations are assimilated into the SOIPS to update sea ice concentration and thickness in the 12 ensemble members of the model state. By evaluating the SOIPS performance in forecasting sea ice metrics in a complete melt–freeze cycle from 1 October 2021 to 30 September 2022, this study shows that the SOIPS can provide reliable Antarctic sea ice forecasts. In comparison with non-assimilated EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) data, annual mean root mean square errors in the sea ice concentration forecasts at a lead time of up to 168 h are lower than 0.19, and the integrated ice edge errors in the sea ice forecasts in most freezing months at lead times of 24 and 72 h maintain around 0.5 × 106 km2 and below 1.0 × 106 km2, respectively. With respect to the scarce Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observations, the mean absolute errors in the sea ice thickness forecasts at a lead time of 24 h are lower than 0.3 m, which is in the range of the ICESat-2 uncertainties. Specifically, the SOIPS has the ability to forecast sea ice drift, in both magnitude and direction. The derived sea ice convergence rate forecasts have great potential for supporting ship navigation on a fine local scale. The comparison between the persistence forecasts and the SOIPS forecasts with and without data assimilation further shows that both model physics and the data assimilation scheme play important roles in producing reliable sea ice forecasts in the Southern Ocean. © copy 2024 Fu Zhao et al. more
Climate Data Records Cryosphere OSI-SAF Validation

Simultaneous Inference of Sea Ice State and Surface Emissivity Model Using Machine Learning and Data Assimilation

Author(s):
Geer, A.J.
Publication title: Journal of Advances in Modeling Earth Systems
2024
 | Volume: 16 | Issue: 7
2024
DOI: 10.1029/2023MS004080
Abstract:
Satellite microwave radiance observations are strongly sensitive to sea ice, but physical descriptions of the radiative transfer of sea ice and snow a… Satellite microwave radiance observations are strongly sensitive to sea ice, but physical descriptions of the radiative transfer of sea ice and snow are incomplete. Further, the radiative transfer is controlled by poorly-known microstructural properties that vary strongly in time and space. A consequence is that surface-sensitive microwave observations are not assimilated over sea ice areas, and sea ice retrievals use heuristic rather than physical methods. An empirical model for sea ice radiative transfer would be helpful but it cannot be trained using standard machine learning techniques because the inputs are mostly unknown. The solution is to simultaneously train the empirical model and a set of empirical inputs: an “empirical state” method, which draws on both generative machine learning and physical data assimilation methodology. A hybrid physical-empirical network describes the known and unknown physics of sea ice and atmospheric radiative transfer. The network is then trained to fit a year of radiance observations from Advanced Microwave Scanning Radiometer 2, using the atmospheric profiles, skin temperature and ocean water emissivity taken from a weather forecasting system. This process estimates maps of the daily sea ice concentration while also learning an empirical model for the sea ice emissivity. The model learns to define its own empirical input space along with daily maps of these empirical inputs. These maps represent the otherwise unknown microstructural properties of the sea ice and snow that affect the radiative transfer. This “empirical state” approach could be used to solve many other problems of earth system data assimilation. © 2024 ECMWF. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union. more
Application Climate Data Records Cryosphere OSI-SAF

Siberian vegetation growth intensifies monsoon precipitation in southern East Asia in late spring and early summer

Author(s):
Yeh, Sang-Wook; Sohn, Byung-Ju; Oh, Sae-Yoon; Song, Se-Yong; Jeong, Jee-Hoon; Wang, Bin; Wu, Renguang; Yang, Young-Min
Publication title: npj Climate and Atmospheric Science
2024
 | Volume: 7 | Issue: 1
2024
DOI: 10.1038/s41612-024-00650-0
Abstract:
Regional hydrological cycle responding to rising temperatures can have significant influences on society and human activities. We suggest a new perspe… Regional hydrological cycle responding to rising temperatures can have significant influences on society and human activities. We suggest a new perspective on East Asia’s enhanced precipitation amount that emphasizes the role of Siberian surface warming. Increased vegetation greenness in late spring and early summer in eastern Siberia, which may be a response to global warming, acts to warm the surface by reducing the surface albedo with an increase in net absorbed shortwave radiation. Subsequently, eastern Siberia warming leads to the strengthening of anti-cyclonic atmospheric circulation over inner East Asia as well as the subtropical western North Pacific high via thermal forcing and the enhanced land-sea thermal contrast, respectively. Consequently, the anticyclonic circulation over inner East Asia transports much drier and cooler air to southern East Asia. This leads to favorable conditions for increased precipitation in combination with an increased tropical moisture flux from the subtropical western North Pacific high. Therefore, continuous Siberian vegetation growth has a potential influence on the future precipitation amount in the subtropics through vegetation–atmosphere coupled processes. more
Application Atmosphere CM-SAF Climate Data Records Terrestrial

Shallow Convective Heating in Weak Temperature Gradient Balance Explains Mesoscale Vertical Motions in the Trades

Author(s):
Janssens, M.; George, G.; Schulz, H.; Couvreux, F.; Bouniol, D.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 18
2024
DOI: 10.1029/2024JD041417
Abstract:
Earth's climate sensitivity depends on how shallow clouds in the trades respond to changes in the large-scale tropical circulation with warming. In ca… Earth's climate sensitivity depends on how shallow clouds in the trades respond to changes in the large-scale tropical circulation with warming. In canonical theory for this cloud-circulation coupling, it is assumed that the clouds are controlled by the field of vertical motion on horizontal scales larger than the convection's depth ((Formula presented.) 1 km). This assumption has been challenged both by recent in situ observations, and idealized large-eddy simulations (LESs). Here, we therefore bring together the recent observations, new analysis from satellite data, and a 40-day, large-domain ((Formula presented.) km2) LES of the North Atlantic from the 2020 EUREC4A field campaign, to study the interaction between shallow convection and vertical motions on scales between 10 and 1,000 km (mesoscales), in settings that are as realistic as possible. Across all data sets, the shallow mesoscale vertical motions are consistently represented, ubiquitous, frequently organized into circulations, and formed without imprinting themselves on the mesoscale buoyancy field. Therefore, we use the weak-temperature gradient approximation to show that between at least 12.5–400 km scales, the vertical motion balances heating fluctuations in groups of precipitating shallow cumuli. That is, across the mesoscales, shallow convection controls the vertical motion in the trades, and does not simply adjust to it. In turn, the mesoscale convective heating patterns appear to consistently grow through moisture-convection feedback. Therefore, to represent and understand the cloud-circulation coupling of trade cumuli, the full range of scales between the synoptics and the hectometer must be included in our conceptual and numerical models. © 2024. The Author(s). more
Application Atmosphere Climate Data Records EUM-Secr

Sea ice cover in the Copernicus Arctic Regional Reanalysis

Author(s):
Batrak, Y.; Cheng, B.; Kallio-Myers, V.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 3
2024
DOI: 10.5194/tc-18-1157-2024
Abstract:
The Copernicus Arctic Regional Reanalysis (CARRA) is a novel regional high-resolution atmospheric reanalysis product that covers a considerable part o… The Copernicus Arctic Regional Reanalysis (CARRA) is a novel regional high-resolution atmospheric reanalysis product that covers a considerable part of the European Arctic including substantial amounts of ice-covered areas. Sea ice in CARRA is modelled by means of a one-dimensional thermodynamic sea ice parameterisation scheme, which also explicitly resolves the evolution of the snow layer over sea ice. In the present study, we assess the representation of sea ice cover in CARRA and validate it against a wide set of satellite products and observations from ice mass balance buoys. We show that CARRA adequately represents general interannual trends towards thinner and warmer ice in the Arctic. Compared to ERA5, sea ice in CARRA shows a reduced warm bias in the ice surface temperature. The strongest improvement was observed for winter months over the central Arctic and the Greenland and Barents seas where a 4.91ĝ€¯°C median ice surface temperature error in ERA5 is reduced to 1.88ĝ€¯°C in CARRA on average. Over Baffin Bay, intercomparisons suggest the presence of a cold winter-time ice surface temperature bias in CARRA. No improvement over ERA5 was found in the ice surface albedo with spring-time errors in CARRA being up to 0.08 higher on average than those in ERA5 when computed against the CLARA-A2 satellite retrieval product. Summer-time ice surface albedos are comparable in CARRA and ERA5. Sea ice thickness and snow depth in CARRA adequately resolve the annual cycle of sea ice cover in the Arctic and bring added value compared to ERA5. However, limitations of CARRA indicate potential benefits of utilising more advanced approaches for representing sea ice cover in next-generation reanalyses. © Copyright: more
Application Atmosphere CM-SAF Climate Data Records Terrestrial

Sea surface wind retrieval from CFOSAT Rotating fan-beam scatterometer in ocean cyclones

Author(s):
Ji, W.; Fang, Z.; Liu, D.; Yu, R.; Feng, D.
Publication title: International Journal of Remote Sensing
2024
 | Volume: 45 | Issue: 22
2024
DOI: 10.1080/01431161.2024.2402007
Abstract:
Rotating fan-beam scatterometer (RFSCAT) is a radar scatterometer system for sea surface wind vector measurement. Compared with other available scatte… Rotating fan-beam scatterometer (RFSCAT) is a radar scatterometer system for sea surface wind vector measurement. Compared with other available scatterometers, RFSCAT can provide more combination of azimuth angles and incidence angles for a single WVC (wind vector cell), this observation mechanism is more conducive to the sea surface wind direction retrieval. In this paper, the NSCAT-4DS GMF (geophysical model function) with SST (sea surface temperature) correction, and the MSS (Multiple Solution Scheme) combination with a 2DVAR (2-dimensional variational analysis) are adopted to retrieve the sea surface winds from RFSCAT on the CFOSAT (Chinese-French Oceanography Satellite). The retrieved RFSCAT sea surface winds and ASCAT (advanced scatterometer) sea surface winds are compared and tested, and the feasibility of the RFSCAT measuring sea surface winds under high wind speeds is analysed. The results show that the RMSE of the RFSCAT sea surface wind speed using improved algorithm has decreased by 0.292 m s−1, the correlation coefficient has increased by 0.032, and the residual standard deviation has decreased by 0.194 m s−1. The RMSE of RFSCAT sea surface wind direction has decreased by 5.950°, the correlation coefficient has increased by 0.002, and the residual standard deviation has decreased by 5.567°. It is shown that the changes in winds RMSE using pre-improved and improved algorithms have statistical significance. In a word, the spaceborne Ku-band rotating fan-beam scatterometer can capture the winds structure of ocean cyclones. Although there may be high wind speeds saturation phenomena, the detecting sea surface winds at high wind speeds show preferable performance. © 2024 Informa UK Limited, trading as Taylor & Francis Group. more
Atmosphere Climate Data Records OSI-SAF Ocean Validation

Satellite-based time-series of sea-surface temperature since 1980 for climate applications

Author(s):
Embury, O; Merchant, CJ; Good, SA; Rayner, NA; Hoyer, JL; Atkinson, C; Block, T; Alerskans, E; Pearson, KJ; Worsfold, M; Mccarroll, N; Donlon, C
Publication title: SCIENTIFIC DATA
2024
 | Volume: 11 | Issue: 1
2024
DOI: 10.1038/s41597-024-03147-w
Abstract:
A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high… A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 x 1013 locations are processed, yielding 1.4 x 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km-2 yr-1 in 1980 to over 100 km-2 yr-1 after 2007. Data are provided at their native resolution, averaged on a global 0.05 degrees latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05 degrees. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

SARAH-3 - satellite-based climate data records of surface solar radiation

Author(s):
Pfeifroth, U.; Drücke, J.; Kothe, S.; Trentmann, J.; Schröder, M.; Hollmann, R.
Publication title: Earth System Science Data
2024
 | Volume: 16 | Issue: 11
2024
DOI: 10.5194/essd-16-5243-2024
Abstract:
The amount of energy reaching Earth's surface from the Sun is a quantity of high importance for the climate system and for renewable energy applicatio… The amount of energy reaching Earth's surface from the Sun is a quantity of high importance for the climate system and for renewable energy applications. SARAH-3 (SurfAce Radiation DAtaset Heliosat, https://doi.org/10.5676/EUM_SAF_CM/SARAH/V003, Pfeifroth et al., 2023) is a new version of a satellitebased climate data record of surface solar radiation parameters, generated and distributed by the European Organisation of Meteorological Satellites (EUMETSAT) Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 provides data from 1983 onwards, i.e. more than 4 decades of data, and has a spatial resolution of 0.05°_0.05°, a temporal resolution of 30 min and daily and monthly means for the region covered by the Meteosat field of view (65°W to 65° E and 65° S to 65° N). SARAH-3 consists of seven parameters: surface irradiance, direct irradiance, direct normal irradiance, sunshine duration, daylight, photosynthetically active radiation and effective cloud albedo. SARAH-3 data between 1983 and 2020 have been generated with stable input data (i.e. satellite and auxiliary data) to ensure a high temporal stability; these data are temporally extended by operational near-real-time processing - the so-called Interim Climate Data Record. The data record is suitable for various applications, from climate monitoring to renewable energy. The validation of SARAH-3 shows good accuracy (deviations of _5Wm-2 from surface reference measurements for monthly surface irradiance), stability of the data record and further improvements over its predecessor SARAH-2.1. One reason for this improved quality is the new treatment of snow-covered surfaces in the algorithm, reducing the misclassification of snow as clouds. The SARAH-3 data record reveals an increase in the surface irradiance (_+3Wm-2 per decade) during recent decades in Europe, in line with surface observations.. © Author(s) 2024. more
Application Atmosphere CM-SAF Climate Data Records Validation

Remote Sensing Time Series Analysis: A Review of Data and Applications

Author(s):
Fu, Y.; Zhu, Z.; Liu, L.; Zhan, W.; He, T.; Shen, H.; Zhao, J.; Liu, Y.; Zhang, H.; Liu, Z.; Xue, Y.; Ao, Z.
Publication title: Journal of Remote Sensing (United States)
2024
 | Volume: 4
2024
DOI: 10.34133/remotesensing.0285
Abstract:
Remote sensing time series research and applications are advancing rapidly in land, ocean, and atmosphere science, demonstrating emerging capabilities… Remote sensing time series research and applications are advancing rapidly in land, ocean, and atmosphere science, demonstrating emerging capabilities in space-based monitoring methodologies and diverse application prospects. This prompts a comprehensive review of remote sensing time series observations, time series data reconstruction, derived products, and the current progress, challenges, and future directions in their applications. The high-frequency new data, i.e., a constellation strategy, increasing computing power and advancing deep learning algorithms, are driving a paradigm shift from traditional point-in-time mapping to near-real-time monitoring tasks, and even to modeling integration of parameter inversion and prediction in land, water, and air science. Correspondingly, the 3 main projects, namely, the Global Climate Observing System, the United States Geological Survey/National Aeronautics and Space Administration (USGS/NASA) Landsat Science team, and the China Global Land Surface Satellite (GLASS) team, along with other time series-derived products, have found widespread applications in the research of Earth’s radiation balance and human–land systems. They have also been utilized for tasks such as land use change detection, assessing coastal effects, ocean environment monitoring, and supporting carbon neutrality strategies. Moreover, the 3 critical challenges and future directions were highlighted including multimode time series data fusion, deep learning modeling for task-specific domain adaptation, and fine-scale remote sensing applications by using dense time series. This review distills historical and current developments spanning the last several decades, providing an insightful understanding into the advancements in remote sensing time series data and applications. Copyright © 2024 Yingchun Fu et al. more
Application Atmosphere CM-SAF Climate Data Records LSA-SAF

Relationship between precipitation and cloud properties in different regions of Southwest China

Author(s):
Wang, Yuting; Zhao, Pengguo; Zhao, Chuanfeng; Xiao, Hui; Mo, Shuying; Yuan, Liang; Wei, Chengqiang; Zhou, Yunjun
Publication title: International Journal of Climatology
2024
 | Volume: 44 | Issue: 7
2024
DOI: 10.1002/joc.8455
Abstract:
The relationship between precipitation and cloud properties in Southwest China are investigated by using the CLARA-A2 cloud parameters data and TRMM-3… The relationship between precipitation and cloud properties in Southwest China are investigated by using the CLARA-A2 cloud parameters data and TRMM-3B43 precipitation data from 1998 to 2015. Ice water path (IWP) and cloud top height (CTH) are significantly and positively correlated with precipitation in all regions, indicating that ice-phase processes and cloud development processes are the critical processes influencing precipitation. Precipitation is also directly associated with cloud fractional coverage (CFC) due to the significant positive correlation between CFC and precipitation in all regions except the Sichuan Basin (SCB). A positive correlation between liquid water path (LWP) and precipitation is found in the Eastern Tibetan Plateau (ETP) and Yunnan-Kweichow Plateau (YKP), but not in the Western Tibetan Plateau (WTP) and SCB. Notably, the response of precipitation to LWP is not as good as that to IWP in SCB. Precipitation is significantly negatively correlated with ice effective radius (IREF) in WTP and ETP and positively correlated with liquid effective radius (LREF) in ETP, YKP and SCB. IREF and LREF are closely related to cloud microphysical processes. Specifically, small IREF could accelerate the Bergeron process and thus increase precipitation, while large LREF is closely related to the cloud droplets coalescence process. Results indicate that the difference in precipitation between the cold and warm seasons is related to convective available potential energy (CAPE) and low troposphere relative humidity (RH). High CAPE and RH favour the precipitation occurrence in Southwest China. The influence of CAPE and RH on precipitation is more significant in the ETP than that in the WTP, owing to the orographic lifting and moisture transport from the Indian Ocean. Thermodynamic and humidity conditions have a greater impact on precipitation by influencing LREF, LWP and IWP in YKP. In SCB, precipitation shows a strong dependence on CAPE, IWP and LREF, but not on RH. more
Application Atmosphere CM-SAF Climate Data Records

Regional Cloud Forecast Verification Using Standard, Spatial, and Object-Oriented Methods

Author(s):
Christophersen, H.; Nachamkin, J.; Davis, W.
Publication title: Weather and Forecasting
2024
 | Volume: 39 | Issue: 3
2024
DOI: 10.1175/WAF-D-23-0197.1
Abstract:
This study assesses the accuracy of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) forecasts for clouds within stable and unstable … This study assesses the accuracy of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) forecasts for clouds within stable and unstable environments (thereafter refers as “stable” and “unstable” clouds). This evaluation is conducted by comparing these forecasts against satellite retrievals through a combination of traditional, spatial, and object-based methods. To facilitate this assessment, the Model Evaluation Tools (MET) community tool is employed. The findings underscore the significance of fine-tuning the MET parameters to achieve a more accurate representation of the features under scrutiny. The study’s results reveal that when employing traditional pointwise statistics (e.g., frequency bias and equitable threat score), there is consistency in the results whether calculated from Method for Object-Based Diagnostic Evaluation (MODE)-based objects or derived from the complete fields. Further-more, the object-based statistics offer valuable insights, indicating that COAMPS generally predicts cloud object locations accurately, though the spread of these predicted locations tends to increase with time. It tends to overpredict the object area for unstable clouds while underpredicting it for stable clouds over time. These results are in alignment with the traditional pointwise bias scores for the entire grid. Overall, the spatial metrics provided by the object-based verification methods emerge as crucial and practical tools for the validation of cloud forecasts. © 2024 American Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

Regional Variation in Extratropical North Atlantic Air-Sea Interaction 1960–2020

Author(s):
Latif, M.; Martin, T.; Bielke, I.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 11
2024
DOI: 10.1029/2024GL108174
Abstract:
Air-sea interaction in late boreal winter is studied over the extratropical North Atlantic (NA) during 1960–2020 by examining the relationship between… Air-sea interaction in late boreal winter is studied over the extratropical North Atlantic (NA) during 1960–2020 by examining the relationship between sea-surface temperature (SST) and total turbulent heat flux (THF). The two quantities are positively correlated on interannual timescales over the central-midlatitude and subpolar NA, suggesting the atmosphere on average drives SST and THF variability is independent of SST. On decadal timescales and over the central-midlatitude NA the correlation is negative, suggesting ocean processes on average drive SST and THF variability is sensitive to SST. The correlation is positive over the subpolar NA. There, interannual and decadal THF variability is governed by the North Atlantic Oscillation (NAO). During the major late 20th and early 21st century SST increase in the subpolar NA diminishing oceanic heat loss associated with a weakening NAO was observed. This study suggests that the atmosphere is more sensitive to SST over the central-midlatitude than subpolar NA. © 2024. The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

Recent and projected changes in climate patterns in the Middle East and North Africa (MENA) region

Author(s):
Francis, D.; Fonseca, R.
Publication title: Scientific Reports
2024
 | Volume: 14 | Issue: 1
2024
DOI: 10.1038/s41598-024-60976-w
Abstract:
Observational and reanalysis datasets reveal a northward shift of the convective regions over northern Africa in summer and an eastward shift in winte… Observational and reanalysis datasets reveal a northward shift of the convective regions over northern Africa in summer and an eastward shift in winter in the last four decades, with the changes in the location and intensity of the thermal lows and subtropical highs also modulating the dust loading and cloud cover over the Middle East and North Africa region. A multi-model ensemble from ten models of the Coupled Model Intercomparison Project—sixth phase gives skillful simulations when compared to in-situ measurements and generally captures the trends in the ERA-5 data over the historical period. For the most extreme climate change scenario and towards the end of the twenty-first century, the subtropical highs are projected to migrate poleward by 1.5°, consistent with the projected expansion of the Hadley Cells, with a weakening of the tropical easterly jet in the summer by up to a third and a strengthening of the subtropical jet in winter typically by 10% except over the eastern Mediterranean where the storm track is projected to shift polewards. The length of the seasons is projected to remain about the same, suggesting the warming is likely to be felt uniformly throughout the year. © The Author(s) 2024. more
Application Atmosphere CM-SAF Climate Data Records Validation

Radiative Effect of Two Contrail Cirrus Outbreaks Over Western Europe Estimated Using Geostationary Satellite Observations and Radiative Transfer Calculations

Author(s):
Wang, X.; Wolf, K.; Boucher, O.; Bellouin, N.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 7
2024
DOI: 10.1029/2024GL108452
Abstract:
Estimation of the perturbation to the Earth's energy budget by contrail outbreaks is required for estimating the climate impact of aviation and verify… Estimation of the perturbation to the Earth's energy budget by contrail outbreaks is required for estimating the climate impact of aviation and verifying the climate benefits of proposed contrail avoidance strategies such as aircraft rerouting. Here we identified two successive large-scale contrail outbreaks developing in clear-sky conditions in geostationary and polar-orbiting satellite infrared images of Western Europe lasting from 22–23 June 2020. Their hourly cloud radiative effect, obtained using geostationary satellite cloud retrievals and radiative transfer calculations, is negative or weakly positive during daytime and positive during nighttime. The cumulative energy forcing of the two outbreaks is 7 PJ and −8.5 PJ, with uncertainties of 3 PJ, stemming each from approximately 15–20 flights over periods of 19 and 7 hr, respectively. This study suggests that an automated quantification of contrail outbreak radiative effect is possible, at least for contrails forming in clear sky conditions. © 2024. The Authors. more
Application Atmosphere Climate Data Records EUM-Secr

Quantifying the Impact of Aerosols on Geostationary Satellite Infrared Radiance Simulations: A Study with Himawari-8 AHI

Author(s):
Sun, H.; Wang, D.; Han, W.; Yang, Y.
Publication title: Remote Sensing
2024
 | Volume: 16 | Issue: 12
2024
DOI: 10.3390/rs16122226
Abstract:
Aerosols exert a significant influence on the brightness temperature observed in the thermal infrared (IR) channels, yet the specific contributions of… Aerosols exert a significant influence on the brightness temperature observed in the thermal infrared (IR) channels, yet the specific contributions of various aerosol types remain underexplored. This study integrated the Copernicus Atmosphere Monitoring Service (CAMS) atmospheric composition reanalysis data into the Radiative Transfer for TOVS (RTTOV) model to quantify the aerosol effects on brightness temperature (BT) simulations for the Advanced Himawari Imager (AHI) aboard the Himawari-8 geostationary satellite. Two distinct experiments were conducted: the aerosol-aware experiment (AER), which accounted for aerosol radiative effects, and the control experiment (CTL), in which aerosol radiative effects were omitted. The CTL experiment results reveal uniform negative bias (observation minus background (O-B)) across all six IR channels of the AHI, with a maximum deviation of approximately −1 K. Conversely, the AER experiment showed a pronounced reduction in innovation, which was especially notable in the 10.4 μm channel, where the bias decreased by 0.7 K. The study evaluated the radiative effects of eleven aerosol species, all of which demonstrated cooling effects in the AHI’s six IR channels, with dust aerosols contributing the most significantly (approximately 86%). In scenarios dominated by dust, incorporating the radiative effect of dust aerosols could correct the brightness temperature bias by up to 2 K, underscoring the substantial enhancement in the BT simulation for the 10.4 μm channel during dust events. Jacobians were calculated to further examine the RTTOV simulations’ sensitivity to aerosol presence. A clear temporal and spatial correlation between the dust concentration and BT simulation bias corroborated the critical role of the infrared channel data assimilation on geostationary satellites in capturing small-scale, rapidly developing pollution processes. © 2024 by the authors. more
Atmosphere Method NWP-SAF Software for CDR development

Projected loss of brown macroalgae and seagrasses with global environmental change

Author(s):
Manca, Federica; Benedetti-Cecchi, Lisandro; Bradshaw, Corey J. A.; Cabeza, Mar; Gustafsson, Camilla; Norkko, Alf M.; Roslin, Tomas V.; Thomas, David N.; White, Lydia; Strona, Giovanni
Publication title: Nature Communications
2024
 | Volume: 15 | Issue: 1
2024
DOI: 10.1038/s41467-024-48273-6
Abstract:
Although many studies predict extensive future biodiversity loss and redistribution in the terrestrial realm, future changes in marine biodiversity re… Although many studies predict extensive future biodiversity loss and redistribution in the terrestrial realm, future changes in marine biodiversity remain relatively unexplored. In this work, we model global shifts in one of the most important marine functional groups—ecosystem-structuring macrophytes—and predict substantial end-of-century change. By modelling the future distribution of 207 brown macroalgae and seagrass species at high temporal and spatial resolution under different climate-change projections, we estimate that by 2100, local macrophyte diversity will decline by 3–4% on average, with 17 to 22% of localities losing at least 10% of their macrophyte species. The current range of macrophytes will be eroded by 5–6%, and highly suitable macrophyte habitat will be substantially reduced globally (78–96%). Global macrophyte habitat will shift among marine regions, with a high potential for expansion in polar regions. more
Application Atmosphere CM-SAF Climate Data Records Ocean

Prescriptive analytics for low and high water management in German waterways

Author(s):
Brum, M.; Meißner, D.; Klein, B.; Hohenrainer, J.; Schwanenberg, D.; Patzke, S.
Publication title: At-Automatisierungstechnik
2024
 | Volume: 72 | Issue: 6
2024
DOI: 10.1515/auto-2024-0013
Abstract:
The real-time management of multi-purpose storage reservoirs aims at an efficient operation of existing hydraulic infrastructure. This management proc… The real-time management of multi-purpose storage reservoirs aims at an efficient operation of existing hydraulic infrastructure. This management process can be structured as a prescriptive analytics setup that considers both current and predicted system states to recommend actions and outline potential implications. In application to a reservoir and river system, it combines hydrological modelling components for the system schematization, observations and data assimilation for the identification of the current system state, meteorological and hydrological predictions as well as optimization-based techniques to support decision-making regarding reservoir operations. In this paper, we present the application of such a framework to the short-term management of the Eder and Diemel storage reservoirs. These reservoirs are operated by the German Federal Waterways and Shipping Administration (WSV) with the primary goal to support navigation in the River Weser during low flow periods. In addition, partially conflicting objectives such as flood protection, energy generation and recreation are considered. The implementation includes an explicit consideration of forecast uncertainty and its impact on the decision-making by using probabilistic forecasts in combination with a multi-stage stochastic optimization approach. We demonstrate the applicability of the approach based on low and high water use cases. Special attention is paid on the benefits of the probabilistic forecast in combination with the multi-stage stochastic optimization versus a deterministic setup. It provides an explicit translation of the forecast uncertainty in the decision variables, in this case the reservoir releases helping the operators to better anticipate the range of future release decisions. Furthermore, the stochastic approach is expected to provide more stable decisions in an operational setting, based on more stable forecasts by considering various possible realizations of the future instead of picking a single one, which gets random after 4-5 days. © 2024 Walter de Gruyter GmbH, Berlin/Boston. more
Application Atmosphere CM-SAF Climate Data Records

Predicting September Arctic Sea Ice: A Multimodel Seasonal Skill Comparison

Author(s):
Bushuk, M.; Ali, S.; Bailey, D.A.; Bao, Q.; Batté, L.; Bhatt, U.S.; Blanchard-Wrigglesworth, E.; Blockley, E.; Cawley, G.; Chi, J.; Counillon, F.; Coulombe, P.G.; Cullather, R.I.; Diebold, F.X.; Dirkson, A.; Exarchou, E.; Göbel, M.; Gregory, W.; Guemas, V.; Hamilton, L.; He, B.; Horvath, S.; Ionita, M.; Kay, J.E.; Kim, E.; Kimura, N.; Kondrashov, D.; Labe, Z.M.; Lee, W.; Lee, Y.J.; Li, C.; Li, X.; Lin, Y.; Liu, Y.; Maslowski, W.; Massonnet, F.; Meier, W.N.; Merryfield, W.J.; Myint, H.; Acosta Navarro, J.C.; Petty, A.; Qiao, F.; Schröder, D.; Schweiger, A.; Shu, Q.; Sigmond, M.; Steele, M.; Stroeve, J.; Sun, N.; Tietsche, S.; Tsamados, M.; Wang, K.; Wang, J.; Wang, W.; Wang, Y.; Wang, Y.; Williams, J.; Yang, Q.; Yuan, X.; Zhang, J.; Zhang, Y.
Publication title: Bulletin of the American Meteorological Society
2024
 | Volume: 105 | Issue: 7
2024
DOI: 10.1175/BAMS-D-23-0163.1
Abstract:
This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospec… This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynamical models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance. SIGNIFICANCE STATEMENT: The observed decline of Arctic sea ice extent has created an emerging need for predictions of sea ice on seasonal time scales. This study provides a comparison of September Arctic sea ice seasonal prediction skill across a diverse set of dynamical and statistical prediction models, quantifying the state of the art in the rapidly growing sea ice prediction research community. We find that both dynamical and statistical models can skillfully predict September Arctic sea ice 0–3 months in advance on pan-Arctic, regional, and local spatial scales. Our results demonstrate that there are bright prospects for skillful operational seasonal predictions of Arctic sea ice and highlight a number of crucial prediction system design aspects to guide future improvements. © 2024 American Meteorological Society. more
Application Climate Data Records Cryosphere OSI-SAF

Potential Modulation of Aerosol on Precipitation Efficiency in Southwest China

Author(s):
Zhao, Pengguo; Liu, Xiaoran; Zhao, Chuanfeng
Publication title: Remote Sensing
2024
 | Volume: 16 | Issue: 8
2024
DOI: 10.3390/rs16081445
Abstract:
The aerosol–cloud–precipitation correlation has been a significant scientific topic, primarily due to its remarkable uncertainty. However, the possibl… The aerosol–cloud–precipitation correlation has been a significant scientific topic, primarily due to its remarkable uncertainty. However, the possible modulation of aerosol on the precipitation capacity of clouds has received limited attention. In this study, we utilized multi-source data on aerosol, cloud properties, precipitation, and meteorological factors to investigate the impact of aerosols on precipitation efficiency (PE) in the Sichuan Basin (SCB) and Yun-nan-Guizhou Plateau (YGP), where the differences between terrain and meteorological environment conditions were prominent. In the two study regions, there were significant negative correlations between the aerosol index (AI) and PE in spring, especially in the YGP, while the correlations between the AI and PE in other seasons were not as prominent as in spring. In spring, aerosol significantly inhibited both the liquid water path (LWP) and the ice water path (IWP) in the YGP, but negatively correlated with the IWP and had no significant relationship with the LWP in the SCB. Aerosol inhibited precipitation in the two regions mainly by reducing cloud droplet effective radius, indicating that warm clouds contributed more to precipitation in spring. The suppressive impact of aerosols on precipitation serving as the numerator of PE is greater than that of the cloud water path as the denominator of PE, resulting in a negative correlation between aerosol and PE. The AI–PE relationship is significantly dependent on meteorological conditions in the YGP, but not in the SCB, which may be related to the perennial cloud cover and stable atmosphere in the SCB. In the future, as air quality continues to improve, precipitation efficiency may increase due to the decrease in aerosol concentration, and of course, the spatio-temporal heterogeneity of the aerosol–cloud–precipitation relationship may become more significant. more
Application Atmosphere CM-SAF Climate Data Records

Potential cloud precipitation capacity in typical regions over China

Author(s):
Mo, Shuying; Zhao, Pengguo; Zhao, Chuanfeng; Zhou, Yunjun
Publication title: Atmospheric Research
2024
 | Volume: 311
2024
DOI: 10.1016/j.atmosres.2024.107653
Abstract:
Based on the CLoud, Albedo and RAdiation dataset, AVHRR-based, version 2 (CLARA-A2), Tropical Rainfall Measuring Mission 3B43 (TRMM-3B43), and Europea… Based on the CLoud, Albedo and RAdiation dataset, AVHRR-based, version 2 (CLARA-A2), Tropical Rainfall Measuring Mission 3B43 (TRMM-3B43), and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) reanalysis data, the potential cloud precipitation capacity (PCPA) of typical regions in China is compared, and the relationship between impact factors and PCPA is discussed. Results have suggested that the Tarim Basin (TB) has scarce cloud water resources, while cloud water path (CWP) values are higher in South China (SC) and Sichuan Basin (SB) under the influence of the East Asian monsoon. Moreover, different typical regions of China exhibit varying dependencies on the ice water path (IWP) and liquid water path (LWP). There is a strong correlation between the IWP and precipitation in the Tibet Plateau (TP), Northeast China (NE), SC, and SB. The precipitation in TB demonstrates a more pronounced correlation with the LWP. Through a comparison of the correlation between PCPA and influencing factors in different typical regions of China, it is found that convective available potential energy (CAPE), surface latent heat flux (SLHF), surface sensible heat flux (SSHF), and 0–3 km relative humidity (RH) exhibit stronger correlation with PCPA than 2 m temperature (T2m) and 2–5 km vertical wind shear (SHEAR). Further investigation revealed that the joint effect of CAPE, RH, and SLHF has a pronounced effect on PCPA, particularly during spring and autumn. Additionally, the PCPA of TP exhibits significant dependency on the joint effect of these three influential factors. Furthermore, the ratio of LWP to IWP (RLI) also affects PCPA. In spring and autumn, the PCPA of TB and NC exhibits a positive correlation with RLI, whereas the PCPA of TP, SC, NE, and SB shows a negative correlation with RLI. In summer, the PCPA of TB and SC exhibits a notably negative correlation with RLI. This study deepens the understanding of the formation mechanism of cloud precipitation in typical regions of China, provides the basis for climate forecast and improves the accuracy of weather forecast. more
Application Atmosphere CM-SAF Climate Data Records

Past and future of the Arctic sea ice in High-Resolution Model Intercomparison Project (HighResMIP) climate models

Author(s):
Selivanova, J.; Iovino, D.; Cocetta, F.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 6
2024
DOI: 10.5194/tc-18-2739-2024
Abstract:
We examine the past and projected changes in Arctic sea ice properties in six climate models participating in the High-Resolution Model Intercompariso… We examine the past and projected changes in Arctic sea ice properties in six climate models participating in the High-Resolution Model Intercomparison Project (HighResMIP) in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Within HighResMIP, each of the experiments is run using a reference resolution configuration (consistent with typical CMIP6 runs) and using higher-resolution configurations. The role of horizontal grid resolution in both the atmosphere model component and the ocean model component in reproducing past and future changes in the Arctic sea ice cover is analysed. Model outputs from the coupled historical (hist-1950) and future (highres-future) runs are used to describe the multi-model, multi-resolution representation of the Arctic sea ice and to evaluate the systematic differences (if any) that resolution enhancement causes. Our results indicate that there is not a strong relationship between the representation of sea ice cover and the ocean/atmosphere grids; the impact of horizontal resolution depends rather on the sea ice characteristic examined and the model used. However, the refinement of the ocean grid has a more prominent effect compared to the refinement of the atmospheric one, with eddy-permitting ocean configurations generally providing more realistic representations of sea ice area and sea ice edges. All models project substantial sea ice shrinking: the Arctic loses nearly 95% of sea ice volume from 1950 to 2050. The model selection based on historical performance potentially improves the accuracy of the model projections and predicts that the Arctic will turn ice-free as early as 2047. Along with the overall sea ice loss, changes in the spatial structure of the total sea ice and its partition in ice classes are noticed: the marginal ice zone (MIZ) will dominate the ice cover by 2050, suggesting a shift to a new sea ice regime much closer to the current Antarctic sea ice conditions. The MIZ-dominated Arctic might drive development and modification of model physics and parameterizations in the new generation of general circulation models (GCMs). © 2024 Julia Selivanova et al. more
Application Climate Data Records Cryosphere OSI-SAF Validation

Phytoplankton bloom distribution and succession driven by sea-ice melt in the Kong H kon VII Hav

Author(s):
Lenss, M.; Moreau, S.; Hattermann, T.; Wiktor, J.; Rózanska, M.; Claeys, P.; Brion, N.; Chierici, M.; Fransson, A.; Campbell, K.
Publication title: Elementa
2024
 | Volume: 12 | Issue: 1
2024
DOI: 10.1525/elementa.2023.00122
Abstract:
The existence of ice-edge phytoplankton blooms in the Southern Ocean is well described, yet direct observations of the mechanisms of phytoplankton blo… The existence of ice-edge phytoplankton blooms in the Southern Ocean is well described, yet direct observations of the mechanisms of phytoplankton bloom development following seasonal sea-ice melt remain scarce. This study constrains such responses using biological and biogeochemical datasets collected along a coastal-to-offshore transect that bisects the receding sea-ice zone in the Kong Håkon VII Hav (off the coast of Dronning Maud Land). We documented that the biogeochemical growing conditions for phytoplankton vary on a latitudinal gradient of sea-ice concentration, where increased sea-ice melting creates optimal conditions for growth with increased light availability and potentially increased iron supply. The zones of the study area with the least ice cover were associated with diatom dominance, the greatest chlorophyll a concentrations, net community production, and dissolved inorganic carbon drawdown, as well as lower sea surface fugacity of CO2. Together, these associations imply higher potential for an oceanic CO2 sink due, at least in part, to more advanced bloom phase and/or larger bloom magnitude stemming from a relatively longer period of light exposure, as compared to the more ice-covered zones in the study area. From stable oxygen isotope fractions, sea-ice meltwater fractions were highest in the open ocean zone and meteoric meltwater fractions were highest in the coastal and polynya zones, suggesting that potential iron sources may also change on a latitudinal gradient across the study area. Variable phytoplankton community compositions were related to changing sea-ice concentrations, with a typical species succession from sympagic flagellate species (Pyramimonas sp. and Phaeocystis antarctica) to pelagic diatoms (e.g., Dactyliosolen tenuijunctus) observed across the study area. These results fill a spatiotemporal gap in the Southern Ocean, as sea-ice melting plays a larger role in governing phytoplankton bloom dynamics in the future Southern Ocean due to changing sea-ice conditions caused by anthropogenic global warming. © 2024 University of California Press. All rights reserved. more
Application Climate Data Records Cryosphere OSI-SAF

Parameterizations for global thundercloud corona discharge distributions

Author(s):
Soler, Sergio; Gordillo-Vázquez, Francisco J.; Pérez-Invernón, Francisco J.; Jöckel, Patrick; Neubert, Torsten; Chanrion, Olivier; Reglero, Victor; Østgaard, Nikolai
Publication title: Atmospheric Chemistry and Physics
2024
 | Volume: 24 | Issue: 18
2024
DOI: 10.5194/acp-24-10225-2024
Abstract:
Four parameterizations, distinguishing between land and ocean, have been developed to simulate global distributions of thundercloud streamer corona di… Four parameterizations, distinguishing between land and ocean, have been developed to simulate global distributions of thundercloud streamer corona discharges (also known as Blue LUminous Events or BLUEs) mainly producing bluish optical emissions associated with the second positive system of N2 accompanied by no (or hardly detectable) 777.4 nm light emission. BLUEs occur globally about 12 times less frequently (Soler et al., 2022) than lightning flashes. The four schemes are based on non-linear functions of the cloud-top height (CTH), the product of the convective available potential energy (CAPE) and total precipitation (TP), the product of CAPE and specific cloud liquid water content (CLWC), and the product of CAPE and specific cloud snow water content (CSWC). Considering that thunderstorms occur on hourly timescales, these parameterizations have been tested using hourly ERA5 data (except for CTH, not available in ERA5) for the meteorological variables considered, finding that the proposed BLUE schemes work fine and are consistent with observations by the Atmosphere–Space Interactions Monitor (ASIM). Moreover, the parameterizations have been implemented in a global chemistry–climate model that generates annual and seasonal global distributions for present-day and end of 21st century climate scenarios. Present-day predictions are in reasonable agreement with recent observations by the ASIM. Predictions for the end of the 21st century suggest BLUE occurrence rates that range between 13 % higher (∼ 3 % K−1) and 52 % higher (∼ 13 % K−1) than present-day average occurrences of BLUEs. more
Application Atmosphere CM-SAF Climate Data Records

Optimising Interannual Sea Ice Thickness Variability Retrieved From CryoSat-2

Author(s):
Nab, C.; Mallett, R.; Nelson, C.; Stroeve, J.; Tsamados, M.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 21
2024
DOI: 10.1029/2024GL111071
Abstract:
Satellite radar altimeters like CryoSat-2 estimate sea ice thickness by measuring the return-time of transmitted radar pulses, reflected from the sea … Satellite radar altimeters like CryoSat-2 estimate sea ice thickness by measuring the return-time of transmitted radar pulses, reflected from the sea ice and ocean surface, to measure the radar freeboard. Converting freeboard to thickness requires an assumption regarding the fractional depth of the snowpack from which the radar waves backscatter (Formula presented.). We derive sea ice thickness from CryoSat-2 radar freeboard data with incremental values for (Formula presented.), for the 2010–2021 winter periods. By comparing these to sea ice thickness estimates derived from upward-looking sonar moorings, we find that (Formula presented.) values between 35%–80% result in the best representation of interannual variability observed over first-year ice, reduced to (Formula presented.) 55% over multi-year ice. The underestimating bias in retrievals caused by optimizing this metric can be removed by reducing the waveform retracking threshold to 20%–50%. Our results pave the way for a new generation of ‘partial penetration’ sea ice thickness products from radar altimeters. © 2024. The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF

Oceanic cloud trends during the satellite era and their radiative signatures

Author(s):
Tselioudis, George; Rossow, William B.; Bender, Frida; Oreopoulos, Lazaros; Remillard, Jasmine
Publication title: Climate Dynamics
2024
 | Volume: 62 | Issue: 9
2024
DOI: 10.1007/s00382-024-07396-8
Abstract:
The present study analyzes zonal mean cloud and radiation trends over the global oceans for the past 35 years from a suite of satellite datasets cover… The present study analyzes zonal mean cloud and radiation trends over the global oceans for the past 35 years from a suite of satellite datasets covering two periods. In the longer period (1984–2018) cloud properties come from the ISCCP-H, CLARA-A3, and PATMOS-x datasets and radiative properties from the ISCCP-FH dataset, while for the shorter period (2000–2018) cloud data from MODIS and CloudSat/CALIPSO and radiative fluxes from CERES-EBAF are added. Zonal mean total cloud cover (TCC) trend plots show an expansion of the subtropical dry zone, a poleward displacement of the midlatitude storm zone and a narrowing of the tropical intertropical convergence zone (ITCZ) region over the 1984–2018 period. This expansion of the ‘low cloud cover curtain’ and the contraction of the ITCZ rearrange the boundaries and extents of all major climate zones, producing a more poleward and narrower midlatitude storm zone and a wider subtropical zone. Zonal mean oceanic cloud cover trends are examined for three latitude zones, two poleward of 50 ° and one bounded within 50oS and 50oN, and show upward or near-zero cloud cover trends in the high latitude zones and consistent downward trends in the low latitude zone. The latter dominate in the global average resulting in TCC decreases that range from 0.72% per decade to 0.17% per decade depending on dataset and period. These contrasting cloud cover changes between the high and low latitude zones produce contrasting low latitude cloud radiative warming and high latitude cloud radiative cooling effects, present in both the ISCCP-FH and CERES-EBAF datasets. The global ocean mean trend of the short wave cloud radiative effect (SWCRE) depends on the balance between these contrasting trends, which in the CERES dataset materializes as a SW cloud radiative warming trend of 0.12 W/m2/decade coming from the dominance of the low-latitude positive SWCRE trends while in the ISCCP-FH dataset it manifests as a 0.3 W/m2/decade SW cloud radiative cooling trend coming from the dominance of the high latitude negative SWCRE trends. The CERES cloud radiative warming trend doubles in magnitude to 0.24 W/m2/decade when the period is extended from 2016 to 2022, implying a strong cloud radiative heating in the past 6 years coming from the low latitude zone. more
Atmosphere CM-SAF Climate Data Records Validation

Offline Correction of CMIP6 HighResMIP Simulated Surface Solar Irradiance With 3D Sub-Grid Terrain Radiative Effects

Author(s):
Gu, C.; Huang, A.; Li, X.; Wu, Y.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 10
2024
DOI: 10.1029/2023GL107737
Abstract:
The surface solar irradiance (SSI) is crucial for the land-atmosphere processes and remarkably affected by the topography over the rugged areas. Howev… The surface solar irradiance (SSI) is crucial for the land-atmosphere processes and remarkably affected by the topography over the rugged areas. However, the Coupled Model Intercomparison Project Phase 6 (CMIP6) HighResMIP models adopting the parallel-plane radiative scheme without considering the sub-grid terrain solar radiative effects (3DSTSRE) overestimate the SSI in the rugged areas and the overestimation increases with the sub-grid terrain complexity. To reduce the biases of the SSI simulations, this study offline corrects the SSI simulations of CMIP6 HighResMIP models by a 3DSTSRE scheme. Results show that the SSI biases produced by the HighResMIP models in the rugged regions can be significantly reduced by adopting the 3DSTSRE offline correction, and the improvements increase with the sub-grid terrain complexity, indicating that considering the 3DSTSRE in the climate models to improve the SSI simulations over rugged areas is necessary. © 2024. The Author(s). more
Application Atmosphere CM-SAF Climate Data Records Validation

Multiday Soil Moisture Persistence and Atmospheric Predictability Resulting From Sahelian Mesoscale Convective Systems

Author(s):
Taylor, C.M.; Klein, C.; Harris, B.L.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 20
2024
DOI: 10.1029/2024GL109709
Abstract:
Skill in predicting where damaging convective storms will occur is limited, particularly in the tropics. In principle, near-surface soil moisture (SM)… Skill in predicting where damaging convective storms will occur is limited, particularly in the tropics. In principle, near-surface soil moisture (SM) patterns from previous storms provide an important source of skill at the mesoscale, yet these structures are often short-lived (hours to days), due to both soil drying processes and the impact of new storms. Here, we use satellite observations over the Sahel to examine how the strong, locally negative, SM-precipitation feedback there impacts rainfall patterns over subsequent days. The memory of an initial storm pattern decays rapidly over the first 3–4 days, but a weak signature is still detected in surface observations 10–20 days later. The wet soil suppresses rainfall over the storm track for the first 2–8 days, depending on aridity regime. Whilst the negative SM feedback initially enhances mesoscale rainfall predictability, the transient nature of SM likely limits forecast skill on sub-seasonal time scales. © 2024. The Author(s). more
Application Climate Data Records H-SAF Land

Multi-decadal climate variability and satellite biases have amplified model-observation discrepancies in tropical troposphere warming estimates

Author(s):
Chung, Eui-Seok; Kim, Seong-Joong; Sohn, Byung-Ju; Noh, Young-Chan; John, Viju O.
Publication title: Communications Earth & Environment
2024
 | Volume: 5 | Issue: 1
2024
DOI: 10.1038/s43247-024-01510-8
Abstract:
Abstract Most coupled model simulations substantially overestimate tropical tropospheric warming trends over the satellite era, underminin… Abstract Most coupled model simulations substantially overestimate tropical tropospheric warming trends over the satellite era, undermining the reliability of model-projected future climate change. Here we show that the model-observation discrepancy over the satellite era has arisen in large part from multi-decadal climate variability and residual biases in the satellite record. Analyses indicate that although the discrepancy is closely linked to multi-decadal variability in the tropical Pacific sea surface temperatures, the overestimation remains over the satellite era in model simulations forced by observed time-varying sea surface temperatures with a La Niña-like pattern. Regarding moist thermodynamic processes governing tropical tropospheric warming, however, we find a broad model-observation consistency over a post-war period, suggesting that residual biases in the satellite record may contribute to model-observation discrepancy. These results underscore the importance of sustaining an accurate long-term observing system as well as constraining the model representation of tropical Pacific sea surface temperature change and variability. more
Application Atmosphere NWP-SAF Software for CDR development

Modeling and analysis of rooftop solar potential in highland and lowland territories: Impact of mountainous topography

Author(s):
Ferry, Apolline; Thebault, Martin; Nérot, Boris; Berrah, Lamia; Ménézo, Christophe
Publication title: Solar Energy
2024
 | Volume: 275
2024
DOI: 10.1016/j.solener.2024.112632
Abstract:
The spatial quantification of solar resources is necessary for the deployment of solar systems and must consider the local specificities of territorie… The spatial quantification of solar resources is necessary for the deployment of solar systems and must consider the local specificities of territories, such as complex topography in mountainous areas. This paper presents a methodology for obtaining solar cadastres, based on the Solar Energy on Building Envelopes (SEBE) model incorporated in QGIS and applied to French municipalities. The differences in solar potential between plain and mountain villages are analyzed through the simulation of 92 carefully selected villages located in these two types of regions. The distributions of annual rooftop irradiation per building are obtained for each studied village and approximated with a Johnson’s SU density function. From this arises the definition of two statistical indicators: the mode and the spread at one-third maximum. Main results include a mean decrease in the mode of 189 kWh/m2 and a higher dispersion of 69 kWh/m2 between mountain and plain villages. Two physical indicators, the Sky View Index (SVI) and the Diffuse Fraction Index (DFI), are defined to explain these differences in the shape of the distributions. Higher cloud covers (high DFI) and the presence of distant shading effects (low SVI), caused by terrain relief, explains respectively the smaller modes and the higher dispersion observed in mountainous areas. SVI, DFI and latitude are fed to a multiple linear regression model, allowing the estimation of distributions with smaller computational costs than the developed methodology. Overall, this analysis demonstrates that the characteristics of mountainous environments greatly influence solar resources and should be considered in energy planning. more
Application Atmosphere CM-SAF Climate Data Records

METEOSAT Long-Term Observations Reveal Changes in Convective Organization Over Tropical Africa and Atlantic Ocean

Author(s):
Roca, Rémy; Fiolleau, Thomas; John, Viju O.; Schulz, Jörg
Publication title: Surveys in Geophysics
2024
 | Volume: 45 | Issue: 6
2024
DOI: 10.1007/s10712-024-09862-8
Abstract:
Abstract In the tropics, deep convection, which is often organized into convective systems, plays a crucial role in the water and energy c… Abstract In the tropics, deep convection, which is often organized into convective systems, plays a crucial role in the water and energy cycles by significantly contributing to surface precipitation and forming upper-level ice clouds. The arrangement of these deep convective systems, as well as their individual properties, has recently been recognized as a key feature of the tropical climate. Using data from Africa and the tropical Atlantic Ocean as a case study, recent shifts in convective organization have been analyzed through a well-curated, unique record of METEOSAT observations spanning four decades. The findings indicate a significant shift in the occurrence of deep convective systems, characterized by a decrease in large, short-lived systems and an increase in smaller, longer-lived ones. This shift, combined with a nearly constant deep cloud fraction over the same period, highlights a notable change in convective organization. These new observational insights are valuable for refining emerging kilometer-scale climate models that accurately represent individual convective systems but struggle to realistically simulate their overall arrangement. more
Application Atmosphere Climate Data Records

Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model

Author(s):
Niehaus, H.; Istomina, L.; Nicolaus, M.; Tao, R.; Malinka, A.; Zege, E.; Spreen, G.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 2
2024
DOI: 10.5194/tc-18-933-2024
Abstract:
The presence of melt ponds on Arctic summer sea ice significantly alters its albedo and thereby the surface energy budget and mass balance. Large-scal… The presence of melt ponds on Arctic summer sea ice significantly alters its albedo and thereby the surface energy budget and mass balance. Large-scale observations of melt pond coverage and sea ice albedo are crucial to investigate the role of sea ice for Arctic amplification and its representation in global climate models. We present the new Melt Pond Detection 2 (MPD2) algorithm, which retrieves melt pond, sea ice, and open-ocean fractions as well as surface albedo from Sentinel-3 visible and near-infrared reflectances. In contrast to most other algorithms, our method uses neither fixed values for the spectral albedo of the surface constituents nor an artificial neural network. Instead, it aims for a fully physical representation of the reflective properties of the surface constituents based on their optical characteristics. The state vector X, containing the optical properties of melt ponds and sea ice along with the area fractions of melt ponds and open ocean, is optimized in an iterative procedure to match the measured reflectances and describe the surface state. A major problem in unmixing a compound pixel is that a mixture of half open water and half bright ice cannot be distinguished from a homogeneous pixel of darker ice. In order to overcome this, we suggest constraining the retrieval with a priori information. Initial values and constraint of the surface fractions are derived with an empirical retrieval which uses the same spectral reflectances as implemented in the physical retrieval. © Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License. more
Application Climate Data Records Cryosphere OSI-SAF

Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972-1977

Author(s):
Kolbe, WM; Tonboe, RT; Stroeve, J
Publication title: EARTH SYSTEM SCIENCE DATA
2024
 | Volume: 16 | Issue: 3
2024
DOI: 10.5194/essd-16-1247-2024
Abstract:
The Electrically Scanning Microwave Radiometer (ESMR) instrument onboard the NIMBUS 5 satellite was a one-channel microwave radiometer that measured t… The Electrically Scanning Microwave Radiometer (ESMR) instrument onboard the NIMBUS 5 satellite was a one-channel microwave radiometer that measured the 19.35 GHz horizontally polarized brightness temperature ( T-B ) from 11 December 1972 to 16 May 1977. The original tape archive data in swath projection have recently been made available online by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Even though the ESMR was a predecessor of modern multi-frequency radiometers, there are still parts of modern processing methodologies which can be applied to the data to derive the sea ice extent globally. Here, we have reprocessed the entire dataset using a modern processing methodology that includes the implementation of pre-processing filtering, dynamical tie points, and a radiative transfer model (RTM) together with numerical weather prediction (NWP) for atmospheric correction. We present the one-channel sea ice concentration (SIC) algorithm and the model for computing temporally and spatially varying SIC uncertainty estimates. Post-processing steps include resampling to daily grids, land-spillover correction, the application of climatological masks, the setting of processing flags, and the estimation of sea ice extent, monthly means, and trends. This sea ice dataset derived from the NIMBUS 5 ESMR extends the sea ice record with an important reference from the mid-1970s. To make it easier to perform a consistent analysis of sea ice development over time, the same grid and land mask as used for EUMETSAT's OSI-SAF SMMR-based sea-ice climate data record (CDR) were used for our ESMR dataset. SIC uncertainties were included to further ease comparison to other datasets and time periods. We find that our sea ice extent in the Arctic and Antarctic in the 1970s is generally higher than those available from the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC), which were derived from the same ESMR dataset, with mean differences of 240 000 and 590 000 km 2 , respectively. When comparing monthly sea ice extents, the largest differences reach up to 2 million km 2 . Such large differences cannot be explained by the different grids and land masks of the datasets alone and must therefore also result from the differences in data filtering and algorithms, such as the dynamical tie points and atmospheric correction. The new ESMR SIC dataset has been released as part of the ESA Climate Change Initiative (ESA CCI) program and is publicly available at 10.5285/34a15b96f1134d9e95b9e486d74e49cf .(Tonboe et al., 2023) more
Application Climate Data Records Cryosphere OSI-SAF

Long-Term Variations and Its Driving Factors of the TOA Albedo over the Loess Plateau

Author(s):
Wang, Qianru; Zhang, Shuhua
2024
2024
DOI: 10.1175/JCLI-D-23-0380.1
Abstract:
Solar radiation balances significantly affect Earth’s surface energy balance and climate change. Studying top-of-the-atmosphere (TOA) albedo changes i… Solar radiation balances significantly affect Earth’s surface energy balance and climate change. Studying top-of-the-atmosphere (TOA) albedo changes is of great significance for understanding Earth’s energy budget and atmospheric circulation. The Loess Plateau (LP), located in the middle reaches of the Yellow River in China, is one of the most severely eroded areas in the world. In this paper, long-term remote sensing data were used to analyze the changes in the TOA albedo in the LP from 1982 to 2016. The results showed that the TOA albedo, its atmospheric contribution (AC), and surface contribution (SC) exhibited decreasing trends: −0.0012, −0.0010, and −0.0003 a−1. The spatial pattern of the TOA albedo was similar to AC, which indicates that AC dominates the change in the TOA albedo. We detected driving factors for AC and SC and found that the cloud fraction (CF) was the main driving factor of the AC, whereas the soil moisture (SM) dominated the SC. The driving factors of two typical regions with a significantly decreasing trend in the TOA albedo were also detected. The Mu Us Desert, where vegetation improved significantly, showed a decreasing trend in the TOA albedo, and we found that NDVI was the main driving factor for the change in the SC of the TOA albedo. However, the Eastern Qilian Mountains, where snow cover decreased in recent years, also showed a significant decreasing trend in the TOA albedo; the SC here was mainly driven by the changes in snow cover days (SCD). These results indicate that changes in the surface environment alter the radiation balance. Significance Statement The Loess Plateau in China is one of the most severe cases of soil erosion in the world, and ecological restoration projects have been carried out to recover the fragile ecological environment. Our study was designed to explore changes in the top-of-the-atmosphere (TOA) albedo of the Loess Plateau between 1982 and 2016 using a long time series of multisource satellite products, and driving factors in the atmosphere and at the surface were analyzed. We concluded that the TOA albedo of the Loess Plateau decreased over 35 years, and its atmospheric contribution dominated the change in the TOA albedo. However, the significant ecological improvement in the Loess Plateau, especially in the central vegetation recovery region, such as the Mu Us Desert, was also strongly related to the regional changes in the surface contribution of the TOA albedo. The climate changes had a considerable impact on the eastern branch of the Qilian Mountains in the Qinghai region, where the decline in snow cover days affected the local Alpine meadow ecosystems; therefore, snow cover days also played a decisive role in the local variation of the surface contribution of the TOA albedo. more
Application Atmosphere CM-SAF Climate Data Records Terrestrial

Limited Benefits of Increased Spatial Resolution for Sea Ice in HighResMIP Simulations

Author(s):
Selivanova, J.; Iovino, D.; Vichi, M.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 14
2024
DOI: 10.1029/2023GL107969
Abstract:
State-of-the-art coupled climate models struggle to accurately simulate historical variability and trends of Antarctic sea ice, impacting their reliab… State-of-the-art coupled climate models struggle to accurately simulate historical variability and trends of Antarctic sea ice, impacting their reliability for future projections. Increasing horizontal resolution is expected to improve the representation of coupled atmosphere-ice-ocean processes at high latitudes. Here, we examine the historical changes in the Antarctic sea ice area and volume in High Resolution Model Intercomparison Project simulations against satellite data sets and ocean reanalyzes to assess the benefits of increased spatial resolution. Our results do not show considerable benefits when horizontal resolutions up to 0.25° in the ocean and 25 km in the atmosphere. Limited improvements are reported in the simulated historical sea ice trends, which are nevertheless model-dependent, and associated with the use of model components with more complex sea-ice parameterizations. Given the high computational cost of climate-scale simulations at high spatial resolution, we advocate prioritizing enhancements in sea-ice physics and the interactions among model components in coupled climate simulations. © 2024. The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF Validation

Lessons Learned from the Updated GEWEX Cloud Assessment Database

Author(s):
Stubenrauch, C.J.; Kinne, S.; Mandorli, G.; Rossow, W.B.; Winker, D.M.; Ackerman, S.A.; Chepfer, H.; Di Girolamo, L.; Garnier, A.; Heidinger, A.; Karlsson, K.-G.; Meyer, K.; Minnis, P.; Platnick, S.; Stengel, M.; Sun-Mack, S.; Veglio, P.; Walther, A.; Cai, X.; Young, A.H.; Zhao, G.
Publication title: Surveys in Geophysics
2024
 | Volume: 45 | Issue: 6
2024
DOI: 10.1007/s10712-024-09824-0
Abstract:
Since the first Global Energy and Water Exchanges cloud assessment a decade ago, existing cloud property retrievals have been revised and new retrieva… Since the first Global Energy and Water Exchanges cloud assessment a decade ago, existing cloud property retrievals have been revised and new retrievals have been developed. The new global long-term cloud datasets show, in general, similar results to those of the previous assessment. A notable exception is the reduced cloud amount provided by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Science Team, resulting from an improved aerosol–cloud distinction. Height, opacity and thermodynamic phase determine the radiative effect of clouds. Their distributions as well as relative occurrences of cloud types distinguished by height and optical depth are discussed. The similar results of the two assessments indicate that further improvement, in particular on vertical cloud layering, can only be achieved by combining complementary information. We suggest such combination methods to estimate the amount of all clouds within the atmospheric column, including those hidden by clouds aloft. The results compare well with those from CloudSat-CALIPSO radar–lidar geometrical profiles as well as with results from the International Satellite Cloud Climatology Project (ISCCP) corrected by the cloud vertical layer model, which is used for the computation of the ISCCP-derived radiative fluxes. Furthermore, we highlight studies on cloud monitoring using the information from the histograms of the database and give guidelines for: (1) the use of satellite-retrieved cloud properties in climate studies and climate model evaluation and (2) improved retrieval strategies. © The Author(s) 2024. more
Atmosphere CM-SAF Climate Data Records Validation

Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting

Author(s):
Geer, A.J.
Publication title: Quarterly Journal of the Royal Meteorological Society
2024
 | Volume: 150 | Issue: 763
2024
DOI: 10.1002/qj.4797
Abstract:
Satellite-observed microwave radiances provide information on both surface and atmosphere. For operational weather forecasting, information on atmosph… Satellite-observed microwave radiances provide information on both surface and atmosphere. For operational weather forecasting, information on atmospheric temperature, humidity, cloud, and precipitation is inferred directly using all-sky radiance data assimilation. In contrast, information on the surface state, such as sea-surface temperature (SST) and sea-ice concentration (SIC), is typically provided through third-party retrieval products. Scientifically, this is a sub-optimal use of the observations, and practically it has disadvantages such as time delays of more than 48 h. A better solution is to estimate the surface and atmospheric state jointly from the radiance observations. This has not been possible until now, due to incomplete knowledge of the surface state and the radiative transfer that links this to the observed radiances. A new approach based on an empirical state and an empirical sea-ice surface emissivity model is used here to add sea-ice state estimation, including SIC, to the European Centre for Medium-range Weather Forecasts atmospheric data assimilation system. The sea-ice state is estimated using augmented control variables at the observation locations. The resulting SIC estimates are of good quality and they highlight apparent defects in the existing OCEAN5 sea-ice analysis. The SIC estimates can also be used to track giant icebergs, which may provide a novel maritime application for passive microwave radiances. Further, the SIC estimates should be suitable for onward use in coupled ocean–atmosphere data assimilation. There is also increased coverage of microwave observations in the proximity of sea ice, leading to improved atmospheric forecasts out to day 4 in the Southern Ocean. © 2024 ECMWF. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society. more
Atmosphere Climate Data Records Cryosphere NWP-SAF OSI-SAF Software for CDR development

Initial evaluation of humidity profiles retrieved by the EOS-07 millimetre-wave humidity sounder

Author(s):
Subrahmanyam, K.V.; Kumar, K.K.; Mishra, M.K.; Thapliyal, P.K.; Nayak, R.; Ramana, M.V.; Chauhan, P.
Publication title: Remote Sensing Letters
2024
 | Volume: 15 | Issue: 6
2024
DOI: 10.1080/2150704X.2024.2354130
Abstract:
The vertical profiles of specific humidity in the troposphere measured by the millimetre-wave humidity sounder (MHS) onboard of the Earth Observation … The vertical profiles of specific humidity in the troposphere measured by the millimetre-wave humidity sounder (MHS) onboard of the Earth Observation Satellite (EOS)-07 (Microsoft 2B) are validated using ground-based radiosonde observations during July-August 2023. MHS onboard EOS-07 (hereafter referred as EOS-07/MHS) is a 6-channel cross-track scanning radiometer operating in the 183.31 ± 16.25 GHz band. The EOS-07 observations are used to retrieve three-dimensional specific humidity profiling from 1000 hPa (surface) to 100 hPa (16 km) atmospheric pressure levels with a spatial resolution of 10 km at nadir. The EOS-07/MHS measurements over India have a high correlation coefficient of 0.98 with the radiosonde observations. The mean relative bias is found to be 0.44 ± 0.55 g kg−1 below 350hPa and 2.8 ± 2.3 g kg−1 above 350 hPa. It is also found that above the 350 hPa level, MHS seems to be systematically overestimating the radiosonde measurements. After that, the EOS-07/MHS measurements are used to construct the diurnal variation of humidity during the active phases of the Indian summer monsoon. The observations are consistent with the present understanding of the Indian summer monsoon system. The present results are very encouraging and demonstrate the great potential of EOS-07/MHS observations of humidity for meteorological application, especially in understanding the hydrological cycle. © 2024 Informa UK Limited, trading as Taylor & Francis Group. more
Application Atmosphere NWP-SAF Software for CDR development

Influence of Atmospheric Slant Path on Geostationary Hyperspectral Infrared Sounder Radiance Simulations

Author(s):
Huang, P.; Li, J.; Min, M.; Li, Z.; Di, D.; Anantharaj, V.; Ahn, M.-H.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 23
2024
DOI: 10.1029/2024GL110579
Abstract:
Accurately simulating a geostationary hyperspectral infrared sounder is critical for quantitative applications. Traditional radiation simulations of s… Accurately simulating a geostationary hyperspectral infrared sounder is critical for quantitative applications. Traditional radiation simulations of such instruments often overlook the influence of slant observation geometry by using vertical profile assumption, leading to inadequate simulation accuracy. By using global atmospheric profiles with 1 km spatial resolution, the slant-path effects on brightness temperature simulations are quantified. Experiments indicate that the slant geometry has less impact on longwave brightness temperature simulations and has a substantial impact on middle-wave brightness temperature simulations. It may introduce 0.5 K (or more) uncertainty to brightness temperatures of water vapor absorption channels when the satellite zenith angle is greater than 45°. Considering the slant profile is recommended for quantitative applications of geostationary hyperspectral sounder data, such as sounding retrieval and data assimilation. © 2024. The Author(s). more
Application Atmosphere NWP-SAF Software for CDR development

Inclusion of the radiative effect of deep convective clouds in the Eta model simulations

Author(s):
Campos, Diêgo de Andrade; Chou, Sin Chan; Bottino, Marcus Jorge; Gomes, Jorge Luís; Lyra, André
Publication title: Quarterly Journal of the Royal Meteorological Society
2024
 | Volume: 150 | Issue: 761
2024
DOI: 10.1002/qj.4673
Abstract:
Convective clouds play an important role in the local energy budget by directly interacting with solar and terrestrial radiation. However, radiation p… Convective clouds play an important role in the local energy budget by directly interacting with solar and terrestrial radiation. However, radiation parameterization schemes of atmospheric models generally consider clouds produced from microphysics schemes or some other grid saturation criteria. Deep convective parameterization schemes tend to rain out the convective cloud before the radiation scheme perceives its water load. This may be a source of the positive bias of the incoming solar radiation at the surface. The objective of this work is to include the effects of deep convective clouds in the radiation scheme of the regional Eta model and to evaluate the impacts on the net radiative energy and other meteorological variables. The radiation scheme is the Rapid Radiative Transfer Model. The work is developed in four stages. The positive bias in the incoming solar radiation was diagnosed in the first stage. In the second stage, the parameters of the convective parameterization scheme were modified to increase convective precipitation. In the third stage, the parameters of the microphysics scheme were modified to increase explicit clouds. In the fourth and last stage, in addition to the previous modifications, the condensates from the convective parameterization were input into the radiation scheme. The runs were performed for a period of one summer rainy month with intense convective activity over South America. Including deep convective cloud condensates into the radiation scheme improved the cloud cover, the diurnal cycle of the surface net radiation, and the 2-m temperature. However, the reduction of the net radiation at the surface caused the reduction of the available energy for convective instability and, consequently, the precipitation reduction. The results show the importance of including cumulus cloud water load in the radiative scheme for bias reduction in the radiative energy components. more
Application Atmosphere CM-SAF Climate Data Records

Improving the Modeled Variability Estimates of Offshore Winds in Northern Europe by Nudging ASCAT-Derived Winds

Author(s):
Alonso-De-linaje, N.G.; Hahmann, A.N.; Karagali, I.; Dimitriadou, K.; Badger, M.
Publication title: Journal of Applied Meteorology and Climatology
2024
 | Volume: 63 | Issue: 7
2024
DOI: 10.1175/JAMC-D-23-0102.1
Abstract:
The paper aims to demonstrate how to enhance the accuracy of offshore wind resource estimation, specifically by incorporating near-surface satellite-d… The paper aims to demonstrate how to enhance the accuracy of offshore wind resource estimation, specifically by incorporating near-surface satellite-derived wind observations into mesoscale models. We utilized the Weather Research and Forecasting (WRF) Model and applied observational nudging by integrating ASCAT data over offshore areas to achieve this. We then evaluated the accuracy of the nudged WRF Model simulations by comparing them with data from ocean oil platforms, tall masts, and a wind lidar mounted on a commercial ferry crossing the southern Baltic Sea. Our findings indicate that including satellite-derived ASCAT wind speeds through nudging enhances the correlation and reduces the error of the mesoscale simulations across all validation platforms. Moreover, it consistently outperforms the control and previously published WRF-based wind atlases. Using satellite-derived winds directly in the model simulations also solves the issue of lifting near-surface winds to wind turbine heights, which has been challenging in estimating wind resources at such heights. The comparison of the 1-yr-long simulations with and without nudging reveals intriguing differences in the sign and magnitude between the Baltic and North Seas, which vary seasonally. The pattern highlights a distinct regional pattern at-tributed to regional dynamics, sea surface temperature, atmospheric stability, and the number of available ASCAT samples. © 2024 American Meteorological Society. more
Application Atmosphere Climate Data Records OSI-SAF

Improved rain event detection in commercial microwave link time series via combination with MSG SEVIRI data

Author(s):
Graf, M.; Wagner, A.; Polz, J.; Lliso, L.; Lahuerta, J.A.; Kunstmann, H.; Chwala, C.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 7
2024
DOI: 10.5194/amt-17-2165-2024
Abstract:
The most reliable areal precipitation estimation is usually generated via combinations of different measurements. Path-averaged rainfall rates can be … The most reliable areal precipitation estimation is usually generated via combinations of different measurements. Path-averaged rainfall rates can be derived from commercial microwave links (CMLs), where attenuation of the emitted radiation is strongly related to rainfall rate. CMLs can be combined with data from other rainfall measurements or can be used individually. They are available almost worldwide and often represent the only opportunity for ground-based measurement in data-scarce regions. However, deriving rainfall estimates from CML data requires extensive data processing. The separation of the attenuation time series into rainy and dry periods (rain event detection) is the most important step in this processing and has a high impact on the resulting rainfall estimates. In this study, we investigate the suitability of Meteosat Second Generation Spinning Enhanced Visible and InfraRed Imager (MSG SEVIRI) satellite data as an auxiliary-data-based (ADB) rain event detection method. We compare this method with two time-series-based (TSB) rain event detection methods. We used data from 3748 CMLs in Germany for 4 months in the summer of 2021 and data from the two SEVIRI-derived products PC and PC-Ph. We analyzed all rain event detection methods for different rainfall intensities, differences between day and night, and their influence on the performance of rainfall estimates from individual CMLs. The radar product RADKLIM-YW was used for validation. The results showed that both SEVIRI products are promising candidates for ADB rainfall detection, yielding only slightly worse results than the TSB methods, with the main advantage that the ADB method does not rely on extensive validation for different CML datasets. The main uncertainty of all methods was found for light rain. Slightly better results were obtained during the day than at night due to the reduced availability of SEVIRI channels at night. In general, the ADB methods led to improvements for CMLs performing comparatively weakly using TSB methods. Based on these results, combinations of ADB and TSB methods were developed by emphasizing their specific advantages. Compared to basic and advanced TSB methods, these combinations improved the Matthews correlation coefficient of the rain event detection from 0.49 (or 0.51) to 0.59 during the day and from 0.41 (or 0.50) to 0.55 during the night. Additionally, these combinations increased the number of true-positive classifications, especially for light rainfall compared to the TSB methods, and reduced the number of false negatives while only leading to a slight increase in false-positive classifications. Our results show that utilizing MSG SEVIRI data in CML data processing significantly increases the quality of the rain event detection step, in particular for CMLs which are challenging to process with TSB methods. While the improvement is useful even for applications in Germany, we see the main potential of using ADB methods in data-scarce regions like West Africa where extensive validation is not possible. © Author(s) 2024. more
Application Atmosphere NWC-SAF Software for CDR development

Impact of the Spatio-Temporal Mismatch Between Satellite and In Situ Measurements on Validations of Surface Solar Radiation

Author(s):
Urraca, R.; Lanconelli, C.; Gobron, N.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 10
2024
DOI: 10.1029/2024JD041007
Abstract:
Satellite and in situ sensors do not observe exactly the same measurand. This introduces a mismatch between both types of measurements in the spatial … Satellite and in situ sensors do not observe exactly the same measurand. This introduces a mismatch between both types of measurements in the spatial or temporal. The mismatch differences can be the dominant component in their comparison, so they have to be removed for an adequate validation of satellite products. With this aim, we propose a methodology to characterize the mismatch between satellite and in situ measurements of surface solar radiation, evaluating the impact of the mismatch on validations. The Surface Solar Radiation Data Set—Heliosat (SARAH-2) and the Baseline Surface Radiation Network are used to characterize the spatial and temporal mismatch, respectively. The mismatch differences in both domains are driven by cloud variability. At least 5 years are needed to characterize the mismatch, which is not constant throughout the year due to seasonal and diurnal cloud cover patterns. Increasing the mismatch can artificially improve the validation metrics under some circumstances, but the mismatch must be always minimized for a correct product assessment. Finally, we test two types of up-scaling methods based on SARAH-2 in the validation of degree-scale products. The fully data-driven correction removes all the mismatch effects (systematic and random) but fully propagates SARAH-2 uncertainty to the corrections. The model-based correction only removes the systematic mismatch difference, but it can correct measurements not covered by the high-resolution data set and depends less SARAH-2 uncertainty. © 2024. The Authors. more
Atmosphere CM-SAF Climate Data Records Validation

Impact of Saharan dust outbreaks on short-range weather forecast errors in Europe

Author(s):
Hermes, Kilian; Quinting, Julian; Grams, Christian M.; Hoose, Corinna; Hoshyaripour, Gholam Ali
Publication title: Quarterly Journal of the Royal Meteorological Society
2024
 | Volume: 150 | Issue: 760
2024
DOI: 10.1002/qj.4666
Abstract:
Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operationa… Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operational numerical weather prediction models account for aerosol direct effects by using climatological mean concentrations and neglect indirect effects. This simplification may lead to shortcomings in model forecasts during outbreaks of Saharan dust towards Europe, when climatological mean dust concentrations deviate strongly from actual concentrations. This study investigates errors in model analyses and short-range forecasts during such events. We investigate a pronounced dust event in March 2021 using the pre-operational ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON-ART) with prognostic calculation of dust and the operational European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) model, which deploys a dust climatology. We compare model analysis and forecast with measurements from satellite and in situ instruments. We find that inclusion of prognostic aerosol and direct radiative effects from dust improves forecasts of surface radiation during clear-sky conditions. However, dust-induced cirrus clouds are strongly underestimated, highlighting the importance of representing indirect effects adequately. These findings are corroborated by systematic quantification of forecast errors against satellite measurements. For this we construct an event catalogue with 49 dust days over Central Europe between January 2018 and March 2022. We classify model cells by simulated and observed cloudiness and simulated dustiness in the total atmospheric column. We find significant overestimations of brightness temperature for cases with dust compared with cases without dust. For surface shortwave radiation, we find median overestimations of 6.2% during cloudy conditions with dust optical depth greater than 0.1, however these are not significant compared with cloudy conditions without dust. Our findings show that the pre-operational ICON-ART and the operational IFS model still do not reproduce cloudiness adequately during events with Saharan dust over Central Europe. Missing implementations of prognostic dust, particularly of indirect effects on cloud formation, lead to significant underestimations of cloudiness and potentially overestimations of surface radiation. more
Application Atmosphere CM-SAF Climate Data Records

Impact of climate change on the behaviour of solar radiation using AFR-CORDEX model over West Africa

Author(s):
Ojo, O. S.; Emmanuel, I.; Adedayo, K. D.; Ogolo, E. O.; Adeyemi, B.
Publication title: Meteorology and Atmospheric Physics
2024
 | Volume: 136 | Issue: 5
2024
DOI: 10.1007/s00703-024-01033-z
Abstract:
The study evaluated the impact of climate change on incoming solar radiation (RSDS) in West Africa by comparing observed data from the CMSAF solar pro… The study evaluated the impact of climate change on incoming solar radiation (RSDS) in West Africa by comparing observed data from the CMSAF solar products (SARAH and CLARA-A1) for the period 1983–2019 with simulated data from the AFR-CORDEX models (RegCM-4.7 and CCCma-canRCM4) for the historical period (1983–2004) and various RCP emission scenarios (2.6, 4.5, 8.5) for 2005–2099. The values of the RCP in parentheses signify the level of increasing radiative forcings due to varying emission controls. Assessment metrics like correlation coefficient (R), Taylor Skill Score (TSS), and root mean square errors (RMSE) were employed for comparative analysis on annual and seasonal timescales. The analyses revealed annual mean RSDS intensities of 256.22 for SARAH, 238.53 for CLARA-A1, 270.81 for Historical, 270.26 for RCP 2.6, 255.90 for RCP 4.5, and 271.93 for the RCP 8.5 scenarios in watts per square metres. The TSS analyses showed average agreement values between observed CMSAF and simulated AFR-CORDEX solar radiation with values of 0.8450 and 0.8575 with historical, 0.8750 and 0.8600 with RCP 2.6, 0.9025 and 0.8550 with RCP 4.5, and 0.8675 and 0.8525 with RCP 8.5 scenarios for SARAH and CLARA-A1 respectively. All the metrics showed better agreement with SARAH than CLARA-A1, likely due to the associated cloud influence on CLARA-A1. Notably, the CORDEX-CCCma-canRCM4 model under RCP 4.5 demonstrated the highest accuracy, with an average correlation of 0.82 and a mean TSS of 0.90 against the SARAH reference dataset. The results suggest the AFR-CORDEX model, particularly the CCCma-canRCM4 for RCP 4.5 scenario, could reliably predict solar radiation and inform climate change impacts on solar energy potential in West Africa under moderate emission conditions. more
Atmosphere CM-SAF Climate Data Records Validation

Impact assessment of snow thickness, sea ice density and water density in CryoSat-2-derived sea ice thickness

Author(s):
Sievers, I.; Skourup, H.; Rasmussen, T.A.S.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 12
2024
DOI: 10.5194/tc-18-5985-2024
Abstract:
Sea ice thickness is an essential climate variable, which is often derived from satellite altimetry freeboard estimates, e.g., by CryoSat-2. In order … Sea ice thickness is an essential climate variable, which is often derived from satellite altimetry freeboard estimates, e.g., by CryoSat-2. In order to convert freeboard to sea ice thickness, assumptions are needed for snow thickness, snow density, sea ice density and water density. These parameters are difficult to observe when co-located in time and space with the satellite-derived freeboard measurements. For this reason, most available CryoSat-2 sea ice thickness products rely on climatologies based on outdated observations and empirical values. Model- and observation-based alternatives to sea ice density and snow thickness values have been suggested in recent years, but their combined influence on the freeboard to sea ice thickness conversion has not been analyzed. This study evaluates model-based spatially varying snow thickness, sea ice density and water density with in situ observations and the associated parameters used in the classical CryoSat-2 sea ice thickness production. The observations used for the comparison are a snow thickness product from Ku- and Ka-band radar, sea ice density observations from airborne campaigns and ice core measurements as well as water density from a large variety of observation platforms included in the World Ocean Atlas. Furthermore, this study calculates the mean sea ice thickness differences resulting from substituting the parameters used in a classical CryoSat-2 sea ice thickness product with model-based values. The evaluation shows that the model-derived snow thickness, sea ice density and water density compare better to observations than the associated parameters used in the CryoSat-2 sea ice thickness product. The parameters were compared to the weekly CryoSat-2 sea ice thickness (SIT) product from the Alfred Wegener Institute, which uses similar values for snow thickness, sea ice density and water density to other available CryoSat-2 SIT products. Furthermore, we find that the model-based snow thickness and sea ice density separately lead to the largest sea ice thickness differences but that, to some extent, their differences cancel out when both parameters are used in combination. For the water density, we find the average and maximum sea ice thickness difference to be small in comparison to the sea ice thickness differences introduced by the snow thickness and sea ice density, but this is not negligible, as currently stated in most studies. We find that the origin of the assumption that water density is negligible in the freeboard to sea ice thickness conversion originates from a study investigating the seasonal Arctic sea ice density variability, not taking into account the spacial variability. Based on our findings, we recommend using either a water density climatology or an uncertainty value of 2.6 kg m-3 instead of the commonly used value of 0 to 0.5 kg m-3 in CryoSat-2 freeboard to sea ice thickness conversion. © 2024 Imke Sievers et al. more
Application Climate Data Records Cryosphere OSI-SAF

How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties

Author(s):
Mayer, J.; Mayer, B.; Bugliaro, L.; Meerkötter, R.; Voigt, C.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 17
2024
DOI: 10.5194/amt-17-5161-2024
Abstract:
This study investigates the sensitivity of two brightness temperature differences (BTDs) in the infrared (IR) window of the Spinning Enhanced Visible … This study investigates the sensitivity of two brightness temperature differences (BTDs) in the infrared (IR) window of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) to various cloud parameters in order to understand their information content, with a focus on cloud thermodynamic phase. To this end, this study presents radiative transfer calculations, providing an overview of the relative importance of all radiatively relevant cloud parameters, including thermodynamic phase, cloud-Top temperature (CTT), optical thickness (τ), effective radius (Reff), and ice crystal habit. By disentangling the roles of cloud absorption and scattering, we are able to explain the relationships of the BTDs to the cloud parameters through spectral differences in the cloud optical properties. In addition, an effect due to the nonlinear transformation from radiances to brightness temperatures contributes to the specific characteristics of the BTDs and their dependence on τ and CTT. We find that the dependence of the BTDs on phase is more complex than sometimes assumed. Although both BTDs are directly sensitive to phase, this sensitivity is comparatively small in contrast to other cloud parameters. Instead, the primary link between phase and the BTDs lies in their sensitivity to CTT (or more generally the surface-cloud temperature contrast), which is associated with phase. One consequence is that distinguishing high ice clouds from low liquid clouds is straightforward, but distinguishing mid-level ice clouds from mid-level liquid clouds is challenging. These findings help to better understand and improve the working principles of phase retrieval algorithms. © 2024 Johanna Mayer et al. more
Application Atmosphere CM-SAF Climate Data Records

How strong are the links between global warming and surface solar radiation changes?

Author(s):
Stamatis, M.; Hatzianastassiou, N.; Korras-Carraca, M.-B.; Matsoukas, C.; Wild, M.; Vardavas, I.
Publication title: Climatic Change
2024
 | Volume: 177 | Issue: 10
2024
DOI: 10.1007/s10584-024-03810-6
Abstract:
The aim of this study is to investigate the possible relationship between the recent global warming and the interdecadal changes in incoming surface s… The aim of this study is to investigate the possible relationship between the recent global warming and the interdecadal changes in incoming surface solar radiation (SSR), known as global dimming and brightening (GDB). The analysis is done on a monthly and annual basis on a global scale for the 35-year period 1984–2018 using surface temperature data from the European Centre for Medium-Range Weather Forecasts (ECMWF) v5 (ERA5) reanalysis and SSR fluxes from the FORTH (Foundation for Research and Technology-Hellas) radiative transfer model (RTM). Our analysis shows that on a monthly basis, SSR is correlated with temperature more strongly over global land than ocean areas. According to the RTM calculations, the SSR increased (inducing brightening) over most land areas during 1984–1999, while this increase leveled-off (causing dimming) in the 2000s and strengthened again in the 2010s. These SSR fluctuations are found to affect the global warming rates. Specifically, during the dimming phase in the 2000s, the warming rates across land areas with intense anthropogenic pollution, like Europe and East Asia, slowed down, while during the brightening phases, in the 1980s, 1990s and 2010s, the warming rates were reinforced. Although the magnitude of GDB and the Earth’s surface warming trends are not proportional, indicating that GDB is not the primary driver of the recent global warming, it seems that GDB can affect the warming rates, partly counterbalancing the dominant greenhouse warming during the dimming or accelerating the greenhouse-induced warming during the brightening phases of GDB. © The Author(s), under exclusive licence to Springer Nature B.V. 2024. more
Application Atmosphere CM-SAF Climate Data Records

High-resolution (1km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites

Author(s):
Rains, D.; Trigo, I.; Dutra, E.; Ermida, S.; Ghent, D.; Hulsman, P.; Gómez-Dans, J.; Miralles, D.G.
Publication title: Earth System Science Data
2024
 | Volume: 16 | Issue: 1
2024
DOI: 10.5194/essd-16-567-2024
Abstract:
Surface net radiation (SNR) is a vital input for many land surface and hydrological models. However, most of the current remote sensing datasets of SN… Surface net radiation (SNR) is a vital input for many land surface and hydrological models. However, most of the current remote sensing datasets of SNR come mostly at coarse resolutions or have large gaps due to cloud cover that hinder their use as input in models. Here, we present a downscaled and continuous daily SNR product across Europe for 2018-2019. Long-wave outgoing radiation is computed from a merged land surface temperature (LST) product in combination with Meteosat Second Generation emissivity data. The merged LST product is based on all-sky LST retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard the geostationary Meteosat Second Generation (MSG) satellite and clear-sky LST retrievals from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the polar-orbiting Sentinel-3A satellite. This approach makes use of the medium spatial (approx. 5-7km) but high temporal (30min) resolution, gap-free data from MSG along with the low temporal (2-3d) but high spatial (1km) resolution of the Sentinel-3 LST retrievals. The resulting 1km and daily LST dataset is based on an hourly merging of both datasets through bias correction and Kalman filter assimilation. Short-wave outgoing radiation is computed from the incoming short-wave radiation from MSG and the downscaled albedo using 1km PROBA-V data. MSG incoming short-wave and long-wave radiation and the outgoing radiation components at 1km spatial resolution are used together to compute the final daily SNR dataset in a consistent manner. Validation results indicate an improvement of the mean squared error by ca. 7% with an increase in spatial detail compared to the original MSG product. The resulting pan-European SNR dataset, as well as the merged LST product, can be used for hydrological modelling and as input to models dedicated to estimating evaporation and surface turbulent heat fluxes and will be regularly updated in the future. The datasets can be downloaded from 10.5281/zenodo.8332222 and 10.5281/zenodo.8332128 . © 2024 Dominik Rains et al. more
Application Atmosphere Climate Data Records LSA-SAF

Global evaluation of fast radiative transfer model coefficients for early meteorological satellite sensors

Author(s):
Silveira, B.B.; Turner, E.C.; Vidot, J.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 4
2024
DOI: 10.5194/amt-17-1279-2024
Abstract:
RTTOV (the Radiative Transfer for TOVS code, where TOVS is the TIROS Operational Vertical Sounder) coefficients are evaluated using a large, independe… RTTOV (the Radiative Transfer for TOVS code, where TOVS is the TIROS Operational Vertical Sounder) coefficients are evaluated using a large, independent dataset of 25000 atmospheric model profiles as a robust test of the diverse 83 training profiles typically used. The study is carried out for nine historical satellite instruments: the InfraRed Interferometer Spectrometer D (IRIS-D), Satellite Infrared Spectrometer B (SIRS-B), Medium Resolution Infrared Radiometer (MRIR) and High Resolution Infrared Radiometer (HRIR) for the infrared part of the spectrum, and the Microwave Sounding Unit (MSU), Special Sensor Microwave Imager (SSM/I), Special Sensor Microwave - Humidity (SSM/T-2), Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager/Sounder (SSMI/S) for the microwave. Simulated channel brightness temperatures show similar statistics for both the independent and the 83-profile datasets, confirming that it is acceptable to validate the RTTOV coefficients with the same profiles used to generate the coefficients. Differences between the RTTOV and the line-by-line models are highest in water vapour channels, where mean values can reach up to 0.4±0.2K for the infrared and 0.04±0.13K for the microwave. Examination of the latitudinal dependence of the bias reveals different patterns of variability for similar channels on different instruments, such as the channel centred at 679cm-1 on both IRIS-D and SIRS-B, showing the importance of the specification of the instrumental spectral response functions (ISRFs). Maximum differences of up to several kelvin are associated with extremely non-typical profiles, such as those in polar or very hot regions. © Copyright: more
Atmosphere NWP-SAF Software for CDR development Validation

Four decades of global surface albedo estimates in the third edition of the CM SAF cLoud, Albedo and surface Radiation (CLARA) climate data record

Author(s):
Riihelä, A.; Jääskeläinen, E.; Kallio-Myers, V.
Publication title: Earth System Science Data
2024
 | Volume: 16 | Issue: 2
2024
DOI: 10.5194/essd-16-1007-2024
Abstract:
We present the surface albedo data in the third edition of the CM SAF cLoud, Albedo and surface Radiation (CLARA) data record family. The temporal cov… We present the surface albedo data in the third edition of the CM SAF cLoud, Albedo and surface Radiation (CLARA) data record family. The temporal coverage of this edition is extended from 1979 until the near-present day. The core algorithms and data format remain unchanged from previous editions, but now white- and blue-sky albedo estimates are also available for the first time in CLARA data. We present an overview of the retrieval, followed by an assessment of the accuracy and stability of the data record, based on collocated comparisons with reference surface albedo measurements and intercomparisons with preceding satellite-based albedo data records. Specific attention is paid to addressing the spatial representativeness problem inherent in the "point-to-pixel"validation of satellite-based coarse surface albedo estimates against in situ measurements. We find the CLARA-A3 albedo data to match or improve upon the accuracy and robustness of the predecessor record (CLARA-A2), with good agreement found when compared to in situ measurements. In cases of a large bias, the spatial representativeness of the measurement site typically explains most of the increase. We conclude with a summarizing discussion on the observed strengths and weaknesses of the new data record, including guidance for potential users. The data are available at 10.5676/EUM_SAF_CM/CLARA_AVHRR/V003 (Karlsson et al., 2023b). © Copyright: more
CM-SAF Climate Data Records Land Validation

From Internal Variability to Aerosol Effects: Physical Mechanisms Behind Observed Decadal Trends in Surface Solar Radiation in the Western Pacific Ocean

Author(s):
Correa, L.F.; Folini, D.; Chtirkova, B.; Wild, M.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 18
2024
DOI: 10.1029/2024JD041014
Abstract:
The Pacific Ocean, spanning over 30% of the Earth's surface, provides an ideal setting for studying the surface radiative balance due to its relativel… The Pacific Ocean, spanning over 30% of the Earth's surface, provides an ideal setting for studying the surface radiative balance due to its relatively pristine atmospheric conditions, far from anthropogenic emission sources. In this study we investigated the causes for the decadal trends of surface solar radiation (SSR) observed at eight stations scattered across seven islands in the Western Pacific Ocean, and extrapolated the results to the whole Western Pacific region based on the understanding of physical processes. Our results show a contrast between the causes for SSR trends in the northwestern and in the southwestern Pacific. In the Southwestern Pacific region, changes in cloud cover play a major role in the SSR decadal trends and interannual variability. The cloud cover in these areas is strongly associated with sea surface temperature (SST) anomalies, especially those induced by El Nino Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO). Modes of variability such as ENSO and IPO affect evaporation and convection, impacting the large-scale dynamics of the atmosphere, therefore influencing the distribution of the regions of deep convection. This consecutively impacts the cloud cover on a regional level and therefore SSR. In the Northern Hemisphere, conversely, a strong influence of these modes on cloudiness and SSR was not found. Instead, indirect evidence suggests that anthropogenic aerosol transported from Eastern Asia plays a major role in the decadal SSR trends. These results contribute to an improved understanding of the physical processes relevant for the long-term SSR trends in remote regions. © 2024 The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

Forward operator for polarimetric radio occultation measurements

Author(s):
Hotta, D.; Lonitz, K.; Healy, S.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 3
2024
DOI: 10.5194/amt-17-1075-2024
Abstract:
Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) observations sense the presence of hydrometeor particles along the ray … Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) observations sense the presence of hydrometeor particles along the ray path by measuring the difference of excess phases in horizontally and vertically polarised carrier waves. As a first step towards using these observations in data assimilation and model diagnostics, a forward operator for the GNSS-PRO observable φDP (polarimetric differential phase shift) has been implemented by extending the existing two-dimensional forward operator for radio occultation bending-angle observations. Evaluation of heavy-precipitation cases showed that the implemented forward operator can simulate the observed φDP in synoptic-scale atmospheric river (AR) cases very accurately. For tropical cyclone cases it is more challenging to produce reasonable φDP simulations, due to the high sensitivity of φDP with respect to displacement of the position of the tropical cyclones. It was also found that snow is the dominant contributor to the simulated φDP and that the ability to compute the ray paths in two dimensions is essential to accurately simulate φDP. © Copyright: more
Application Atmosphere NWP-SAF Software for CDR development

First Release of the Optimal Cloud Analysis Climate Data Record from the EUMETSAT SEVIRI Measurements 2004–2019

Author(s):
Bozzo, A.; Doutriaux-Boucher, M.; Jackson, J.; Spezzi, L.; Lattanzio, A.; Watts, P.D.
Publication title: Remote Sensing
2024
 | Volume: 16 | Issue: 16
2024
DOI: 10.3390/rs16162989
Abstract:
Clouds are key to understanding the atmosphere and climate, and a long series of satellite observations provide invaluable information to study their … Clouds are key to understanding the atmosphere and climate, and a long series of satellite observations provide invaluable information to study their properties. EUMETSAT has published Release 1 of the Optimal Cloud Analysis (OCA) Climate Data Record (CDR), which provides a homogeneous time series of cloud properties of up to two overlapping layers, together with uncertainties. The OCA product is derived using the 15 min Spinning Enhanced Visible and Infrared Imager (SEVIRI) measurements onboard Meteosat Second Generation (MSG) in geostationary orbit and covers the period from 19 January 2004 until 31 August 2019. This paper presents the validation of the OCA cloud-top pressure (CTP) against independent lidar-based estimates and the quality assessment of the cloud optical thickness (COT) and cloud particle effective radius (CRE) against a combination of products from satellite-based active and passive instruments. The OCA CTP is in good agreement with the CTP sensed by lidar for low thick liquid clouds and substantially below in the case of high ice clouds, in agreement with previous studies. The retrievals of COT and CRE are more reliable when constrained by solar channels and are consistent with other retrievals from passive imagers. The resulting cloud properties are stable and homogeneous over the whole period when compared against similar CDRs from passive instruments. For CTP, the OCA CDR and the near-real-time OCA products are consistent, allowing for the use of OCA near-real time products to extend the CDR beyond August 2019. © 2024 by the authors. more
CM-SAF Climate Data Records EUM-Secr NWC-SAF NWP-SAF Software for CDR development

Extremes of summer Arctic sea ice reduction investigated with a rare event algorithm

Author(s):
Sauer, J; Demaeyer, J; Zappa, G; Massonnet, F; Ragone, F
Publication title: CLIMATE DYNAMICS
2024
 | Volume: 62 | Issue: 6
2024
DOI: 10.1007/s00382-024-07160-y
Abstract:
Various studies identified possible drivers of extremes of Arctic sea ice reduction, such as observed in the summers of 2007 and 2012, including preco… Various studies identified possible drivers of extremes of Arctic sea ice reduction, such as observed in the summers of 2007 and 2012, including preconditioning, local feedback mechanisms, oceanic heat transport and the synoptic- and large-scale atmospheric circulations. However, a robust quantitative statistical analysis of extremes of sea ice reduction is hindered by the small number of events that can be sampled in observations and numerical simulations with computationally expensive climate models. Recent studies tackled the problem of sampling climate extremes by using rare event algorithms, i.e., computational techniques developed in statistical physics to reduce the computational cost required to sample rare events in numerical simulations. Here we apply a rare event algorithm to ensemble simulations with the intermediate complexity coupled climate model PlaSim-LSG to investigate extreme negative summer pan-Arctic sea ice area anomalies under pre-industrial greenhouse gas conditions. Owing to the algorithm, we estimate return times of extremes orders of magnitude larger than feasible with direct sampling, and we compute statistically significant composite maps of dynamical quantities conditional on the occurrence of these extremes. We find that extremely low sea ice summers in PlaSim-LSG are associated with preconditioning through the winter sea ice-ocean state, with enhanced downward longwave radiation due to an anomalously moist and warm spring Arctic atmosphere and with enhanced downward sensible heat fluxes during the spring-summer transition. As a consequence of these three processes, the sea ice-albedo feedback becomes active in spring and leads to an amplification of pre-existing sea ice area anomalies during summer. more
Application Climate Data Records Cryosphere OSI-SAF

Extension of all-sky radiance assimilation to hyperspectral infrared sounders

Author(s):
Okamoto, K.; Ishibashi, T.; Okabe, I.; Shimizu, H.
Publication title: Quarterly Journal of the Royal Meteorological Society
2024
 | Volume: 150 | Issue: 765
2024
DOI: 10.1002/qj.4883
Abstract:
This study accomplished the all-sky infrared (IR) radiance assimilation of the hyperspectral IR sounders of the IR atmospheric sounding interferometer… This study accomplished the all-sky infrared (IR) radiance assimilation of the hyperspectral IR sounders of the IR atmospheric sounding interferometer in the Japan Meteorological Agency's global system. Essential assimilation procedures, including cloud-dependent quality control, bias correction, and observation-error modeling, were directly adapted from the all-sky assimilation of geostationary satellite imagers in our previous study, without any sophisticated modifications. Data assimilation experiments conducted in different seasons demonstrated that, compared with clear-sky radiance assimilation, the all-sky radiance assimilation of three channels sensitive to mid and upper tropospheric water vapor yielded significant forecast improvements in not only humidity but also temperature, wind, and geopotential height. These improvements originated from more than twofold increments in the number of globally assimilated observations under the all-sky approach and better observation coverages. Increasing the number of assimilated channels to nine further amplified these improvements. The incorporation of an upper tropospheric channel mitigated upper tropospheric humidity biases that were originally exacerbated during three-channel assimilation. These results underscore the broad applicability of the all-sky assimilation approach to various IR instruments. © 2024 Royal Meteorological Society. more
Atmosphere Method NWP-SAF Software for CDR development

Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system

Author(s):
Mile, M.; Guedj, S.; Randriamampianina, R.
Publication title: Geoscientific Model Development
2024
 | Volume: 17 | Issue: 17
2024
DOI: 10.5194/gmd-17-6571-2024
Abstract:
The microwave radiances are key observations, especially over data-sparse regions, for operational data assimilation in numerical weather prediction (… The microwave radiances are key observations, especially over data-sparse regions, for operational data assimilation in numerical weather prediction (NWP). An often applied simplification is that these observations are used as point measurements; however, the satellite field of view may cover many grid points of high-resolution models. Therefore, we examine a solution in high-resolution data assimilation to better account for the spatial representation of the radiance observations. This solution is based on a footprint operator implemented and tested in the variational assimilation scheme of the AROME-Arctic (Application of Research to Operations at MEsoscale - Arctic) limited-area model. In this paper, the design and technical challenges of the microwave radiance footprint operator are presented. In particular, implementation strategies, the representation of satellite field-of-view ellipses, and the emissivity retrieval inside the footprint area are discussed. Furthermore, the simulated brightness temperatures and the sub-footprint variability are analysed in a case study, indicating particular areas where the use of the footprint operator is expected to provide significant added value. For radiances measured by the Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) sensors, the standard deviation of the observation minus background (OmB) departures is computed over a short period in order to compare the statistics of the default and the implemented footprint observation operator. For all operationally used AMSU-A and MHS tropospheric channels, it is shown that the standard deviation of OmB departures is reduced when the footprint operator is applied. For AMSU-A radiances, the reduction is around 1 % for high-peaking channels and about 4 % for low-peaking channels. For MHS data, this reduction is somewhere between 1 %-2 % by the footprint observation operator. © 2024 Máté Mile et al. more
Atmosphere Climate Data Records Method NWP-SAF Software for CDR development

Exploring the characteristics of Fengyun-4A Advanced Geostationary Radiation Imager (AGRI) visible reflectance using the China Meteorological Administration Mesoscale (CMA-MESO) forecasts and its implications for data assimilation

Author(s):
Zhou, Y.; Liu, Y.; Han, W.; Zeng, Y.; Sun, H.; Yu, P.; Zhu, L.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 22
2024
DOI: 10.5194/amt-17-6659-2024
Abstract:
The Advanced Geostationary Radiation Imager (AGRI) on board the Fengyun (FY)-4A geostationary satellite has provided high-spatiotemporal-resolution vi… The Advanced Geostationary Radiation Imager (AGRI) on board the Fengyun (FY)-4A geostationary satellite has provided high-spatiotemporal-resolution visible reflectance data since 12 March 2018. Data assimilation experiments under the framework of observing system simulation experiments have shown the great potential of these data to improve the forecasting skills of numerical weather prediction (NWP) models. To assimilate the AGRI visible reflectance in real-world cases, it is important to evaluate the quality and to quantify the observation errors in these data. In this study, the FY-4A AGRI channel 2 (0.55-0.75 μm) reflectance data (O) were compared with the equivalents (B) derived from the short-term forecasts of the China Meteorological Administration Mesoscale (CMA-MESO) model using the Radiative Transfer for the Television Infrared Observation Satellite Operational Vertical Sounder (RTTOV, v12.3). It is shown that the O-B biases could be used to reveal the abrupt change related to the measurement calibration processes. In general, the O-B departure was positively biased in most cases. Potential causes include the deficiencies of the NWP model, the forward-operator errors, and the unresolved aerosol processes. The relative biases of O-B computed from cloud-free and cloudy pixels were used to correct the systematic biases for the corresponding scenarios over land and sea surfaces separately. In general, the method effectively reduced the O-B biases. Moreover, the bias-correction method based on an ensemble forecast is more robust than a deterministic forecast due to the advantages of the former in dealing with uncertainties in cloud simulations. The findings demonstrate that analyzing the O-B biases has a potential to monitor the performance of the FY-4A AGRI visible instrument and to correct the systematic biases in the observations, which will facilitate the assimilation of these data in conventional data assimilation applications. Copyright: © 2024 Yongbo Zhou et al. more
Application Atmosphere NWP-SAF Software for CDR development

Evapotranspiration and surface energy fluxes across Europe, Africa and Eastern South America throughout the operational life of the Meteosat second generation satellite

Author(s):
Barrios, J.M.; Arboleda, A.; Dutra, E.; Trigo, I.; Gellens-Meulenberghs, F.
Publication title: Geoscience Data Journal
2024
2024
DOI: 10.1002/gdj3.235
Abstract:
The exchange of energy and water fluxes between the Earth's surface and the atmosphere is crucial to a series of processes that impact human life. Not… The exchange of energy and water fluxes between the Earth's surface and the atmosphere is crucial to a series of processes that impact human life. Noteworthy examples are agriculture yields, water availability, intensity and extent of droughts and the ability of ecosystems to provide services to society. The relevance of these processes has motivated the Satellite Application Facility on Land Surface Analysis (LSA SAF) programme to set up an operational framework to estimate—among other variables—evapotranspiration (ET) and surface energy fluxes (SEF) on the basis of observations by the Meteosat Second Generation (MSG) satellite. The LSA SAF programme has recently launched the reprocessing of the ET and SEF datasets on the basis of the most recent version of the algorithm and homogenous forcing datasets. This article features the resulting ET/SEF dataset, a Data Record that encompasses the period from the start of the operational life of the MSG satellite (2004) till 2020 and covers the field of view of the MSG satellite (i.e. Europe, Africa and Eastern South America). Details on the algorithm and the datasets driving the ET/SEF estimates are also provided as well as a quality assessment. © 2024 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. more
Climate Data Records H-SAF LSA-SAF Method Terrestrial

Evaluation of twelve algorithms to estimate suspended particulate matter from OLCI over contrasted coastal waters

Author(s):
Subirade, C.; Jamet, C.; Tran, M.D.; Vantrepotte, V.; Han, B.
Publication title: Optics Express
2024
 | Volume: 32 | Issue: 26
2024
DOI: 10.1364/OE.529712
Abstract:
Remote sensing of suspended particulate matter (SPM) is crucial for water-quality monitoring, as it influences turbidity, light availability, or nutri… Remote sensing of suspended particulate matter (SPM) is crucial for water-quality monitoring, as it influences turbidity, light availability, or nutrient transport. This study aims to provide a comprehensive evaluation of twelve common and well-used SPM models for the Ocean and Land Color Instrument (OLCI) on-board Sentinel-3 satellite, based on different methods and assumptions, including estimation from water-leaving reflectance or proxies, a combination of semi-analytical equations, and machine learning algorithms. The models are tested in three stages: 1) performance assessment on in-situ measurements, 2) matchup exercise with OLCI and 3) visual assessment of satellite SPM products. The models are first tested on the GLORIA dataset (n = 767, 0.21 g.m−3 more
Atmosphere Climate Data Records EUM-Secr Validation

Evaluation of total column water vapour products from satellite observations and reanalyses within the GEWEX Water Vapor Assessment

Author(s):
Trent, T.; Schröder, M.; Ho, S.-P.; Beirle, S.; Bennartz, R.; Borbas, E.; Borger, C.; Brogniez, H.; Calbet, X.; Castelli, E.; Compo, G.P.; Ebisuzaki, W.; Falk, U.; Fell, F.; Forsythe, J.; Hersbach, H.; Kachi, M.; Kobayashi, S.; Kursinski, R.E.; Loyola, D.; Luo, Z.; Nielsen, J.K.; Papandrea, E.; Picon, L.; Preusker, R.; Reale, A.; Shi, L.; Slivinski, L.; Teixeira, J.; Haar, T.V.; Wagner, T.
Publication title: Atmospheric Chemistry and Physics
2024
 | Volume: 24 | Issue: 16
2024
DOI: 10.5194/acp-24-9667-2024
Abstract:
Since 2011, the Global Energy and Water cycle Exchanges (GEWEX) Water Vapor Assessment (GVAP) has provided performance analyses for state-of-the-art r… Since 2011, the Global Energy and Water cycle Exchanges (GEWEX) Water Vapor Assessment (GVAP) has provided performance analyses for state-of-the-art reanalysis and satellite water vapour products to the GEWEX Data and Analysis Panel (GDAP) and the user community in general. A significant component of the work undertaken by G-VAP is to characterise the quality and uncertainty of these water vapour records to (i) ensure full exploitation and (ii) avoid incorrect use or interpretation of results. This study presents results from the second phase of G-VAP, where we have extended and expanded our analysis of total column water vapour (TCWV) from phase 1, in conjunction with updating the G-VAP archive. For version 2 of the archive, we consider 28 freely available and mature satellite and reanalysis data products, remapped to a regular longitude–latitude grid of 2° × 2° and on monthly time steps between January 1979 and December 2019. We first analysed all records for a “common” short period of 5 years (2005–2009), focusing on variability (spatial and seasonal) and deviation from the ensemble mean. We observed that clear-sky daytime-only satellite products were generally drier than the ensemble mean, and seasonal variability/disparity in several regions up to 12 kg m−2 related to original spatial resolution and temporal sampling. For 11 of the 28 data records, further analysis was undertaken between 1988–2014. Within this “long period”, key results show (i) trends between −1.18 ± 0.68 to 3.82 ± 3.94 kg m−2 per decade and −0.39 ± 0.27 to 1.24 ± 0.85 kg m−2 per decade were found over ice-free global oceans and land surfaces, respectively, and (ii) regression coefficients of TCWV against surface temperatures of 6.17 ± 0.24 to 27.02 ± 0.51 % K−1 over oceans (using sea surface temperature) and 3.00 ± 0.17 to 7.77 ± 0.16 % K−1 over land (using surface air temperature). It is important to note that trends estimated within G-VAP are used to identify issues in the data records rather than analyse climate change. Additionally, breakpoints have been identified and characterised for both land and ocean surfaces within this period. Finally, we present a spatial analysis of correlations to six climate indices within the long period, highlighting regional areas of significant positive and negative correlation and the level of agreement among records. © 2024 Tim Trent et al. more
Atmosphere CM-SAF Climate Data Records Validation

Evaluation of the WRF-solar model for 72-hour ahead forecasts of global horizontal irradiance in West Africa: A case study for Ghana

Author(s):
Sawadogo, Windmanagda; Fersch, Benjamin; Bliefernicht, Jan; Meilinger, Stefanie; Rummler, Thomas; Salack, Seyni; Guug, Samuel; Kunstmann, Harald
Publication title: Solar Energy
2024
 | Volume: 271
2024
DOI: 10.1016/j.solener.2024.112413
Abstract:
Accurate global horizontal irradiance (GHI) forecasting is critical for integrating solar energy into the power grid and operating solar power plants.… Accurate global horizontal irradiance (GHI) forecasting is critical for integrating solar energy into the power grid and operating solar power plants. The Weather Research and Forecasting model with its solar radiation extension (WRF-Solar) has been used to forecast solar irradiance in different regions around the world. However, the application of the WRF-Solar model to the prediction of GHI in West Africa, particularly Ghana, has not yet been investigated. The aim of this study is to evaluate the performance of the WRF-Solar model for predicting GHI in Ghana, focusing on three automatic weather stations (Akwatia, Kumasi and Kologo) for the year 2021. We used two one-way nested domains (D1 = 15 km and D2 = 3 km) to investigate the ability of the fully coupled WRF-Solar model to forecast GHI up to 72-hour  ahead under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF high-resolution operational forecasts. Our findings reveal that the WRF-Solar model performs better under clear skies than cloudy skies. Under clear skies, Kologo performed best in predicting 72-hour GHI, with a first day nRMSE of 9.62 %. However, forecasting GHI under cloudy skies at all three sites had significant uncertainties. Additionally, WRF-Solar model is able to reproduce the observed GHI diurnal cycle under high AOD conditions in most of the selected days. This study enhances the understanding of the WRF-Solar model’s capabilities and limitations for GHI forecasting in West Africa, particularly in Ghana. The findings provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management in the region. more
Atmosphere CM-SAF Climate Data Records Validation

Evaluation of Summertime Passive Microwave and Reanalysis Sea-Ice Concentration in the Central Arctic

Author(s):
Song, K.; Minnett, P.J.
Publication title: Earth and Space Science
2024
 | Volume: 11 | Issue: 1
2024
DOI: 10.1029/2023EA003214
Abstract:
Passive microwave (PM) observations have been used to monitor ice retreat in the Arctic. However, various PM sea ice concentration (SIC) algorithms ar… Passive microwave (PM) observations have been used to monitor ice retreat in the Arctic. However, various PM sea ice concentration (SIC) algorithms are prone to underestimate ice fraction during summer. We evaluated the accuracy of 2002–2019 low SICs in the Central Arctic Ocean of four PM products from the University of Bremen, the National Snow and Ice Data Center (NSIDC), and the Ocean and Sea Ice Satellite Application Facility (OSI SAF), and two reanalysis data sets from the fifth generation of European ReAnalysis (ERA5) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). Three reference fields were used: (a) Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) true-color composites, (b) MODIS sea ice extent, and (c) multi-product ensemble (MPE-SIC) comprising the median of collocated SIC estimates. Our results indicate SICs derived from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) high frequency channels have the best accuracy. Reanalysis SICs indicate almost identical patterns as their remote sensing inputs. The assessment shows that the Bremen (+1.06%) and NSIDC (+0.99%) SICs are higher than the median field, while the OSI-401 (−6.65%) and OSI-408 (−4.64%) have negative mean deviations. The mean error of MODIS-derived SIC (−0.80%) is smaller than PM SICs. These small mean values belie wide distributions of values. The correlation coefficients of pairs of time series of Low sea-Ice Concentration Index range from 0.37 to 0.96. © 2024 The Authors. Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union. more
Climate Data Records Cryosphere OSI-SAF Validation

Evaluation of Downward Shortwave Radiation Products Over the Loess Plateau

Author(s):
Tian, Qianqian; Zhang, Shuhua; Duan, Weili; Ming, Guanghui
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2024
 | Volume: 17
2024
DOI: 10.1109/JSTARS.2023.3346032
Abstract:
Downward shortwave radiation (DSR) is a key component of the surface energy budget, influencing atmospheric circulation and climate change. DSR produc… Downward shortwave radiation (DSR) is a key component of the surface energy budget, influencing atmospheric circulation and climate change. DSR products derived from remote sensing observations or generated from reanalysis systems are commonly used as inputs for ecohydrological and climate models. The Loess Plateau is severely affected by soil erosion and has experienced frequent extreme weather events in recent years. Therefore, an accurate DSR product is crucial for accurately simulating climate change and surface-atmosphere processes on the Loess Plateau. In this study, newly released satellite DSR products CLouds, Albedo and Radiation Edition 3 data (CLARA-A3) and Moderate Resolution Imaging Spectroradiometer land surface Downward Shortwave Radiation Version 6.1 data (MCD18A1 V6.1), along with the reanalysis product Land component of the Fifth Generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5-Land), were evaluated over the Loess Plateau and its surrounding areas. Intraday, daily, monthly, and seasonal DSR were evaluated against ground measurements which were collected from five observation networks. CLARA-A3 outperformed MCD18A1 and ERA5-Land on both monthly and daily scales. The root-mean-square error for monthly (daily) DSR from CLARA-A3, ERA5-Land, and MCD18A1 were 19.31 (31.3) W/m2, 25.36 (39.74) W/m2, and 25.03 (46.14) W/m2, respectively. The study explored potential factors contributing to significant errors in DSR products. Results indicated that snow cover was one possible factor influencing the error in MCD18A1, and CLARA-A3 exhibited greater sensitivity to terrain influence compared to ERA5-Land and MCD18A1. The findings can be the reference for selecting DSR products over the Loess Plateau. more
Atmosphere CM-SAF Climate Data Records Validation

Evaluating the First Year On-Orbit Radiometric Calibration Performance of GIIRS Onboard Fengyun-4B

Author(s):
Wang, W.; Huang, P.; Xu, N.; Li, J.; Di, D.; Zhang, Z.; Gao, L.; Ji, Z.; Min, M.
Publication title: IEEE Geoscience and Remote Sensing Letters
2024
 | Volume: 21
2024
DOI: 10.1109/LGRS.2024.3422976
Abstract:
The geostationary interferometric infrared sounder (GIIRS) onboard the Fengyun-4B (FY-4B) is the first operational geostationary hyperspectral infrare… The geostationary interferometric infrared sounder (GIIRS) onboard the Fengyun-4B (FY-4B) is the first operational geostationary hyperspectral infrared (IR) sounder. This study analyzes the first-year FY-4B/GIIRS on-orbit calibration performance by comparing it to the collocated IR atmospheric sounder interferometer (IASI) observations and radiative transfer (RT) simulations. The results reveal that the mid-wave IR (MWIR) channels had a slightly larger calibration bias compared to the long-wave IR (LWIR) channels. However, the operational FY-4B/GIIRS showed improved performance compared to the experimental FY-4A/GIIRS. Furthermore, this study also found that most channels exhibited negligible annual and weak diurnal variations in calibration bias. However, there was a significant degradation in the LWIR channels ( more
Climate Data Records NWP-SAF Software for CDR development

Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals

Author(s):
Wernecke, Andreas; Notz, Dirk; Kern, Stefan; Lavergne, Thomas
Publication title: The Cryosphere
2024
 | Volume: 18 | Issue: 5
2024
DOI: 10.5194/tc-18-2473-2024
Abstract:
The net Arctic sea-ice area (SIA) can be estimated from the sea-ice concentration (SIC) by passive microwave measurements from satellites. To be a tru… The net Arctic sea-ice area (SIA) can be estimated from the sea-ice concentration (SIC) by passive microwave measurements from satellites. To be a truly useful metric, for example of the sensitivity of the Arctic sea-ice cover to global warming, we need, however, reliable estimates of its uncertainty. Here we retrieve this uncertainty by taking into account the spatial and temporal error correlations of the underlying local sea-ice concentration products. As 1 example year, we find that in 2015 the average observational uncertainties of the SIA are 306 000 km2 for daily estimates, 275 000 km2 for weekly estimates, and 164 000 km2 for monthly estimates. The sea-ice extent (SIE) uncertainty for that year is slightly smaller, with 296 000 km2 for daily estimates, 261 000 km2 for weekly estimates, and 156 000 km2 for monthly estimates. These daily uncertainties correspond to about 7 % of the 2015 sea-ice minimum and are about half of the spread in estimated SIA and SIE from different passive microwave SIC products. This shows that random SIC errors play a role in SIA uncertainties comparable to inter-SIC-product biases. We further show that the September SIA, which is traditionally the month with the least amount of Arctic sea ice, declined by 105 000±9000 km2 a−1 for the period from 2002 to 2017. This is the first estimate of a SIA trend with an explicit representation of temporal error correlations. more
Climate Data Records Cryosphere OSI-SAF Validation

End-to-end learning of representative PV capacity factors from aggregated PV feed-ins

Author(s):
Zech, Matthias; von Bremen, Lueder
Publication title: Applied Energy
2024
 | Volume: 361
2024
DOI: 10.1016/j.apenergy.2024.122923
Abstract:
Energy system models rely on accurate weather information to capture the spatio-temporal characteristics of renewable energy generation. Whereas energ… Energy system models rely on accurate weather information to capture the spatio-temporal characteristics of renewable energy generation. Whereas energy system models are often solved with high abstraction of the actual energy system, meteorological data from reanalysis or satellites provides rich gridded information of the weather. The mapping from meteorological data to renewable energy generation usually relies on major assumptions as for solar photovoltaic energy the photovoltaic module parameters. In this study, we show that these assumptions can lead to large deviations between the reported and estimated energy, as shown for the case of photovoltaic energy in Germany. We propose a novel gradient-based end-to-end framework that can learn local representative photovoltaic capacity factors from aggregated PV feed-ins. As part of the end-to-end framework, we compare physical and neural network model formulations to obtain a functional mapping from meteorological data to photovoltaic capacity factors. We show that all the methods developed have better performance than commonly used reference methods. Both physical and neural network models have much better performance than reference models whereas operational use cases may prefer the neural network due to higher accuracy while interpretable, physical models are more suited to academic settings. more
Atmosphere CM-SAF Climate Data Records Validation

Enhanced light absorption by ambient brown carbon aerosols in the eastern Himalayas

Author(s):
Arun, B. S.; Gogoi, Mukunda M.; Deshmukh, Dhananjay Kumar; Hegde, Prashant; Boreddy, Suresh Kumar Reddy; Borgohain, Arup; Babu, S. Suresh
Publication title: Environmental Science: Atmospheres
2024
 | Volume: 4 | Issue: 7
2024
DOI: 10.1039/D4EA00021H
Abstract:
This study investigates the light absorption properties of organic aerosols in PM10 collected at a high-altitude location (2700 m a.s.l.) in the easte… This study investigates the light absorption properties of organic aerosols in PM10 collected at a high-altitude location (2700 m a.s.l.) in the eastern Himalayas from March 2019 to February 2020. The analysis reveals an enhanced light-absorbing signature of methanol-soluble brown carbon (MeS-BrC) extracts compared to water-soluble brown carbon (WS-BrC) within the optical wavelength range of 300–700 nm. MeS-BrC exhibits approximately twice the absorption compared to that of WS-BrC at 365 nm. The highest light absorption coefficients at 365 nm (babs365) are observed during spring for both MeS-BrC (9 ± 4.6 Mm−1) and WS-BrC (5.9 ± 4.2 Mm−1). Notably, the contribution of absorption from the water-insoluble fraction is relatively higher during the summer monsoon (45.2 ± 19.5%) and autumn (44.1 ± 18.4%). A significant linear relationship between WSOC and WS-BrC as well as OC and MeS-BrC at 365 nm suggests similar sources for BrC and WSOC (OC). Furthermore, significant positive correlations of babs365 (WS-BrC and MeS-BrC) with the water-soluble fraction of total nitrogen (WSTN) and organic nitrogen (WSON) indicate the presence of nitrogenous organic chromophores playing a crucial role in BrC absorption during spring and autumn. The mass absorption efficiency at 365 nm (MAE365) reveals that BrC in spring aerosols (WS-BrC: 1.5 ± 0.6 m2 g−1; MeS-BrC: 2.07 ± 0.8 m2 g−1) absorbs UV-visible light more efficiently compared to aerosols collected during other seasons. The enhanced MAE365 during spring resulted the highest simple forcing efficiency of 8.7 ± 3.9 W g−1 and 10.8 ± 5.2 W g−1 for WS-BrC and MeS-BrC, respectively, for a specific solar geometry and surface properties. This may be attributed to intense biomass burning followed by atmospheric processing of organic aerosols in the aqueous phase. These findings confirm the significant role of anthropogenic sources in enhancing BrC light absorption and radiative effects in this highly sensitive region of the eastern Himalayas. Such insights are crucial for devising effective strategies for mitigating climate change impacts in the Himalayan ecosystem. more
Application Atmosphere CM-SAF Climate Data Records

Effects of clouds and aerosols on downwelling surface solar irradiance nowcasting and short-Term forecasting

Author(s):
Papachristopoulou, K.; Fountoulakis, I.; Bais, A.F.; Psiloglou, B.E.; Papadimitriou, N.; Raptis, I.-P.; Kazantzidis, A.; Kontoes, C.; Hatzaki, M.; Kazadzis, S.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 7
2024
DOI: 10.5194/amt-17-1851-2024
Abstract:
Solar irradiance nowcasting and short-Term forecasting are important tools for the integration of solar plants into the electricity grid. Understandin… Solar irradiance nowcasting and short-Term forecasting are important tools for the integration of solar plants into the electricity grid. Understanding the role of clouds and aerosols in those techniques is essential for improving their accuracy. In this study, we introduce improvements in the existing nowcasting and short-Term forecasting operational systems SENSE (Solar Energy Nowcasting System) and NextSENSE achieved by using a new configuration and by upgrading cloud and aerosol inputs, and we also investigate the limitations of evaluating such models using surface-based sensors due to cloud effects. We assess the real-Time estimates of surface global horizontal irradiance (GHI) produced by the improved SENSE2 operational system at high spatial and temporal resolution (gkm, 15gmin) for a domain including Europe and the Middle East-North Africa (MENA) region and the short-Term forecasts of GHI (up to 3gh ahead) produced by the NextSENSE2 system against ground-based measurements from 10 stations across the models' domain for a whole year (2017). Results for instantaneous (every 15gmin) comparisons show that the GHI estimates are within ±50gWgm-2 (or ±10g%) of the measured GHI for 61g% of the cases after the implementation of the new model configuration and a proposed bias correction. The bias ranges from-12 to 23gWgm-2 (or from-2g% to 6.1g%) with a mean value of 11.3gWgm-2 (2.3g%). The correlation coefficient is between 0.83 and 0.96 and has a mean value of 0.93. Statistics are significantly improved when integrating on daily and monthly scales (the mean bias is 3.3 and 2.7gWgm-2, respectively). We demonstrate that the main overestimation of the SENSE2 GHI is linked with the uncertainties of the cloud-related information within the satellite pixel, while relatively low underestimation, linked with aerosol optical depth (AOD) forecasts (derived from the Copernicus Atmospheric Monitoring Service-CAMS), is reported for cloudless-sky GHI. The highest deviations for instantaneous comparisons are associated with cloudy atmospheric conditions, when clouds obscure the sun over the ground-based station. Thus, they are much more closely linked with satellite vs. ground-based comparison limitations than the actual model performance. The NextSENSE2 GHI forecasts based on the cloud motion vector (CMV) model outperform the persistence forecasting method, which assumes the same cloud conditions for future time steps. The forecasting skill (FS) of the CMV-based model compared to the persistence approach increases with cloudiness (FS is up to g1/4g20g%), which is linked mostly to periods with changes in cloudiness (which persistence, by definition, fails to predict). Our results could be useful for further studies on satellite-based solar model evaluations and, in general, for the operational implementation of solar energy nowcasting and short-Term forecasting, supporting solar energy production and management. © 2024 Copernicus Publications. All rights reserved. more
Application Atmosphere CM-SAF Climate Data Records

Earth's Sea Ice Radiative Effect From 1980 to 2023

Author(s):
Duspayev, A.; Flanner, M.G.; Riihelä, A.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 14
2024
DOI: 10.1029/2024GL109608
Abstract:
Sea ice cools Earth by reducing its absorbed solar energy. We combine radiative transfer modeling with satellite-derived surface albedo, sea ice, and … Sea ice cools Earth by reducing its absorbed solar energy. We combine radiative transfer modeling with satellite-derived surface albedo, sea ice, and cloud distributions to quantify the top-of-atmosphere sea ice radiative effect (SIRE). Averaged over 1980–2023, Arctic and Antarctic SIREs range from −0.64 to −0.86 W m−2 and −0.85 to −0.98 W m−2, respectively, with different cloud data sets and assumptions of climatological versus annually-varying clouds. SIRE trends, however, are relatively insensitive to these assumptions. Arctic SIRE has weakened quasi-linearly at a rate of 0.04–0.05 W m−2 decade−1, implying a 21%–27% reduction in the reflective power of Arctic sea ice since 1980. Antarctic sea ice exhibited a regime change in 2016, resulting in 2016–2023 Antarctic and global SIRE being 0.08–0.12 and 0.22–0.27 W m−2 weaker, respectively, relative to 1980–1988. Global sea ice has therefore lost 13%–15% of its planetary cooling effect since the early/mid 1980s, and the implied global sea ice albedo feedback is 0.24–0.38 W m−2 K−1. © 2024. The Author(s). more
Application CM-SAF Climate Data Records Cryosphere OSI-SAF

Dynamic and thermodynamic processes related to sea-ice surface melt advance in the Laptev Sea and East Siberian Sea

Author(s):
Liang, H.; Zhou, W.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 8
2024
DOI: 10.5194/tc-18-3559-2024
Abstract:
Arctic summer sea ice has shrunk considerably in recent decades. This study investigates springtime sea-ice surface melt onset in the Laptev Sea and E… Arctic summer sea ice has shrunk considerably in recent decades. This study investigates springtime sea-ice surface melt onset in the Laptev Sea and East Siberian Sea, which are key seas along the Northeast Passage. Instead of region-mean melt onset, we define an index of melt advance, which is the areal percentage of a sea that has experienced sea-ice surface melting before the end of May. Four representative scenarios of melt advance in the region are identified. Each scenario is accompanied by a combination of distinct patterns between atmospheric circulation, atmospheric thermodynamic state, sea-ice cover (polynya activity), and surface energy balance in May. In general, concurrent with faster melt advance are a warmer and wetter atmosphere, less sea-ice cover, and surface energy gains in spring. Melt advance can be potentially used in the practical seasonal prediction of summer sea-ice cover. This study suggests the interannual and interdecadal flexibility of spring circulation in the lower troposphere and the significance of seasonal evolution in the Arctic. © Copyright: more
Application Climate Data Records Cryosphere OSI-SAF

Drivers of summer Arctic sea-ice extent at interannual time scale in CMIP6 large ensembles revealed by information flow

Author(s):
Docquier, D.; Massonnet, F.; Ragone, F.; Sticker, A.; Fichefet, T.; Vannitsem, S.
Publication title: Scientific Reports
2024
 | Volume: 14 | Issue: 1
2024
DOI: 10.1038/s41598-024-76056-y
Abstract:
Arctic sea-ice extent has strongly decreased since the beginning of satellite observations in the late 1970s. While several drivers are known to be im… Arctic sea-ice extent has strongly decreased since the beginning of satellite observations in the late 1970s. While several drivers are known to be implicated, their respective contribution is not fully understood. Here, we apply the Liang-Kleeman information flow method to five different large ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over the 1970-2060 period to investigate the extent to which fluctuations in winter sea-ice volume, air temperature and ocean heat transport drive changes in subsequent summer Arctic sea-ice extent. This allows us to go beyond classical correlation analyses. Results show that air temperature is the most important controlling factor of summer sea-ice extent at interannual time scale, and that winter sea-ice volume and Atlantic Ocean heat transport play a secondary role. If we replace air temperature by net shortwave and downward longwave radiations, we find that the sum of influences from both radiations is almost similar to the air temperature influence, with the longwave radiation being dominant in driving changes in summer sea-ice extent. Finally, we find that the influence of air temperature is more prominent during periods of large sea-ice reduction and that this temperature influence has overall increased since 1970. © The Author(s) 2024. more
Application Climate Data Records Cryosphere OSI-SAF

Description of FIO-ESM version 2.1 and evaluation of its sea ice simulations

Author(s):
Shu, Q; Qiao, FL; Liu, JP; Bao, Y; Song, ZY
Publication title: OCEAN MODELLING
2024
 | Volume: 187
2024
DOI: 10.1016/j.ocemod.2023.102308
Abstract:
To improve Arctic sea ice simulations by the First Institute of Oceanography-Earth System Model (FIO-ESM), the model version has been updated from FIO… To improve Arctic sea ice simulations by the First Institute of Oceanography-Earth System Model (FIO-ESM), the model version has been updated from FIO-ESM v2.0 to FIO-ESM v2.1 by upgrading its sea ice component from Los Alamos Sea-Ice Model (CICE) version 4.0 (CICE4.0) to CICE6.0, and improving the ice-ocean heat exchange process from a two-equation boundary condition parameterization to a more realistic three-equation boundary condition parameterization. Numerical experiments show that the underestimation of Arctic summer sea ice extent (SIE) in FIO-ESM v2.0 is significantly improved by the model enhancements. The root mean square error of the simulated Arctic September SIE during 1979-2014 is reduced from 2.9 million to 0.7 million km2. Nevertheless, the biases of Antarctic SIE increase following the model version update. FIO-ESM v2.1 performs well for the simulations of surface air temperature, sea surface temperature, Atlantic Meridional Overturning Circulation, and Arctic SIE; however, it overestimates summer SIE in the Antarctic. Furthermore, future projections based on FIO-ESM v2.1 indicate that the first ice-free Arctic summer will occur in the 2050s and the 2040s under SSP2-4.5 and SSP5-8.5, respectively. more
Climate Data Records Cryosphere OSI-SAF Validation

Development of New Models Using Empirical Modeling of Global Solar Radiation and Its Application in Usak City, Turkey

Author(s):
Ersan, Rabia; Külcü, Recep
Publication title: Tekirdağ Ziraat Fakültesi Dergisi
2024
 | Volume: 21 | Issue: 5
2024
DOI: 10.33462/jotaf.1512442
Abstract:
With this study, 12 empirical models in the literature, 2 new models developed within the scope of this study, SARAH and CMSAF satellite-based models,… With this study, 12 empirical models in the literature, 2 new models developed within the scope of this study, SARAH and CMSAF satellite-based models, COSMO and ERA5 re-analysis solar radiation data sets in the PVGIS database were compared in order to detect the monthly average global solar radiation coming to the horizontal plane of Usak province. New models developed within the scope of the study; it uses the region's temperature, cloudiness coefficient and sunset hour angle. In comparison of the datas within the scope of the study; coefficient of determination (R²), mean percent error (MPE), deviation error (MBE), root mean square error (RMSE), absolute relative error (ARE) parameters were used. As a result of the evaluations, the method that most successfully predicts the global solar radiation values of Usak province was tried to be determined. According to the monthly evaluation of the models; It was determined that 14 models and satellite-based systems have absolute relative error values below 5% in March-April-May-June, September-October and December. The most accurate estimates were realized for May in 16 of 18 different estimation methods used in the study. The coefficient of determination of empirical models and PVGIS data sets was above 0.97. When the success of the models was evaluated according to the RMSE values, It was determined that the logarithmic based Model 14 (0.90058 RMSE, 0.98327 R2, -1.079894 MPE, -0.05033 MBE, 0.185628 t) which was obtained by using the sunset hour angle and the max-min temperature difference developed within the scope of this study, made the most accurate estimations. COSMO data from spatial data (1.053134 RMSE, 0.979036 R2, -1.196348 MPE, -0.25105 MBE, 0.8141 t) made successful estimations, but the accuracy of the COSMO data was lower than the data estimated by Model 14. It was concluded that used the models and satellite-based systems were generally successful. As a result, In the studies to be carried out for the global solar radiation forecast of Usak province. It has been concluded that Model 14 developed within the scope of the study can be used in precise calculations and COSMO data from PVGIS datas can be used in more superficial or pre-feasibility studies. more
Atmosphere CM-SAF Climate Data Records Validation

Daily sunshine grids for Austria since 1961 – combining station and satellite observations for a multi-decadal climate-monitoring dataset

Author(s):
Hiebl, Johann; Bourgeois, Quentin; Tilg, Anna-Maria; Frei, Christoph
Publication title: Theoretical and Applied Climatology
2024
 | Volume: 155 | Issue: 8
2024
DOI: 10.1007/s00704-024-05103-5
Abstract:
Grid datasets of sunshine duration at high spatial resolution and extending over many decades are required for quantitative applications in regional c… Grid datasets of sunshine duration at high spatial resolution and extending over many decades are required for quantitative applications in regional climatology and environmental change (e.g., modelling of droughts and snow/ice covers, evaluation of clouds in numerical models, mapping of solar energy potentials). We present a new gridded dataset of relative (and derived absolute) sunshine duration for Austria at a grid spacing of 1 km, extending back until 1961 at daily time resolution. Challenges in the dataset construction were consistency issues in the available station data, the scarcity of long time series, and the high variation of cloudiness in the study region. The challenges were addressed by special efforts to correct evident breaks in the station series and by adopting an analysis method, which combines station data with satellite data. The methodology merges the data sources non-contemporaneously, using statistical patterns distilled over a short period, which allowed involving satellite data even for the early part of the study period. The resulting fields contain plausible mesoscale structures, which could not be resolved by the station network alone. On average, the analyses explain 47% of the spatial variance in daily sunshine duration at the stations. Evaluation revealed a slight systematic underestimation (− 1.5%) and a mean absolute error of 9.2%. The average error is larger during winter, at high altitudes, and around the 1990s. The dataset exhibits a conditional bias, which can lead to considerable systematic errors (up to 15%) when calculating sunshine-related climate indices. more
Atmosphere CM-SAF Climate Data Records Validation

Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0

Author(s):
Ho-Hagemann, H.T.M.; Maurer, V.; Poll, S.; Fast, I.
Publication title: Geoscientific Model Development
2024
 | Volume: 17 | Issue: 21
2024
DOI: 10.5194/gmd-17-7815-2024
Abstract:
Interactions and feedback between components of the Earth system can have a significant impact on local and regional climate and its changes due to gl… Interactions and feedback between components of the Earth system can have a significant impact on local and regional climate and its changes due to global warming. These effects can be better represented by regional Earth system models (RESMs) than by traditional stand-alone atmosphere and ocean models. Here, we present the RESM Geesthacht Coupled cOAstal model SysTem (GCOAST)-AHOI v2.0, which includes a new atmospheric component, the regional climate model Icosahedral Nonhydrostatic (ICON)-CLM, which is coupled to the Nucleus for European Modelling of the Ocean (NEMO) and the hydrological discharge model HD via the OASIS3-MCT coupler. The GCOAST-AHOI model has been developed and applied for climate simulations over the EURO-CORDEX domain. Two 11-year simulations from 2008 to 2018 of the uncoupled ICON-CLM and GCOAST-AHOI give similar results for seasonal and annual means of near-surface air temperature, precipitation, mean sea level pressure, and wind speed at a height of 10 m. However, GCOAST-AHOI has a cold sea surface temperature (SST) bias of 1-2 K over the Baltic and North seas that is most pronounced in the winter and spring seasons. A possible reason for the cold SST bias could be the underestimation of the downward shortwave radiation at the surface of ICON-CLM with the current model settings. Despite the cold SST bias, GCOAST-AHOI was able to capture other key variables well, such as those mentioned above. Therefore, GCOAST-AHOI can be a useful tool for long-term climate simulations over the EURO-CORDEX domain. Compared to the stand-alone NEMO3.6 forced by ERA5 and ORAS5 boundary forcing, GCOAST-AHOI has positive biases in sea ice fraction and salinity but negative biases in runoff, which need to be investigated further in the future to improve the coupled simulations. The new OASIS3-MCT coupling interface OMCI implemented in ICON-CLM adds the possibility of coupling ICON-CLM to an external ocean model and an external hydrological discharge model using OASIS3-MCT instead of the YAC (Yet Another Coupler). Using OMCI, it is also possible to set up a RESM with ICON-CLM and other ocean and hydrology models possessing the OASIS3-MCT interface for other regions, such as the Mediterranean Sea. Copyright: © 2024 Ha Thi Minh Ho-Hagemann et al. more
Application Atmosphere CM-SAF Climate Data Records Validation

Convection-Permitting ICON-LAM Simulations for Renewable Energy Potential Estimates Over Southern Africa

Author(s):
Chen, S.; Poll, S.; Hendricks Franssen, H.-J.; Heinrichs, H.; Vereecken, H.; Goergen, K.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 6
2024
DOI: 10.1029/2023JD039569
Abstract:
Renewable energy is recognized in Africa as a means for climate change mitigation, but also to provide access to electricity in sub-Saharan Africa, wh… Renewable energy is recognized in Africa as a means for climate change mitigation, but also to provide access to electricity in sub-Saharan Africa, where three-quarters of the global population without electricity resides. Reliable and highly resolved renewable energy potential (REP) information is indispensable to support power plants expansion. Existing atmospheric data sets over Africa that are used for REP estimates are often characterized by data gaps, or coarse resolution. With the aim to overcome these challenges, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON-NWP) model in its Limited Area Mode (ICON-LAM) is implemented and run over southern Africa in a hindcast dynamical downscaling setup at a convection-permitting 3.3 km horizontal resolution. The simulation time span covers contrasting solar and wind weather years from 2017 to 2019. To assess the suitability of the novel simulations for REP estimates, the simulated hourly 10 m wind speed (sfcWind) and hourly surface solar irradiance (rsds) are extensively evaluated against a large compilation of in situ observations, satellite, and composite data products. ICON-LAM reproduces the spatial patterns, temporal evolution, the variability, and absolute values of sfcWind sufficiently well, albeit with a slight overestimation and a mean bias (mean error (ME)) of 1.12 m s−1 over land. Likewise the simulated rsds with an ME of 50 W m−2 well resembles the observations. This new ICON simulation data product will be the basis for ensuing REP estimates that will be compared with existing lower resolution data sets. © 2024. The Authors. more
Application Atmosphere CM-SAF Climate Data Records Validation

Contrasting extremely warm and long-lasting cold air anomalies in the North Atlantic sector of the Arctic during the HALO-(AC)3 campaign

Author(s):
Walbröl, A.; Michaelis, J.; Becker, S.; Dorff, H.; Ebell, K.; Gorodetskaya, I.; Heinold, B.; Kirbus, B.; Lauer, M.; Maherndl, N.; Maturilli, M.; Mayer, J.; Müller, H.; Neggers, R.A.J.; Paulus, F.M.; Röttenbacher, J.; Rückert, J.E.; Schirmacher, I.; Slättberg, N.; Ehrlich, A.; Wendisch, M.; Crewell, S.
Publication title: Atmospheric Chemistry and Physics
2024
 | Volume: 24 | Issue: 13
2024
DOI: 10.5194/acp-24-8007-2024
Abstract:
How air masses transform during meridional transport into and out of the Arctic is not well represented by numerical models. The airborne field campai… How air masses transform during meridional transport into and out of the Arctic is not well represented by numerical models. The airborne field campaign HALO-(AC)3 applied the High Altitude and Long-range Research Aircraft (HALO) within the framework of the collaborative research project on Arctic amplification (AC)3 to address this question by providing a comprehensive observational basis. The campaign took place from 7 March to 12 April 2022 in the North Atlantic sector of the Arctic, a main gateway of atmospheric transport into and out of the Arctic. Here, we investigate to which degree the meteorological and sea ice conditions during the campaign align with the long-term climatology (1979–2022). For this purpose, we use the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis v5 (ERA5), satellite data, and measurements at Ny-Ålesund, including atmospheric soundings. The observations and reanalysis data revealed two distinct periods with different weather conditions during HALO-(AC)3: the campaign started with a warm period (11–20 March 2022) where strong southerly winds prevailed that caused poleward transport of warm and moist air masses, so-called moist and warm air intrusions (WAIs). Two WAI events were identified as atmospheric rivers (ARs), which are narrow bands of strong moisture transport. These warm and moist air masses caused the highest measured 2 m temperatures (5.5 °C) and daily precipitation rates (42 mm d−1) at Ny-Ålesund for March since the beginning of the record (1993). Over the sea ice northwest of Svalbard, ERA5 indicated record-breaking rainfall. After the passage of a strong cyclone on 21 March 2022, a cold period followed. Northerly winds advected cold air into the Fram Strait, causing marine cold air outbreaks (MCAOs) until the end of the campaign. This second phase included one of the longest MCAO events found in the ERA5 record (19 d). On average, the entire campaign period was warmer than the climatological mean due to the strong influence of the ARs. In the Fram Strait, the sea ice concentration was well within the climatological variability over the entire campaign duration. However, during the warm period, a large polynya opened northeast of Svalbard, untypical for this season. Compared to previous airborne field campaigns focusing on the evolution of (mixed-phase) clouds, a larger variety of MCAO conditions was observed during HALO-(AC)3. In summary, air mass transport into and out of the Arctic was more pronounced than usual, providing exciting prospects for studying air mass transformation using HALO-(AC)3 © Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License. more
Application Climate Data Records Cryosphere OSI-SAF

Coastal wind retrievals from corrected QuikSCAT Normalized Radar Cross Sections

Author(s):
Grieco, G.; Portabella, M.; Stoffelen, A.; Verhoef, A.; Vogelzang, J.; Zanchetta, A.; Zecchetto, S.
Publication title: Remote Sensing of Environment
2024
 | Volume: 308
2024
DOI: 10.1016/j.rse.2024.114179
Abstract:
A new correction scheme named “noise regularization”, aiming at mitigating land contamination in SeaWinds scatterometer coastal Normalized Radar Cross… A new correction scheme named “noise regularization”, aiming at mitigating land contamination in SeaWinds scatterometer coastal Normalized Radar Cross Sections (σ0s) is presented. The scheme is based on an analytical Cumulative Distribution Function (CDF) matching technique. Its efficacy is demonstrated in a semi-enclosed basin of the Mediterranean Sea, both in the σ0 and wind field domains. Wind biases along the coasts disappear and the sampling improves by a factor of 3 within the first 10 km from the coastline. This figure is likely underestimated because of a non-optimal tuning of the a-posteriori quality control tests in coastal areas. Finally, wind retrievals are validated against those from a collocated Synthetic Aperture Radar (SAR) image acquired by the Envisat Advanced SAR (ASAR) offshore Norway. The agreement is very good in both speed and direction, and opens new perspectives on the use of SAR as a validation tool of coastal winds. © 2024 The Author(s) more
Atmosphere Climate Data Records NWP-SAF OSI-SAF Software for CDR development Validation

Comparing the simulated influence of biomass burning plumes on low-level clouds over the southeastern Atlantic under varying smoke conditions

Author(s):
Baró Pérez, A.; Diamond, M.S.; Bender, F.A.-M.; Devasthale, A.; Schwarz, M.; Savre, J.; Tonttila, J.; Kokkola, H.; Lee, H.; Painemal, D.; Ekman, A.M.L.
Publication title: Atmospheric Chemistry and Physics
2024
 | Volume: 24 | Issue: 8
2024
DOI: 10.5194/acp-24-4591-2024
Abstract:
Biomass burning plumes are frequently transported over the southeast Atlantic (SEA) stratocumulus deck during the southern African fire season (June-O… Biomass burning plumes are frequently transported over the southeast Atlantic (SEA) stratocumulus deck during the southern African fire season (June-October). The plumes bring large amounts of absorbing aerosols and enhanced moisture, which can trigger a rich set of aerosol-cloud-radiation interactions with climatic consequences that are still poorly understood. We use large-eddy simulation (LES) to explore and disentangle the individual impacts of aerosols and moisture on the underlying stratocumulus clouds, the marine boundary layer (MBL) evolution, and the stratocumulus-to-cumulus transition (SCT) for three different meteorological situations over the southeast Atlantic during August 2017. For all three cases, our LES shows that the SCT is driven by increased sea surface temperatures and cloud-top entrainment as the air is advected towards the Equator. In the LES model, aerosol indirect effects, including impacts on drizzle production, have a small influence on the modeled cloud evolution and SCT, even when aerosol concentrations are lowered to background concentrations. In contrast, local semi-direct effects, i.e., aerosol absorption of solar radiation in the MBL, cause a reduction in cloud cover that can lead to a speed-up of the SCT, in particular during the daytime and during broken cloud conditions, especially in highly polluted situations. The largest impact on the radiative budget comes from aerosol impacts on cloud albedo: the plume with absorbing aerosols produces a total average 3gd of simulations. We find that the moisture accompanying the aerosol plume produces an additional cooling effect that is about as large as the total aerosol radiative effect. Overall, there is still a large uncertainty associated with the radiative and cloud evolution effects of biomass burning aerosols. A comparison between different models in a common framework, combined with constraints from in situ observations, could help to reduce the uncertainty. © 2024 Alejandro Baro Perez et al. more
Application Atmosphere CM-SAF Climate Data Records

Clouds dissipate quickly during solar eclipses as the land surface cools

Author(s):
Trees, Victor J. H.; de Roode, Stephan R.; Wiltink, Job I.; Meirink, Jan Fokke; Wang, Ping; Stammes, Piet; Siebesma, A. Pier
Publication title: Communications Earth & Environment
2024
 | Volume: 5 | Issue: 1
2024
DOI: 10.1038/s43247-024-01213-0
Abstract:
Clouds affected by solar eclipses could influence the reflection of sunlight back into space and might change local precipitation patterns. Satellite … Clouds affected by solar eclipses could influence the reflection of sunlight back into space and might change local precipitation patterns. Satellite cloud retrievals have so far not taken into account the lunar shadow, hindering a reliable spaceborne assessment of the eclipse-induced cloud evolution. Here we use satellite cloud measurements during three solar eclipses between 2005 and 2016 that have been corrected for the partial lunar shadow together with large-eddy simulations to analyze the eclipse-induced cloud evolution. Our corrected data reveal that, over cooling land surfaces, shallow cumulus clouds start to disappear at very small solar obscurations (~15%). Our simulations explain that the cloud response was delayed and was initiated at even smaller solar obscurations. We demonstrate that neglecting the disappearance of clouds during a solar eclipse could lead to a considerable overestimation of the eclipse-related reduction of net incoming solar radiation. These findings should spur cloud model simulations of the direct consequences of sunlight-intercepting geoengineering proposals, for which our results serve as a unique benchmark. more
Application Atmosphere Climate Data Records LSA-SAF NWC-SAF OSI-SAF Ocean Terrestrial

Climatic precipitation efficiency and its dependence on environmental factors over the Sichuan Basin and adjacent regions, Southwest China

Author(s):
Mo, Shuying; Zhao, Pengguo; Zhao, Chuanfeng; Xiao, Hui; Wang, Yuting; Zhang, Peiwen; Wen, Xiaohang; Qiu, Shuang
Publication title: Theoretical and Applied Climatology
2024
 | Volume: 155 | Issue: 5
2024
DOI: 10.1007/s00704-024-04835-8
Abstract:
Based on satellite observation and reanalysis data, basic features of cloud water and precipitation and the dependence of precipitation efficiency (PE… Based on satellite observation and reanalysis data, basic features of cloud water and precipitation and the dependence of precipitation efficiency (PE) on environmental factors over the Sichuan Basin and adjacent regions are investigated. Results found that the spatiotemporal distribution characteristics of precipitation and cloud water over the Sichuan Basin and adjacent regions are consistent. The liquid water path (LWP) and ice water path (IWP) in the Sichuan Basin (SCB) are richer than the West Sichuan Plateau (WSP) and Yunnan-Guizhou Plateau (YGP), and the contribution of IWP to precipitation in Sichuan Basin and adjacent regions is greater than that of LWP. Furthermore, the results indicate that PE has the most significant dependence on the low-tropospheric relative humidity (RH) and the convective available potential energy (CAPE) over the Sichuan Basin and adjacent regions. Higher RH and CAPE contribute to a larger PE in the Sichuan Basin. The CAPE has a positive effect on the PE, which indicates that PE is directly affected by precipitation convection, mainly due to the special topography of the Sichuan Basin and adjacent regions, leading to frequent convective activities. The ratio of LWP to IWP (RLI) affects PE. The RLI decreases with the increase of IWP, leading to an increase in PE. RLI is negatively correlated with PE, which further indicates that ice water clouds have a more significant impact on PE over the Sichuan Basin and adjacent regions. Through this study, we can enhance our understanding of the formation processes, spatio-temporal structures, and evolutionary mechanisms of cloud precipitation in the Sichuan Basin and its adjacent areas. This is crucial for unraveling the dynamics of atmospheric water cycle, climate change processes, and optimizing the utilization efficiency of cloud water resources. more
Application Atmosphere CM-SAF Climate Data Records

Climate data integration into wheat performance evaluation reveals large inter-varietal responses

Author(s):
Raymond, Joanna; Penfield, Steven; Lovett, Andrew; Mackay, Ian; Philpott, Haidee; Simpson, Conor John Christopher; Dorling, Stephen
Publication title: Environmental Research: Food Systems
2024
 | Volume: 2 | Issue: 1
2024
DOI: 10.1088/2976-601X/ad90e4
Abstract:
There is an urgent need to adapt crop breeding strategies to boost resilience in the face of a growing food demand and a changing climate. Achieving t… There is an urgent need to adapt crop breeding strategies to boost resilience in the face of a growing food demand and a changing climate. Achieving this requires an understanding of how weather and climate variability impacts crop growth and development. Using the United Kingdom (UK) as an example, we evaluate changes in the UK agroclimate and analyse how these have influenced domestic wheat production. Here we quantify spatial and temporal variability and changes in weather and climate across growing seasons over the last four decades (1981–2020). Drawing on variety trial data, we then use statistical modelling to explore the interaction between genotype and agroclimate variation. We show that changes in the UK agroclimate present both risks, and opportunities for wheat growers, depending on location. From 1981–2020, in Wales, the West Midlands, large parts of the North West, and Northern Ireland, there was an overall increase in frost risk in early spring of 0.15 additional frost days per year, whilst in the east early frost risk decreased by up to 0.29 d per year. Meanwhile, over the period 1987–2020, surface incoming shortwave radiation during grainfill increased in the east by up to 13% but decreased in Western areas by up to 15%. We show significant inter-varietal differences in yield responses to growing degree days, heavy rainfall, and the occurrence of late frost. This highlights the importance of evaluating variety-climate interactions in variety trial analyses, and in climate-optimised selection of crops and varieties by growers. This work provides guidance for future research on how climate change is affecting the UK agroclimate and resulting impacts on winter cereal production. more
Application Atmosphere CM-SAF Climate Data Records Terrestrial

Characterization and Validation of ECOSTRESS Sea Surface Temperature Measurements at 70 m Spatial Scale

Author(s):
Wethey, D.S.; Weidberg, N.; Woodin, S.A.; Vazquez-Cuervo, J.
Publication title: Remote Sensing
2024
 | Volume: 16 | Issue: 11
2024
DOI: 10.3390/rs16111876
Abstract:
The ECOSTRESS push-whisk thermal radiometer on the International Space Station provides the highest spatial resolution temperature retrievals over the… The ECOSTRESS push-whisk thermal radiometer on the International Space Station provides the highest spatial resolution temperature retrievals over the ocean that are currently available. It is a precursor to the future TRISHNA (CNES/ISRO), SBG (NASA), and LSTM (ESA) 50 to 70 m scale missions. Radiance transfer simulations and triple collocations with in situ ocean observations and NOAA L2P geostationary satellite ocean temperature retrievals were used to characterize brightness temperature biases and their sources in ECOSTRESS Collection 1 (software Build 6) data for the period 12 January 2019 to 31 October 2022. Radiometric noise, non-uniformities in the focal plane array, and black body temperature dynamics were characterized in ocean scenes using L1A raw instrument data, L1B calibrated radiances, and L2 skin temperatures. The mean brightness temperature biases were −1.74, −1.45, and −1.77 K relative to radiance transfer simulations in the 8.78, 10.49, and 12.09 µm wavelength bands, respectively, and skin temperatures had a −1.07 K bias relative to in situ observations. Cross-track noise levels range from 60 to 600 mK and vary systematically along the focal plane array and as a function of wavelength band and scene temperature. Overall, radiometric uncertainty is most strongly influenced by cross-track noise levels and focal plane non-uniformity. Production of an ECOSTRESS sea surface temperature product that meets the requirements of the SST community will require calibration methods that reduce the biases, noise levels, and focal plane non-uniformities. © 2024 by the authors. more
Application Climate Data Records NWP-SAF OSI-SAF Ocean Software for CDR development

Changes in cloudiness contribute to changing seasonality in the Baltic Sea region

Author(s):
Post, Piia; Aun, Margit
Publication title: Oceanologia
2024
 | Volume: 66 | Issue: 1
2024
DOI: 10.1016/j.oceano.2023.11.004
Abstract:
In the Baltic Sea region, a significant increase in solar radiation has been detected during the past half-century. Changes in shortwave irradiance ar… In the Baltic Sea region, a significant increase in solar radiation has been detected during the past half-century. Changes in shortwave irradiance are associated with atmospheric transparency and cloudiness parameters like cloud fraction and albedo. One of the most important reasons for day-to-day changes in cloudiness is the synoptic-scale atmospheric circulation; thus, we look for reasons for solar radiation trends due to changes in atmospheric circulation. We analysed regional time series and trends from satellite-based cloud climate data record CLARA-A2 for the Baltic Sea region in 1982–2018. As the rise in solar radiation depends on the seasonally averaged values of total fractional cloud cover (CFC), surface incoming shortwave radiation (SIS) and occurrences of circulation types were analysed. We show that the shift in seasonality connected to the earlier accumulated sums of SIS is at least partly explained by the changes in synoptic-scale atmospheric circulation. more
Application Atmosphere CM-SAF Climate Data Records

Can satellite products monitor solar brightening in Europe?

Author(s):
Urraca, Ruben; Trentmann, Jörg; Pfeifroth, Uwe; Gobron, Nadine
Publication title: Remote Sensing of Environment
2024
 | Volume: 315
2024
DOI: 10.1016/j.rse.2024.114472
Abstract:
Satellite products provide the best way to monitor the solar radiation reaching the Earth’s surface on a global scale. However, their capability to mo… Satellite products provide the best way to monitor the solar radiation reaching the Earth’s surface on a global scale. However, their capability to monitor solar radiation trends needs to be constantly evaluated. This depends on their temporal stability and the accurate representation of all processes driving solar radiation. This study evaluates these aspects by comparing and cross-comparing different solar radiation products (ERA5, CAMS-RAD 4.6, SARAH-3, CLARA-A3, CERES-EBAF 4.2) against in-situ measurements over Europe. All products show a moderate positive bias over Europe but strong differences in their root mean squared deviation (RMSD) related to their different cloud transmittance models. Geostationary-based products (SARAH-3, CAMS-RAD 4.6) provide the smallest RMSD closely followed by CLARA-A3, whereas ERA5 shows a large RMSD due to random errors in cloud transmittance. All products show an increase in surface solar radiation, or brightening, over the last 40 years over Europe, but the magnitude of the trends and their spatiotemporal variability differ between products. Despite finding temporal inhomogeneities in some products, the different trends are mostly due to different aerosol modeling approaches implemented by each product. Both SARAH-3 (+2.3 W/m2/decade, 2001–22) and CERES-EBAF 4.2 (+2.2 W/m2/decade, 2001–22) provide the most consistent trends compared to in-situ data, showing that after stabilizing in the late 2000s, brightening is particularly recovering in Western Europe. In-situ measurements show a reduction of aerosol optical depth from 2001 to 2022 that has been accentuated in the last 10 years, particularly in Western Europe. This would be consistent with the hypothesis that brightening recovery is driven by an aerosol reduction, though other analyses suggest that clouds also play a role in this recovery. More work is needed to understand the contribution of aerosols to solar radiation trends and the exact aerosol effects represented by each solar radiation product. more
Atmosphere CM-SAF Climate Data Records Validation

Benchmark of estimated solar irradiance data at high latitude locations

Author(s):
Nygard Riise, Heine; Moe Nygård, Magnus; Lupton Aarseth, Bjørn; Dobler, Andreas; Berge, Erik
Publication title: Solar Energy
2024
 | Volume: 282
2024
DOI: 10.1016/j.solener.2024.112975
Abstract:
Estimated solar irradiances from CAMS, PVGIS SARAH-2, Solargis, Meteonorm, PVGIS ERA5, and NASA POWER are benchmarked against measurements conducted a… Estimated solar irradiances from CAMS, PVGIS SARAH-2, Solargis, Meteonorm, PVGIS ERA5, and NASA POWER are benchmarked against measurements conducted at 34 ground stations in Norway at latitudes between 58 and 76°N. We find that the data products that mainly rely on high-resolution, geostationary satellite images, i.e., CAMS, PVGIS SARAH-2, and Solargis, have higher accuracy with lower relative Mean Absolute Error (rMAE) and relative Mean Bias Error. By dividing the stations in distinct categories, such as above 65°N, snow-affected and horizon-shaded, challenges with irradiance estimation that are common in Norway and at high latitudes in general are highlighted and discussed. The accuracy of the data products is dependent on latitude, and by excluding stations above 65°N, the median rMAE of the different data products improves 3.2 – 9.4 %abs compared to the median rMAE when including all stations, depending on data product. Similarly, by excluding snow-affected stations, the median rMAE improves 1.9 – 8.1 %abs, depending on data product. The improvement in rMAE by excluding snow-affected stations is partially related to the difficulty of separating snow on the ground from cloud cover in satellite images. This difficulty is illustrated by concrete examples of irradiance time series from clear sky days when the ground is covered in snow. Although the performance of the data products is dependent on the categorization of stations, i.e., latitude, snow conditions, and local topography, the relative performance between the products is maintained regardless of sub-division. more
Atmosphere CM-SAF Climate Data Records Validation

Bayesian cloud-top phase determination for Meteosat Second Generation

Author(s):
Mayer, J.; Bugliaro, L.; Mayer, B.; Piontek, D.; Voigt, C.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 13
2024
DOI: 10.5194/amt-17-4015-2024
Abstract:
A comprehensive understanding of the cloud thermodynamic phase is crucial for assessing the cloud radiative effect and is a prerequisite for remote se… A comprehensive understanding of the cloud thermodynamic phase is crucial for assessing the cloud radiative effect and is a prerequisite for remote sensing retrievals of microphysical cloud properties. While previous algorithms mainly detected ice and liquid phases, there is now a growing awareness for the need to further distinguish between warm liquid, supercooled and mixed-phase clouds. To address this need, we introduce a novel method named ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI), which enables cloud detection and the determination of cloud-top phase using SEVIRI (Spinning Enhanced Visible and Infrared Imager), the geostationary passive imager aboard Meteosat Second Generation. ProPS discriminates between clear sky, optically thin ice (TI) cloud, optically thick ice (IC) cloud, mixed-phase (MP) cloud, supercooled liquid (SC) cloud and warm liquid (LQ) cloud. Our method uses a Bayesian approach based on the cloud mask and cloud phase from the lidar-radar cloud product DARDAR (liDAR/raDAR). The validation of ProPS using 6 months of independent DARDAR data shows promising results: the daytime algorithm successfully detects 93% of clouds and 86% of clear-sky pixels. In addition, for phase determination, ProPS accurately classifies 91% of IC, 78% of TI, 52% of MP, 58% of SC and 86% of LQ clouds, providing a significant improvement in accurate cloud-top phase discrimination compared to traditional retrieval methods. © Copyright: more
Atmosphere CM-SAF Climate Data Records Method Validation

Assessment of the Solar Energy Potential over South America Estimated by CMIP6 Models in the Present and Future Climate

Author(s):
Ferreira, Glauber W. S.; Reboita, Michelle S.; Ribeiro, João Gabriel M.
Publication title: Journal of Environmental & Earth Sciences
2024
 | Volume: 6 | Issue: 2
2024
DOI: 10.30564/jees.v6i2.6425
Abstract:
Developing the renewable energy matrix of South America (SA) is fundamental for sustainable socioeconomic growth and mitigating climate change's adver… Developing the renewable energy matrix of South America (SA) is fundamental for sustainable socioeconomic growth and mitigating climate change's adverse effects. Thus, this study estimates changes in SA's solar irradiance and solar power potential using data from eight global climate models (GCMs) belonging to the Coupled Model Intercomparison Project—Phase 6 (CMIP6). Applying statistical downscaling and bias correction with the Quantile Delta Mapping (QDM) technique, we evaluate projected changes in the Concentrated Solar Power (CSP) and Photovoltaic Power (PVP) outputs under different future climate scenarios (SSP2-4.5 and SSP5-8.5). Historical simulations (1995–2014) are validated using ERA5 reanalysis and CLARA-A3 satellite observations. The QDM method reduces the models' systematic biases, decreasing the ensemble's errors by 50% across SA throughout the year. Regarding future decades (2020–2099), the CMIP6 ensemble shows spatial and seasonal variability in solar generation. For CSP, estimates suggest that regions traditionally favorable to solar energy generation (such as the Brazilian Northeast and portions of Chile) will maintain their suitable conditions during the 21st century, projecting a potential 1–6% increase (particularly under the SSP5-8.5 scenario in southern Chile and most of Brazil). Concerning PVP generation, the CMIP6 ensemble projects a rise of 1–4% (mainly under the SSP5-8.5 scenario in the Amazonia, Midwest, and Southeast Brazilian sectors). Moreover, trend analyses projected individually by the CMIP6 GCMs converge on an increasing PVP, mainly in Brazil's Amazonia and Midwest regions. In contrast, for South Brazil, approximately 84% of the projections show a negative trend (or no trend), evidencing unfavorable or uncertain conditions for solar generation development in the region. Despite the data and processes' inherent limitations, this study yields a first analysis of statistically downscaled projections from CMIP6 for solar power generation in South America, providing valuable information for energy sector decision-makers. more
Application Atmosphere CM-SAF Climate Data Records Validation

Assessment of Atmospheric and Surface Energy Budgets Using Observation-Based Data Products

Author(s):
Mayer, Michael; Kato, Seiji; Bosilovich, Michael; Bechtold, Peter; Mayer, Johannes; Schröder, Marc; Behrangi, Ali; Wild, Martin; Kobayashi, Shinya; Li, Zhujun; L’Ecuyer, Tristan
Publication title: Surveys in Geophysics
2024
 | Volume: 45 | Issue: 6
2024
DOI: 10.1007/s10712-024-09827-x
Abstract:
Accurate diagnosis of regional atmospheric and surface energy budgets is critical for understanding the spatial distribution of heat uptake associated… Accurate diagnosis of regional atmospheric and surface energy budgets is critical for understanding the spatial distribution of heat uptake associated with the Earth’s energy imbalance (EEI). This contribution discusses frameworks and methods for consistent evaluation of key quantities of those budgets using observationally constrained data sets. It thereby touches upon assumptions made in data products which have implications for these evaluations. We evaluate 2001–2020 average regional total (TE) and dry static energy (DSE) budgets using satellite-based and reanalysis data. For the first time, a consistent framework is applied to the ensemble of the 5th generation European Reanalysis (ERA5), version 2 of modern-era retrospective analysis for research and applications (MERRA-2), and the Japanese 55-year Reanalysis (JRA55). Uncertainties of the computed budgets are assessed through inter-product spread and evaluation of physical constraints. Furthermore, we use the TE budget to infer fields of net surface energy flux. Results indicate biases  more
Application Atmosphere CM-SAF Climate Data Records Validation

Assessing the representation of Arctic sea ice and the marginal ice zone in ocean–sea ice reanalyses

Author(s):
Cocetta, F.; Zampieri, L.; Selivanova, J.; Iovino, D.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 10
2024
DOI: 10.5194/tc-18-4687-2024
Abstract:
The recent development of data-assimilating reanalyses of the global ocean and sea ice enables a better understanding of the polar region dynamics and… The recent development of data-assimilating reanalyses of the global ocean and sea ice enables a better understanding of the polar region dynamics and provides gridded descriptions of sea ice variables without temporal and spatial gaps. Here, we study the spatiotemporal variability of the Arctic sea ice area and thickness using the Global ocean Reanalysis Ensemble Product (GREP) produced and disseminated by the Copernicus Marine Service (CMS). GREP is compared and validated against the state-of-the-art regional reanalyses PIOMAS and TOPAZ, as well as observational datasets of sea ice concentration and thickness for the period 1993–2020. Our analysis presents pan-Arctic metrics but also emphasizes the different responses of ice classes, the marginal ice zone (MIZ), and pack ice to climate changes. This aspect is of primary importance since the MIZ accounts for an increasing percentage of the summer sea ice as a consequence of the Arctic warming and sea ice extent retreat, among other processes. Our results show that GREP provides reliable estimates of present-day and recent-past Arctic sea ice states and that the seasonal to interannual variability and linear trends in the MIZ area are properly reproduced, with the ensemble spread often being as broad as the uncertainty of the observational dataset. The analysis is complemented by an assessment of the average MIZ latitude and its northward migration in recent years, a further indicator of the Arctic sea ice decline. There is substantial agreement between GREP and reference datasets in the summer. Overall, GREP is an adequate tool for gaining an improved understanding of the Arctic sea ice, also in light of the expected warming and the Arctic transition to ice-free summers. © Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License. more
Application Climate Data Records Cryosphere OSI-SAF Validation

Assessing the Influences of Cloud Top Height Information on Passive Microwave Retrieval of Cloud Liquid Water Path

Author(s):
Li, J.; Liu, C.; Yao, B.; Zhao, Y.; Dou, F.; Hu, X.; Weng, F.; Sohn, B.-J.
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2024
 | Volume: 62
2024
DOI: 10.1109/TGRS.2024.3493598
Abstract:
Cloud liquid water path (LWP) quantifies liquid water amount within the atmosphere and is closely related to water cycle, weather, and climate. Passiv… Cloud liquid water path (LWP) quantifies liquid water amount within the atmosphere and is closely related to water cycle, weather, and climate. Passive microwave (MW) observations are powerful tools for retrieving LWP. An empirical relationship between the LWPs and MW brightness temperatures (BTs) can be obtained for conventional retrievals, which consider only the influence of LWP on BTs. However, besides LWP, the cloud vertical extent [e.g., cloud top height (CTH)] can affect MW emission, absorption, and corresponding channel BTs, but it is ignored in conventional retrievals. This study investigates the influences of CTH on MW LWP retrievals, and a CTH-dependent algorithm is developed using CTHs from infrared retrievals. Synthetic radiative transfer simulations are performed to quantify CTH effects on MW channel BTs and to establish the CTH-dependent retrieval coefficients. We use the Advanced MW Scanning Radiometer 2 (AMSR2) observations. Cloud products from Moderate Resolution Imaging Spectroradiometer (MODIS) are collocated to provide the necessary CTH information. Thus, we develop an LWP retrieval algorithm by combining AMSR2 BTs with MODIS CTHs. The results indicate that incorporating CTH information into LWP retrievals enhances the consistency between MW and visible/infrared retrievals. Specifically, the CTH-dependent algorithm showed an improvement in the intraclass correlation coefficient (ICC) and a reduction in mean relative differences (MRDs) by approximately 4% (from 18% to 14%) compared to AMSR2 operational retrievals. The CTH-dependent results are slightly more consistent with the MODIS results than the CTH-independent ones, though it remains important to note that the CTH-dependent retrievals introduce less differences compared to their CTH-independent retrievals. © 2024 IEEE. more
Application Atmosphere NWP-SAF Software for CDR development

Assessing sea ice microwave emissivity up to submillimeter waves from airborne and satellite observations

Author(s):
Risse, N.; Mech, M.; Prigent, C.; Spreen, G.; Crewell, S.
Publication title: Cryosphere
2024
 | Volume: 18 | Issue: 9
2024
DOI: 10.5194/tc-18-4137-2024
Abstract:
Upcoming submillimeter wave satellite missions require an improved understanding of sea ice emissivity to separate atmospheric and surface microwave s… Upcoming submillimeter wave satellite missions require an improved understanding of sea ice emissivity to separate atmospheric and surface microwave signals under dry polar conditions. This work investigates hectometer-scale observations of airborne sea ice emissivity between 89 and 340 GHz, combined with high-resolution visual imagery from two Arctic airborne field campaigns that took place in summer 2017 and spring 2019 northwest of Svalbard, Norway. Using k-means clustering, we identify four distinct sea ice emissivity spectra that occur predominantly across multiyear ice, first-year ice, young ice, and nilas. Nilas features the highest emissivity, and multiyear ice features the lowest emissivity among the clusters. Each cluster exhibits similar nadir emissivity distributions from 183 to 340 GHz. To relate hectometer-scale airborne measurements to kilometer-scale satellite footprints, we quantify the reduction in the variability of airborne emissivity as footprint size increases. At 340 GHz, the emissivity interquartile range decreases by almost half when moving from the hectometer scale to a footprint of 16 km, typical of satellite instruments. Furthermore, we collocate the airborne observations with polar-orbiting satellite observations. After resampling, the absolute relative bias between airborne and satellite emissivities at similar channels lies below 3 %. Additionally, spectral variations in emissivity at nadir on the satellite scale are low, with slightly decreasing emissivity from 183 to 243 GHz, which occurs for all hectometer-scale clusters except those predominantly composed of multiyear ice. Our results will enable the development of microwave retrievals and assimilation over sea ice in current and future satellite missions, such as the Ice Cloud Imager (ICI) and EUMETSAT Polar System - Sterna (EPS-Sterna). © 2024 Nils Risse et al. more
Application Atmosphere NWP-SAF Software for CDR development

Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data

Author(s):
Brüning, S.; Niebler, S.; Tost, H.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 3
2024
DOI: 10.5194/amt-17-961-2024
Abstract:
Satellite instruments provide high-temporal-resolution data on a global scale, but extracting 3D information from current instruments remains a challe… Satellite instruments provide high-temporal-resolution data on a global scale, but extracting 3D information from current instruments remains a challenge. Most observational data are two-dimensional (2D), offering either cloud top information or vertical profiles. We trained a neural network (Res-UNet) to merge high-resolution satellite images from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI) with 2D CloudSat radar reflectivities to generate 3D cloud structures. The Res-UNet extrapolates the 2D reflectivities across the full disk of MSG SEVIRI, enabling a reconstruction of the cloud intensity, height, and shape in three dimensions. The imbalance between cloudy and clear-sky CloudSat profiles results in an overestimation of cloud-free pixels. Our root mean square error (RMSE) accounts for 2.99dBZ. This corresponds to 6.6% error on a reflectivity scale between -25 and 20dBZ. While the model aligns well with CloudSat data, it simplifies multi-level and mesoscale clouds in particular. Despite these limitations, the results can bridge data gaps and support research in climate science such as the analysis of deep convection over time and space. © Copyright: more
Application Atmosphere CM-SAF Climate Data Records EUM-Secr Validation

Arctic and Antarctic Sea Ice Thickness and Volume Changes From Observations Between 1994 and 2023

Author(s):
Bocquet, M.; Fleury, S.; Rémy, F.; Piras, F.
Publication title: Journal of Geophysical Research: Oceans
2024
 | Volume: 129 | Issue: 11
2024
DOI: 10.1029/2023JC020848
Abstract:
Both Arctic and Antarctic sea ice are affected by climate change. While Arctic sea ice has been declining for several decades, Antarctic sea ice exten… Both Arctic and Antarctic sea ice are affected by climate change. While Arctic sea ice has been declining for several decades, Antarctic sea ice extent slowly increased until 2015, followed by a sharp drop in 2016. Quantifying sea ice changes is essential to assess their impacts on the ocean, atmosphere, ecosystems and Arctic communities. In this study, we combine sea ice thickness estimates from four satellite radar altimeters to derive the longest time series of homogeneous sea ice thickness for both hemispheres over 30 years (1994–2023). The record supports the rapid loss of sea ice in the Arctic for each month of the year and the heterogeneous changes in sea ice thickness in the Antarctic. The study confirms that most of the volume variability is due to the thickness variability, which holds true for both hemispheres. The sea ice thickness time series presented here offer new insights for models, in particular the possibility to evaluate sea ice reanalyses and to initialize forecasts, especially in the Antarctic, where the data set presented here has no equivalent in terms of spatial and temporal coverage. © 2024. The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF

Arctic Sea Ice Concentration Prediction Using Spatial Attention Deep Learning

Author(s):
Gu, HQ; Zhang, LC; Qin, MJ; Wu, SS; Du, ZH
Publication title: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
2024
 | Volume: 17
2024
DOI: 10.1109/JSTARS.2024.3486187
Abstract:
With the accelerating impact of global warming, the changes of Arctic sea ice has become a focal point of research. Due to the spatial heterogeneity a… With the accelerating impact of global warming, the changes of Arctic sea ice has become a focal point of research. Due to the spatial heterogeneity and the complexity of its evolution, long-term prediction of Arctic sea ice remains a challenge. In this article, a spatial attention U-Net (SAU-Net) method integrated with a gated spatial attention mechanism is proposed. Extracting and enhancing the spatial features from the historical atmospheric and SIC data, this method improves the accuracy of Arctic sea ice prediction. During the test periods (2018-2020), our method can skillfully predict the Arctic sea ice up to 12 months, outperforming the naive U-Net, linear trend models, and dynamical models, especially in extreme sea ice scenarios. The importance of different atmospheric factors affecting sea ice prediction are also analyzed for further exploration. more
Application Climate Data Records Cryosphere OSI-SAF

Anatomy of the uncertainty of satellite vicarious calibration using radiosondes: concepts and preliminary results for microwave radiometric observations

Author(s):
Cimini, D.; Barlakas, V.; Carminati, F.; De Angelis, F.; Di Paola, F.; Fassò, A.; Gallucci, D.; Gentile, S.; Hewison, T.; Larosa, S.; Madonna, F.; Mattioli, V.; Montopoli, M.; Romano, F.; Rosoldi, M.; Viggiano, M.; Von Engeln, A.; Ricciardelli, E.
Publication title: Bulletin of Atmospheric Science and Technology
2024
 | Volume: 5 | Issue: 1
2024
DOI: 10.1007/s42865-024-00073-y
Abstract:
Calibration of satellite observations is crucial for ensuring the quality of retrieved products essential for meteorological and climate applications.… Calibration of satellite observations is crucial for ensuring the quality of retrieved products essential for meteorological and climate applications. Calibration is obtained and monitored through a cascade of stages, including postlaunch vicarious calibration/validation activities through comparison with independent reference measurements. Here, the vicarious calibration method using radiative transfer simulations based on reference radiosondes is considered in the framework of the calibration/validation activities for the Microwave Imager (MWI) and the Ice Cloud Imager (ICI) to be launched with the Second Generation of the EUMETSAT Polar System. This paper presents an overview of the uncertainty characterizing the vicarious calibration of MWI and ICI using radiosondes as performed within the EUMETSAT-funded VICIRS study. The uncertainty characterization is pursued following a metrological approach, providing a preliminary estimation of all the identified sources. The same approach is used to develop a rigorous method for estimating the number of comparison pairs (i.e., observations vs. simulations) needed to reach a certain level of accuracy in bias determination. © The Author(s) 2024. more
Atmosphere NWP-SAF Software for CDR development Validation

An Investigation on Causes of the Detected Surface Solar Radiation Brightening in Europe Using Satellite Data

Author(s):
Schilliger, L.; Tetzlaff, A.; Bourgeois, Q.; Correa, L.F.; Wild, M.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 15
2024
DOI: 10.1029/2024JD041101
Abstract:
Surface solar radiation is fundamental for terrestrial life. It provides warmth to make our planet habitable, drives atmospheric circulation, the hydr… Surface solar radiation is fundamental for terrestrial life. It provides warmth to make our planet habitable, drives atmospheric circulation, the hydrological cycle and photosynthesis. Europe has experienced an increase in surface solar radiation, termed “brightening,” since the 1980s. This study investigates the causative factors behind this brightening. A novel algorithm from the EUMETSAT satellite application facility on climate monitoring (CM SAF) provides the unique opportunity to simulate surface solar radiation under various atmospheric conditions for clouds (clear-sky or all-sky), aerosol optical depth (time-varying or climatological averages) and water vapor content (with or without its direct influence on surface solar radiation). Through a multiple linear regression approach, the study attributes brightening trends to changes in these atmospheric parameters. Analyzing 61 locations distributed across Europe from 1983 to 2020, aerosols emerge as key driver during 1983–2002, with Southern Europe and high elevations showing subdued effects (0%/decade–1%/decade) versus more pronounced impacts in Northern and Eastern Europe (2%/decade–6%/decade). Cloud effects exhibit spatial variability, inducing a negative effect on surface solar radiation (−3%/decade–−2%/decade) at most investigated locations in the same period. In the period 2001–2020, aerosol effects are much smaller, while cloud effects dominate the observed brightening (2%/decade–5%/decade). This study therefore finds a substantial decrease in the cloud radiative effect over Europe in the first two decades of the 21st century. Water vapor exerts negligible influence in both sub-periods. © 2024. The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

An Ensemble Learning Model Reveals Accelerated Reductions in Snow Depth Over Arctic Sea Ice Under High-Emission Scenarios

Author(s):
Li, H. L.; Ke, C. Q.; Shen, X. Y.; Zhu, Q. H.; Cai, Y.
Publication title: Journal of Geophysical Research: Atmospheres
2024
 | Volume: 129 | Issue: 8
2024
DOI: 10.1029/2023JD039910
Abstract:
There are significant differences in snow depth predictions among different earth system models, and many models underestimate snow depth, restricting… There are significant differences in snow depth predictions among different earth system models, and many models underestimate snow depth, restricting their application. Here, major factors influencing snow depth changes in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were identified and evaluated. Based on satellite-derived snow depth and CMIP6 data, an ensemble learning model based on multiple deep learning methods (hereafter referred to as the Multi-DL model) was developed to predict future snow depth. According to satellite observations and two Operation IceBridge products, the Multi-DL model yielded root mean square errors of 7.48, 6.20, and 6.17 cm. A continuous decrease in snow depth was observed from 2002 to 2100, and the rate of decrease accelerated with increasing emissions. Under the highest emission scenario, the first snow-free year occurred in 2047, within the same decade as the first ice-free year (2056). The predicted warm season snow depth was sensitive to sea ice velocity, sea ice concentration (siconc), precipitation, sea surface temperature (tos) and albedo, while the predicted cold season snow depth was sensitive to tos, air temperature, and siconc. The above parameters introduce some snow depth uncertainty. This method provides new ideas for predicting snow depth, and the generated snow depth records can provide data support for formulating Arctic-related policies. more
Application Atmosphere CM-SAF Climate Data Records Validation

An Assessment of Subseasonal Prediction Skill of the Antarctic Sea Ice Edge

Author(s):
Gao, Y.; Xiu, Y.; Nie, Y.; Luo, H.; Yang, Q.; Zampieri, L.; Lv, X.; Uotila, P.
Publication title: Journal of Geophysical Research: Oceans
2024
 | Volume: 129 | Issue: 11
2024
DOI: 10.1029/2024JC021499
Abstract:
In this study, the subseasonal Antarctic sea ice edge prediction skill of the Copernicus Climate Change Service (C3S) and Subseasonal to Seasonal (S2S… In this study, the subseasonal Antarctic sea ice edge prediction skill of the Copernicus Climate Change Service (C3S) and Subseasonal to Seasonal (S2S) projects was evaluated by a probabilistic metric, the spatial probability score (SPS). Both projects provide subseasonal to seasonal scale forecasts of multiple coupled dynamical systems. We found that predictions by individual dynamical systems remain skillful for up to 38 days (i.e., the ECMWF system). Regionally, dynamical systems are better at predicting the sea ice edge in the West Antarctic than in the East Antarctic. However, the seasonal variations of the prediction skill are partly system-dependent as some systems have a freezing-season bias, some had a melting-season bias, and some had a season-independent bias. Further analysis reveals that the model initialization is the crucial prerequisite for skillful subseasonal sea ice prediction. For those systems with the most realistic initialization, the model physics dictates the propagation of initialization errors and, consequently, the temporal length of predictive skill. Additionally, we found that the SPS-characterized prediction skill could be improved by increasing the ensemble size to gain a more realistic ensemble spread. Based on the C3S systems, we constructed a multi-model forecast from the above principles. This forecast consistently demonstrated a superior prediction skill compared to individual dynamical systems or statistical observation-based benchmarks. In summary, our results elucidate the most important factors (i.e., the model initialization and the model physics) affecting the currently available subseasonal Antarctic sea ice prediction systems and highlighting the opportunities to improve them significantly. © 2024 The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF

An Adaptive Channel Selection Method for Assimilating the Hyperspectral Infrared Radiances

Author(s):
Zhou, L.; Lei, L.; Whitaker, J.S.; Tan, Z.-M.
Publication title: Monthly Weather Review
2024
 | Volume: 152 | Issue: 3
2024
DOI: 10.1175/MWR-D-23-0131.1
Abstract:
Hyperspectral infrared (IR) satellites can provide high-resolution vertical profiles of the atmospheric state, which significantly contributes to the … Hyperspectral infrared (IR) satellites can provide high-resolution vertical profiles of the atmospheric state, which significantly contributes to the forecast skill of numerical weather prediction, especially for regions with sparse observations. One challenge in assimilating the hyperspectral radiances is how to effectively extract the observation information, due to the interchannel correlations and correlated observation errors. An adaptive channel selection method is proposed, which is implemented within the data assimilation scheme and selects the radiance observation with the maximum reduction of variance in observation space. Compared to the commonly used channel selection method based on the maximum entropy reduction (ER), the adaptive method can provide flow-dependent and time-varying channel selections. The performance of the adaptive selection method is evaluated by assimilating only the synthetic Fengyun-4A (FY-4A) GIIRS IR radiances in an observing system simulation experiment (OSSE), with model resolutions from 7.5 to 1.5 km and then 300 m. For both clear-sky and all-sky conditions, the adaptive method generally produces smaller RMS errors of state variables than the ER-based method given similar amounts of assimilated radiances, especially with fine model resolutions. Moreover, the adaptive method has minimum RMS errors smaller than or approaching those with all channels assimilated. For the intensity of the tropical cyclone, the adaptive method also produces smaller errors of the minimum dry air mass and maximal wind speed at different levels, compared to the ER-based selection method. © 2024 American Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

Advances in Methodology and Generation of All-Weather Land Surface Temperature Products from Polar-Orbiting and Geostationary Satellites: A comprehensive review

Author(s):
Jia, A.; Liang, S.; Wang, D.; Mallick, K.; Zhou, S.; Hu, T.; Xu, S.
Publication title: IEEE Geoscience and Remote Sensing Magazine
2024
 | Volume: 12 | Issue: 4
2024
DOI: 10.1109/MGRS.2024.3421268
Abstract:
Land surface temperature (LST) is crucial for understanding surface energy budgets, hydrological cycling, and land-Atmosphere interactions. However, c… Land surface temperature (LST) is crucial for understanding surface energy budgets, hydrological cycling, and land-Atmosphere interactions. However, cloud cover leads to numerous data gaps in existing remote sensing thermal infrared (TIR) LST products, seriously restricting their applications. This article provides a comprehensive review concerning both LST recovery methodologies and 26 emerging all-weather products derived from polar-orbiting and geostationary (GEO) satellites. Clarifying product distinctions will enable end users to select suitable options for diverse research. Methodologies are categorized into spatiotemporal interpolation, surface energy balance (SEB)-based physical estimation, passive microwave (PMW)-based methods, and simulated temperature-based approaches. Historical research trajectories, strengths, limitations, and potential research directions of the methodologies and products are discussed. The review reports that existing all-weather LST products generally exhibit root-mean-square errors (RMSEs) of more
Climate Data Records LSA-SAF Terrestrial Validation

Aerosol influence on cloud macrophysical and microphysical properties over the Tibetan Plateau and its adjacent regions

Author(s):
Wei, Chengqiang; Zhao, Pengguo; Wang, Yuting; Wang, Yuan; Mo, Shuying; Zhou, Yunjun
Publication title: Environmental Science and Pollution Research
2024
 | Volume: 31 | Issue: 20
2024
DOI: 10.1007/s11356-024-33247-4
Abstract:
This study uses aerosol optical depth (AOD) and cloud properties data to investigate the influence of aerosol on the cloud properties over the Tibetan… This study uses aerosol optical depth (AOD) and cloud properties data to investigate the influence of aerosol on the cloud properties over the Tibetan Plateau and its adjacent regions. The study regions are divided as the western part of the Tibetan Plateau (WTP), the Indo-Gangetic Plain (IGP), and the Sichuan Basin (SCB). All three regions show significant cloud effects under low aerosol loading conditions. In WTP, under low aerosol loading conditions, the effective radius of liquid cloud particles (LREF) decreases with the increase of aerosol loading, while the effective radius of ice cloud particles (IREF) and cloud top height (CTH) increase during the cold season. Increased aerosol loading might inhibit the development of warm rain processes, transporting more cloud droplets above the freezing level and promoting ice cloud development. During the warm season, under low aerosol loading conditions, both the cloud microphysical (LREF and IREF) and macrophysical (cloud top height and cloud fraction) properties increase with the increase of aerosol loading, likely due to higher dust aerosol concentration in this region. In IGP, both LREF and IREF increase with the increase in aerosol loading during the cold season. In SCB, LREF increases with the increase in aerosol loading, while IREF decreases, possibly due to the higher hygroscopic aerosol concentration in the SCB during the cold season. Meteorological conditions also modulate the aerosol-cloud interaction. Under different convective available potential energy (CAPE) and relative humidity (RH) conditions, the influence of aerosol on clouds varies in the three regions. Under low CAPE and RH conditions, the relationship between LREF and aerosol in both the cold and warm seasons is opposite in the WTP: LREF decreases with the increase of aerosol in the cold season, while it increases in the warm season. This discrepancy may be attributed to a difference in the moisture condition between the cold and warm seasons in this region. In general, the influence of aerosols on cloud properties in TP and its adjacent regions is characterized by significant nonlinearity and spatial variability, which is likely related to the differences in aerosol types and meteorological conditions between different regions. more
Application Atmosphere CM-SAF Climate Data Records

A statistically significant increase in ice supersaturation in the atmosphere in the past 40 years

Author(s):
Benetatos, C.; Eleftheratos, K.; Gierens, K.; Zerefos, C.
Publication title: Scientific Reports
2024
 | Volume: 14 | Issue: 1
2024
DOI: 10.1038/s41598-024-75756-9
Abstract:
Ice saturation (and supersaturation) is a frequent phenomenon in cold regions of the upper troposphere. Its existence is essential for the formation o… Ice saturation (and supersaturation) is a frequent phenomenon in cold regions of the upper troposphere. Its existence is essential for the formation of ice clouds and a necessary condition for the persistence of contrails. Its spatial and temporal evolution is important for weather and climate. The ice saturation and supersaturation values are found in the upper tail of the probability density function (pdf) of upper tropospheric humidity with respect to ice (UTHi). Here, we analyse the changes in the frequency of occurrence of ice saturation and supersaturation from 1979 to 2020 and compare them to changes in the mean UTHi. Our results show that while the mean UTHi increases near-globally with a rate of about 0.15% per decade, high UTHi values exceeding the 70%, 80%, 90% and 100% thresholds increase faster than the mean, at rates of about 0.7%, 0.6%, 0.4% and 0.3% per decade, respectively. The increasing rates of values found in the upper tail of the UTHi pdf suggest that the ambient conditions for cirrus and contrail formation and persistence will be more favourable in the future and this is expected to further enhance the impact of aviation on climate. © The Author(s) 2024. more
Application Atmosphere CM-SAF Climate Data Records

A Simple and Robust CryoSat-2 Radar Freeboard Correction Method Dedicated to TFMRA50 for the Arctic Winter Snow Depth and Sea Ice Thickness Retrieval

Author(s):
Shi, H.; Tonboe, R.; Lee, S.-M.; Dybkjær, G.; Sohn, B.-J.; Singha, S.; Baordo, F.
Publication title: Earth and Space Science
2024
 | Volume: 11 | Issue: 10
2024
DOI: 10.1029/2024EA003715
Abstract:
CryoSat-2 has been successful in observing sea ice thickness from space by providing ice freeboard information. The initial estimate of the ice freebo… CryoSat-2 has been successful in observing sea ice thickness from space by providing ice freeboard information. The initial estimate of the ice freeboard, called radar freeboard, is obtained by analyzing the observed waveform using a retracker. A series of corrections are needed to convert the radar freeboard to the ice freeboard. Those are the physical effects (e.g., changes in wave propagation speed and the distribution of scattering at snow and ice surfaces, etc.) and the bias of the retracker; however, traditionally, only the wave speed correction has been applied due to lack of enough information to perform the complete correction. Here, an alternative correction method for the CryoSat-2 radar freeboard derived using the Threshold First-Maximum Retracker Algorithm with a 50% threshold (TFMRA50) is proposed. Snow depth was used as a predictor for the correction, similar to the traditional wave speed correction, but the coefficients were empirically determined by performing a direct comparison of the radar freeboard from CryoSat-2 and the ice freeboard from airborne observations. Consequently, this new empirical correction treats the physical effects and the retracker bias as a whole, which have been difficult to separate in the retrieval process. In this paper, we demonstrate that the retrieval accuracy of snow and ice variables and the consistency of the two independent retrieval methods are improved when the new correction is applied. The result of this study emphasizes the importance of compatibility between the retracker and the freeboard correction method. © 2024. The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF

A robust stepwise jump in the Arctic wintertime warming in 2005 coherent with the increased clear-sky downward longwave radiation flux

Author(s):
Latonin, M.M.; Demchenko, A.Y.
Publication title: Dynamics of Atmospheres and Oceans
2024
 | Volume: 108
2024
DOI: 10.1016/j.dynatmoce.2024.101503
Abstract:
In some areas of the Arctic, the Earth's surface temperature and near-surface air temperature are rising faster than in others. The purpose of this st… In some areas of the Arctic, the Earth's surface temperature and near-surface air temperature are rising faster than in others. The purpose of this study is to identify, based on the ERA5 climate reanalysis data, the spatiotemporal structure of climatic changes in the Arctic during 1959–2022. The main emphasis is put on the following three parameters: mean surface clear-sky downward longwave radiation flux, near-surface air temperature, and skin temperature. A statistical model of stepwise changes was applied to the time series of the studied characteristics at each grid point of the entire Arctic (67°N–90°N). The results obtained indicate a close relationship between all parameters in the winter season. The dominant year of stepwise changes in the Arctic is 2005. Moreover, it is precisely this transition from one state of the climate system to another that is statistically significant over a large territory, which is located mainly in the Eastern Hemisphere. The time series averaged over the identified areas are highly correlated with each other, and the year 2005 characterizes the change from a sharp increase in values to their variability without a pronounced trend. The available satellite observations fully confirm the temporal structure of the stepwise changes for the studied parameters and largely confirm its spatial structure. Thus, the clear-sky downward longwave radiation flux is one of the leading factors in the formation of the thermal regime of the Arctic. © 2024 Elsevier B.V. more
Application Atmosphere CM-SAF Climate Data Records

A satellite view of the exceptionally warm summer of 2022 over Europe

Author(s):
Martins, J.P.A.; Caetano, S.; Pereira, C.; Dutra, E.; Cardoso, R.M.
Publication title: Natural Hazards and Earth System Sciences
2024
 | Volume: 24 | Issue: 4
2024
DOI: 10.5194/nhess-24-1501-2024
Abstract:
Summer heatwaves are becoming increasingly dangerous over Europe, and their close monitoring is essential for human activities. Typically, they are mo… Summer heatwaves are becoming increasingly dangerous over Europe, and their close monitoring is essential for human activities. Typically, they are monitored using the 2 m temperature from meteorological weather stations or reanalysis datasets. In this study, the 2022 extremely warm summer over Europe is analysed using satellite land surface temperature (LST), specifically the LSA SAF (Land Surface Analysis Satellite Application Facility) all-sky LST product (available from 2004 onwards). Since climate applications of LST are still poorly explored, heatwave diagnostics derived from satellite observations are compared with those derived using ERA5/ERA5-Land reanalysis data. Results highlight the exceptionality of 2022 in different metrics such as the mean LST anomaly, area under extreme heat conditions, number of hot days and heatwave magnitude index. In all metrics, 2022 ranked first when compared with the remaining years. Compared to 2018 (next in all rankings), 2022 exceeded its LST anomaly by 0.7 °C and each pixel had on average 7 more hot days. Satellite LST complements reanalysis diagnostics, as higher LST anomalies occur over areas under severe drought, indicating a higher control and amplification of the heatwave by surface processes and vegetation stress. These cross-cutting diagnostics increase the confidence across satellite data records and reanalyses, fostering their usage in climate applications. © Author(s) 2024. more
Application Climate Data Records LSA-SAF Terrestrial

A Machine Learning-Based Bias Correction Scheme for the All-Sky Assimilation of AGRI Infrared Radiances in a Regional OSSE Framework

Author(s):
Zhang, X.; Xu, D.; Min, J.; Li, H.; Shen, F.; Lei, Y.
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2024
 | Volume: 62
2024
DOI: 10.1109/TGRS.2024.3427434
Abstract:
Most bias correction (BC) schemes based on a linear fitting function have undesirable effects on the all-sky assimilation of satellite radiances from … Most bias correction (BC) schemes based on a linear fitting function have undesirable effects on the all-sky assimilation of satellite radiances from infrared bands. This study introduces a newly nonlinear BC method for the all-sky assimilation of Fengyun-4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) infrared radiances. The proposed BC method uses a machine learning technology of random forest (RF) to emulate the fitting relationship between the observation-minus-background (OMB) departures and BC predictors. The effectiveness of this BC algorithm is verified in an idealized case, where the sources of the systematic bias and the real states of the atmosphere are assumed to be known. The OMB departures here were artificially produced including the predictor-dependent systematic biases and the Gauss errors. Meanwhile, the so-called 'truth' was simulated from natural run forecasts in a regional observing system simulation experiment (OSSE) framework. As expected, it is demonstrated that the RF BC method has the ability to remove linear and lower degree nonlinear biases of all-sky AGRI infrared observations whether caused by a single source or multiple sources. Another advantage of the RF BC method is that meteorological signals are potentially reserved after BC when the predictors have been properly selected according to feature importance scores in the RF model. Henceforth, assimilating the bias-corrected AGRI observations is conducive to decreasing the erroneous increments, followed by more accurate analyses of water vapor and cloud ice in the middle and upper troposphere. © 1980-2012 IEEE. more
Application Atmosphere NWP-SAF Software for CDR development

A Glimpse into the Future The 2023 Ocean Temperature and Sea Ice Extremes in the Context of Longer-Term Climate Change

Author(s):
Kuhlbrodt, T.; Swaminathan, R.; Ceppi, P.; Wilder, T.
Publication title: Bulletin of the American Meteorological Society
2024
 | Volume: 105 | Issue: 3
2024
DOI: 10.1175/BAMS-D-23-0209.1
Abstract:
In the year 2023, we have seen extraordinary extrema in high sea surface temperature (SST) in the North Atlantic and in low sea ice extent in the Sout… In the year 2023, we have seen extraordinary extrema in high sea surface temperature (SST) in the North Atlantic and in low sea ice extent in the Southern Ocean, outside the 4σ envelope of the 1982–2011 daily time series. Earth’s net global energy imbalance (12 months up to September 2023) amounts to +1.9 W m−2 as part of a remarkably large upward trend, ensuring further heating of the ocean. However, the regional radiation budget over the North Atlantic does not show signs of a suggested significant step increase from less negative aerosol forcing since 2020. While the temperature in the top 100 m of the global ocean has been rising in all basins since about 1980, specifically the Atlantic basin has continued to further heat up since 2016, potentially contributing to the extreme SST. Similarly, salinity in the top 100 m of the ocean has increased in recent years specifically in the Atlantic basin, and in addition in about 2015 a substantial negative trend for sea ice extent in the Southern Ocean began. Analyzing climate and Earth system model simulations of the future, we find that the extreme SST in the North Atlantic and the extreme in Southern Ocean sea ice extent in 2023 lie at the fringe of the expected mean climate change for a global surface-air temperature warming level (GWL) of 1.5°C, and closer to the average at a 3.0°C GWL. Understanding the regional and global drivers of these extremes is indispensable for assessing frequency and impacts of similar events in the coming years. © 2024 American Meteorological Society. more
Application Climate Data Records Cryosphere OSI-SAF

A Comprehensive Analysis of Air-Sea CO2 Flux Uncertainties Constructed From Surface Ocean Data Products

Author(s):
Ford, D.J.; Blannin, J.; Watts, J.; Watson, A.J.; Landschützer, P.; Jersild, A.; Shutler, J.D.
Publication title: Global Biogeochemical Cycles
2024
 | Volume: 38 | Issue: 11
2024
DOI: 10.1029/2024GB008188
Abstract:
Increasing anthropogenic CO2 emissions to the atmosphere are partially sequestered into the global oceans through the air-sea exchange of CO2 and its … Increasing anthropogenic CO2 emissions to the atmosphere are partially sequestered into the global oceans through the air-sea exchange of CO2 and its subsequent movement to depth, commonly referred to as the global ocean carbon sink. Quantifying this ocean carbon sink provides a key component for closing the global carbon budget, which is used to inform and guide policy decisions. These estimates are typically accompanied by an uncertainty budget built by selecting what are perceived as critical uncertainty components based on selective experimentation. However, there is a growing realization that these budgets are incomplete and may be underestimated, which limits their power as a constraint within global budgets. In this study, we present a methodology for quantifying spatially and temporally varying uncertainties in the air-sea CO2 flux calculations for the fCO2-product based assessments that allows an exhaustive assessment of all known sources of uncertainties, including decorrelation length scales between gridded measurements, and the approach follows standard uncertainty propagation methodologies. The resulting standard uncertainties are higher than previously suggested budgets, but the component contributions are largely consistent with previous work. The uncertainties presented in this study identify how the significance and importance of key components change in space and time. For an exemplar method (the UExP-FNN-U method), the work identifies that we can currently estimate the annual ocean carbon sink to a precision of ±0.70 Pg C yr−1 (1σ uncertainty). Because this method has been built on established uncertainty propagation and approaches, it appears that applicable to all fCO2-product assessments of the ocean carbon sink. © 2024. The Author(s). more
Application Atmosphere Climate Data Records Cryosphere OSI-SAF

A cloud-by-cloud approach for studying aerosol-cloud interaction in satellite observations

Author(s):
Alexandri, F.; Müller, F.; Choudhury, G.; Achtert, P.; Seelig, T.; Tesche, M.
Publication title: Atmospheric Measurement Techniques
2024
 | Volume: 17 | Issue: 6
2024
DOI: 10.5194/amt-17-1739-2024
Abstract:
The effective radiative forcing (ERF) due to aerosol-cloud interactions (ACIs) and rapid adjustments (ERFaci) still causes the largest uncertainty in … The effective radiative forcing (ERF) due to aerosol-cloud interactions (ACIs) and rapid adjustments (ERFaci) still causes the largest uncertainty in the assessment of climate change. It is understood only with medium confidence and is studied primarily for warm clouds. Here, we present a novel cloud-by-cloud (C×C) approach for studying ACI in satellite observations that combines the concentration of cloud condensation nuclei (nCCN) and ice nucleating particles (nINP) from polar-orbiting lidar measurements with the development of the properties of individual clouds by tracking them in geostationary observations. We present a step-by-step description for obtaining matched aerosol-cloud cases. The application to satellite observations over central Europe and northern Africa during 2014, together with rigorous quality assurance, leads to 399 liquid-only clouds and 95 ice-containing clouds that can be matched to surrounding nCCN and nINP respectively at cloud level. We use this initial data set for assessing the impact of changes in cloud-relevant aerosol concentrations on the cloud droplet number concentration (Nd) and effective radius (reff) of liquid clouds and the phase of clouds in the regime of heterogeneous ice formation. We find a ΔlnNd/ΔlnnCCN of 0.13 to 0.30, which is at the lower end of commonly inferred values of 0.3 to 0.8. The Δlnreff/ΔlnnCCN between -0.09 and -0.21 suggests that reff decreases by -0.81 to -3.78 nm per increase in nCCN of 1 cm-3. We also find a tendency towards more cloud ice and more fully glaciated clouds with increasing nINP that cannot be explained by the increasingly lower cloud top temperature of supercooled-liquid, mixed-phase, and fully glaciated clouds alone. Applied to a larger number of observations, the C×C approach has the potential to enable the systematic investigation of warm and cold clouds. This marks a step change in the quantification of ERFaci from space. © Copyright: more
Application Atmosphere CM-SAF Climate Data Records

2023's Antarctic sea ice extent is the lowest on record

Author(s):
Gilbert, E.; Holmes, C.
Publication title: Weather
2024
2024
DOI: 10.1002/wea.4518
Abstract:
Antarctic sea ice is a vitally important part of the regional and global climate. In 2023, sea ice extent fell to record lows, reaching unprecedented … Antarctic sea ice is a vitally important part of the regional and global climate. In 2023, sea ice extent fell to record lows, reaching unprecedented values for both the summer minimum, winter maximum and intervening freeze-up period. Here, we show that the extreme values observed were truly remarkable within the context of the satellite record, despite the challenge of quantifying how rare such an event might be, and discuss some contributing factors. While this could be part of a decline in sea ice associated with human-caused climate change, it is too early to say conclusively if this is the case. © 2024 The Authors. Weather published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society. more
Application Climate Data Records Cryosphere OSI-SAF

Winter Arctic sea ice thickness from ICESat-2: upgrades to freeboard and snow loading estimates and an assessment of the first three winters of data collection

Author(s):
Petty, Alek A.; Keeney, Nicole; Cabaj, Alex; Kushner, Paul; Bagnardi, Marco
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 1
2023
DOI: 10.5194/tc-17-127-2023
Abstract:
NASA's ICESat-2 mission has provided near-continuous, high-resolution estimates of sea ice freeboard across both hemispheres since data collection sta… NASA's ICESat-2 mission has provided near-continuous, high-resolution estimates of sea ice freeboard across both hemispheres since data collection started in October 2018. This study provides an impact assessment of upgrades to both the ICESat-2 freeboard data (ATL10) and NASA Eulerian Snow On Sea Ice Model (NESOSIM) snow loading on estimates of winter Arctic sea ice thickness. Misclassified leads were removed from the freeboard algorithm in the third release (rel003) of ATL10, which generally results in an increase in freeboards compared to rel002 data. The thickness increases due to increased freeboards in ATL10 improved comparisons of Inner Arctic Ocean sea ice thickness with thickness estimates from ESA's CryoSat-2. The upgrade from NESOSIM v1.0 to v1.1 results in only small changes in snow depth and density which have a less significant impact on thickness compared to the rel002 to rel003 ATL10 freeboard changes. The updated monthly gridded thickness data are validated against ice draft measurements obtained by upward-looking sonar moorings deployed in the Beaufort Sea, showing strong agreement (r2 of 0.87, differences of 11 ± 20 cm). The seasonal cycle in winter monthly mean Arctic sea ice thickness shows good agreement with various CryoSat-2 products (and a merged ICESat-2-CryoSat-2 product) and PIOMAS (Pan-Arctic Ice-Ocean Modeling and Assimilation System). Finally, changes in Arctic sea ice conditions over the past three winter seasons of data collection (November 2018-April 2021) are presented and discussed, including a 50 cm decline in multiyear ice thickness and negligible interannual differences in first-year ice. Interannual changes in snow depth provide a notable impact on the thickness retrievals on regional and seasonal scales. Our monthly gridded thickness analysis is provided online in a Jupyter Book format to increase transparency and user engagement with our ICESat-2 winter Arctic sea ice thickness data. © 2023 Alek A. Petty et al. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Vortex streets to the lee of Madeira in a kilometre-resolution regional climate model

Author(s):
Gao, Q.; Zeman, C.; Vergara-Temprado, J.; Lima, D.C.A.; Molnar, P.; Schär, C.
Publication title: Weather and Climate Dynamics
2023
 | Volume: 4 | Issue: 1
2023
DOI: 10.5194/wcd-4-189-2023
Abstract:
Atmospheric vortex streets are a widely studied dynamical effect of isolated mountainous islands. Observational evidence comes from case studies and s… Atmospheric vortex streets are a widely studied dynamical effect of isolated mountainous islands. Observational evidence comes from case studies and satellite imagery, but the climatology and annual cycle of vortex shedding are often poorly understood. Using the non-hydrostatic limited-area COSMO model driven by the ERA-Interim reanalysis, we conducted a 10-year-long simulation over a mesoscale domain covering the Madeira and Canary archipelagos at high spatial (grid spacing of 1 km) and temporal resolutions. Basic properties of vortex streets were analysed and validated through a 6 d long case study in the lee of Madeira Island. The simulation compares well with satellite and aerial observations and with existing literature on idealised simulations. Our results show a strong dependency of vortex shedding on local and synoptic-flow conditions, which are to a large extent governed by the location, shape and strength of the Azores high. As part of the case study, we developed a vortex identification algorithm. The algorithm is based on a set of criteria and enabled us to develop a climatology of vortex shedding from Madeira Island for the 10-year simulation period. The analysis shows a pronounced annual cycle with an increasing vortex-shedding rate from April to August and a sudden decrease in September. This cycle is consistent with mesoscale wind conditions and local inversion height patterns. © 2023 Qinggang Gao et al. more
Application Atmosphere NWP-SAF Software for CDR development

Validation of the CLARA-A3 Top-of-Atmosphere Radiative Fluxes Climate Data Record

Author(s):
Akkermans, Tom; Clerbaux, Nicolas
Publication title: Journal of Atmospheric and Oceanic Technology
2023
 | Volume: 40 | Issue: 11
2023
DOI: 10.1175/JTECH-D-23-0065.1
Abstract:
Abstract The third edition of the CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data (CLARA-A3) contains for the first time the top-of… Abstract The third edition of the CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data (CLARA-A3) contains for the first time the top-of-atmosphere products reflected solar flux (RSF) and outgoing longwave radiation (OLR), which are presented and validated using CERES, HIRS, and ERA5 reference data. The products feature an unprecedented resolution (0.25°) and time span (4 decades) and offer synergy and compatibility with other CLARA-A3 products. The RSF is relatively stable; its bias with respect to (w.r.t.) ERA5 remains mostly within ±2 W m−2. Deviations are predominantly caused by absence of either morning or afternoon satellite, mostly during the first decade. The radiative impact of the Pinatubo volcanic eruption is estimated at 3 W m−2. The OLR is stable w.r.t. ERA5 and HIRS, except during 1979–80. OLR regional uncertainty w.r.t. HIRS is quantified by the mean absolute bias (MAB) and correlates with observation density and time (satellite orbital configuration), which is optimal during 2002–16, with monthly and daily MAB of approximately 1.5 and 3.5 W m−2, respectively. Daily OLR uncertainty is higher (MAB +40%) during periods with only morning or only afternoon observations (1979–87). During the CERES era (2000–20), the OLR uncertainties w.r.t. CERES-EBAF, CERES-SYN, and HIRS are very similar. The RSF uncertainty achieves optimal results during 2002–16 with a monthly MAB w.r.t. CERES-EBAF of ∼2 W m−2 and a daily MAB w.r.t. CERES-SYN of ∼5 W m−2, and it is more sensitive to orbital configuration than is OLR. Overall, validation results are satisfactory for this first release of TOA flux products in the CLARA-A3 portfolio. more
Atmosphere CM-SAF Climate Data Records Validation

Validation of Himawari-8 Sea Surface Temperature Retrievals Using Infrared SST Autonomous Radiometer Measurements

Author(s):
Zhang, H.; Beggs, H.; Griffin, C.; Govekar, P.D.
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 11
2023
DOI: 10.3390/rs15112841
Abstract:
This study has evaluated five years (2016–2020) of Himawari-8 (H8) Sea Surface Temperature (SST) Level 2 Pre-processed (L2P) data produced by the Aust… This study has evaluated five years (2016–2020) of Himawari-8 (H8) Sea Surface Temperature (SST) Level 2 Pre-processed (L2P) data produced by the Australian Bureau of Meteorology (Bureau) against shipborne radiometer SST measurements obtained from the Infrared SST Autonomous Radiometer (ISAR) onboard research vessel RV Investigator. Before being used, all data sets employed in this study have gone through careful quality control, and only the most trustworthy measurements are retained. With a large matchup database (31,871 collocations in total, including 16,418 during daytime and 15,453 during night-time), it is found that the Bureau H8 SST product is of good quality, with a mean bias ± standard deviation (SD) of −0.12 °C ± 0.47 °C for the daytime and −0.04 °C ± 0.37 °C for the night-time. The performance of the H8 data under different environmental conditions, determined by the observations obtained concurrently from RV Investigator, is examined. Daytime and night-time satellite data behave slightly differently. During the daytime, a cold bias can be seen under almost all environmental conditions, including for most values of wind speed, SST, and relative humidity. On the other hand, the performance of the night-time H8 SST product is consistently more stable under most meteorological conditions with the mean bias usually close to zero. © 2023 by the authors. more
Application Atmosphere NWP-SAF Software for CDR development

Using Model Cloud Information to Reassign Low-Level Atmospheric Motion Vectors in the ECMWF Assimilation System

Author(s):
Lean, K.; Bormann, N.
Publication title: Journal of Applied Meteorology and Climatology
2023
 | Volume: 62 | Issue: 3
2023
DOI: 10.1175/JAMC-D-22-0094.1
Abstract:
This paper investigates the use of model cloud information in the assimilation of low-level atmospheric motion vectors (AMVs) in the ECMWF global data… This paper investigates the use of model cloud information in the assimilation of low-level atmospheric motion vectors (AMVs) in the ECMWF global data assimilation system, with the aim to characterize and address issues encountered in the assimilation of these observations. An analysis of background departure statistics (comparison of observations with the model background) shows that AMVs placed above the model cloud show larger deviations from the model background relative to those placed unrealistically close to the surface. Reassigning the pressure of AMVs diagnosed above the model cloud layer to either the model cloud top, cloud base, or average pressure leads to improvements in rootmean-square vector difference (RMSVD) and speed bias against the background wind fields. In assimilation experiments, reassigning AMVs placed above the model cloud to the model cloud top, cloud base, or average pressure results overall in a positive impact on subsequent forecasts. The reassignment to an average model cloud pressure performs best in this respect, and this approach has been implemented in the operational ECMWF system in October 2021. © 2023 American Meteorological Society. more
Application Atmosphere Climate Data Records EUM-Secr Validation

Upper ocean warming and sea ice reduction in the East Greenland Current from 2003 to 2019

Author(s):
de Steur, Laura; Sumata, Hiroshi; Divine, Dmitry V.; Granskog, Mats A.; Pavlova, Olga
Publication title: Communications Earth & Environment
2023
 | Volume: 4 | Issue: 1
2023
DOI: 10.1038/s43247-023-00913-3
Abstract:
The sea ice extent and sea ice thickness in the Arctic Ocean have declined consistently in the last decades. The loss of sea ice as well as warmer inf… The sea ice extent and sea ice thickness in the Arctic Ocean have declined consistently in the last decades. The loss of sea ice as well as warmer inflowing Atlantic Water have major consequences for the Arctic Ocean heat content and the watermasses flowing out from the Arctic. Sustained observations from ocean moorings show that the upper ocean temperature across the Arctic outflow with the East Greenland Current in the Fram Strait has increased significantly between 2003 and 2019. Polar Water contains more heat in summer due to lower sea ice concentration and longer periods of open water upstream. Warm returning Atlantic Water has a greater presence in the central Fram Strait in winter since 2015, impacting winter sea ice thickness and extent. Combined, these processes result in a reduced sea ice cover downstream along the whole east coast of Greenland with inevitable consequences for winter-time ocean convection and ecosystem functioning. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Under-ice observations by trawls and multi-frequency acoustics in the Central Arctic Ocean reveals abundance and composition of pelagic fauna

Author(s):
Ingvaldsen, Randi B.; Eriksen, Elena; Gjøsæter, Harald; Engås, Arill; Schuppe, Birte Katarina; Assmann, Karen M.; Cannaby, Heather; Dalpadado, Padmini; Bluhm, Bodil A.
Publication title: Scientific Reports
2023
 | Volume: 13 | Issue: 1
2023
DOI: 10.1038/s41598-023-27957-x
Abstract:
The rapid ongoing changes in the Central Arctic Ocean call for baseline information on the pelagic fauna. However, sampling for motile organisms which… The rapid ongoing changes in the Central Arctic Ocean call for baseline information on the pelagic fauna. However, sampling for motile organisms which easily escape vertically towed nets is challenging. Here, we report the species composition and catch weight of pelagic fishes and larger zooplankton from 12 trawl hauls conducted in ice covered waters in the Central Arctic Ocean beyond the continental slopes in late summer. Combined trawl catches with acoustics data revealed low amounts of fish and zooplankton from the advective influenced slope region in the Nansen Basin in the south to the ice-covered deep Amundsen Basin in the north. Both arctic and subarctic-boreal species, including the ones considered as Atlantic expatriate species were found all the way to 87.5o N. We found three fish species (Boreogadus saida, Benthosema glaciale and Reinhardtius hippoglossoides), but the catch was limited to only seven individuals. Euphausiids, amphipods and gelatinous zooplankton dominated the catch weight in the Nansen Basin in the mesopelagic communities. Euphausiids were almost absent in the Amundsen Basin with copepods, amphipods, chaetognaths and gelatinous zooplankton dominating. We postulate asymmetric conditions in the pelagic ecosystems of the western and eastern Eurasian Basin caused by ice and ocean circulation regimes. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Tundra Browning in the Indigirka Lowlands (North-Eastern Siberia) Explained by Drought, Floods and Small-Scale Vegetation Shifts

Author(s):
Magnússon, R.Í.; Groten, F.; Bartholomeus, H.; van Huissteden, K.; Heijmans, M.M.P.D.
Publication title: Journal of Geophysical Research: Biogeosciences
2023
 | Volume: 128 | Issue: 7
2023
DOI: 10.1029/2022JG007330
Abstract:
Contrary to the general “greening of the Arctic”, the Siberian Indigirka Lowlands show strong “browning” (a decrease in the Normalized Difference Vege… Contrary to the general “greening of the Arctic”, the Siberian Indigirka Lowlands show strong “browning” (a decrease in the Normalized Difference Vegetation Index or “NDVI”) in various recent satellite records. Since greening and browning are generally indicative of increases and losses in photosynthetically active biomass, this browning trend may have implications for the carbon balance and vegetation of this Arctic tundra region. To explore potential mechanisms responsible for this trend break from general Arctic greening, we studied timeseries of Landsat summer maximum NDVI, weather data, and high-resolution maps of vegetation compositional change, topography, geomorphology and hydrology. We find that a significant proportion of browning (lower summer NDVI) is explained by moisture dynamics, with high snow depths and resulting floods as well as summer drought coinciding with low NDVI. Relations between seasonal weather variables and NDVI are spatially heterogeneous, with floodplains, drained thaw lake basins and Yedoma ridges showing different patterns of association with weather variables. Low summer NDVI after high snowfall was particularly evident in floodplains, likely explained by early summer floods. Local small-scale vegetation changes explained only small amounts of variance in browning rates in Landsat NDVI. Local expansion of Sphagnum vegetation in particular may have contributed to recent browning of our study site, but higher resolution NDVI timeseries are necessary to accurately constrain the role of small-scale vegetation shifts. Overall, associations identified in this study suggest that future increases in Arctic precipitation variability and extremes may limit tundra greening, but to different extents even across comparatively small topographical contrasts. © 2023. The Authors. more
Application Climate Data Records H-SAF Land

Towards a new generation of artificial-intelligence-based infrared atmospheric sounding interferometer retrievals of surface temperature: Part II - Assessment

Author(s):
Boucher, E; Aires, F
Publication title: QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
2023
 | Volume: 149 | Issue: 754
2023
DOI: 10.1002/qj.4472
Abstract:
When using neural networks (NNs), the lack of input information characterizing the radiative transfer can result in regional biases, especially when r… When using neural networks (NNs), the lack of input information characterizing the radiative transfer can result in regional biases, especially when retrieving surface properties. In the Part I companion article we explored localization techniques in an attempt to help the NN adjust its behaviour to local conditions. In this article we analyze results from an image-processing approach, the novel localized convolutional NN (CNN) model for the retrieval of surface temperature (TS) over a fixed domain using infrared atmospheric sounding interferometer (IASI) observations. An in-depth evaluation is performed. The localized-CNN architecture is a promising artificial intelligence solution that provides retrievals similar to, if not better than, those of the European Organisation for the Exploitation of Meteorological Satellites' PWLR3 retrieval algorithm that also uses IASI observations, collocated with microwave data too. This shows the benefits of localizing the CNN retrieval. This image-processing retrieval scheme allows interpolation of the TS below the clouds, and thus a preliminary analysis of the cloud impact on the TS is performed. The possibility to estimate retrieval uncertainties is investigated, and a practical solution, based on the binning of the input space, is proposed for CNN architectures. The best strategy for a global-scale retrieval is yet to be found for such an image-processing scheme, but potential solutions and their respective advantages and disadvantages are discussed. more
Application Atmosphere Climate Data Records EUM-Secr Land

Thunderstorm Nowcasting With Deep Learning: A Multi-Hazard Data Fusion Model

Author(s):
Leinonen, J.; Hamann, U.; Sideris, I.V.; Germann, U.
Publication title: Geophysical Research Letters
2023
 | Volume: 50 | Issue: 8
2023
DOI: 10.1029/2022GL101626
Abstract:
Predictions of thunderstorm-related hazards are needed in several sectors, including first responders, infrastructure management and aviation. To addr… Predictions of thunderstorm-related hazards are needed in several sectors, including first responders, infrastructure management and aviation. To address this need, we present a deep learning model that can be adapted to different hazard types. The model can utilize multiple data sources; we use data from weather radar, lightning detection, satellite visible/infrared imagery, numerical weather prediction and digital elevation models. We demonstrate the ability of the model to predict lightning, hail and heavy precipitation probabilistically on a 1 km resolution grid, with a temporal resolution of 5 min and lead times up to 60 min. Shapley values quantify the importance of the different data sources, showing that the weather radar products are the most important predictors for all three hazard types. © 2023 The Authors. more
Application Atmosphere NWC-SAF Software for CDR development

The Solar Energy Potential of Greece for Flat-Plate Solar Panels Mounted on Double-Axis Systems

Author(s):
Kambezidis, Harry D.; Mimidis, Konstantinos; Kavadias, Kosmas A.
Publication title: Energies
2023
 | Volume: 16 | Issue: 13
2023
DOI: 10.3390/en16135067
Abstract:
The aim of the present work is to investigate the efficiency of flat-plate solar panels in Greece for delivering solar energy. In this study, the sola… The aim of the present work is to investigate the efficiency of flat-plate solar panels in Greece for delivering solar energy. In this study, the solar panels are mounted on a two-axis tracker, which follows the daily path of the sun. In this context, the annual energy sums are estimated on such surfaces from hourly solar horizontal radiation values at forty-three locations, covering all of Greece. The solar horizontal radiation values are embedded in the typical meteorological years of the sites obtained from the PVGIS tool. All calculations use near-real surface-albedo values for the sites, and isotropic and anisotropic models are used to estimate the diffuse-inclined radiation. The analysis provides non-linear regression expressions for the energy sums as a function of time (month, season). The annual energy sums are found to vary between 2247 kWhm−2 and 2878 kWhm−2 under all-sky conditions with the anisotropic transposition model. Finally, maps of Greece showing the distribution of the annual and seasonal solar energy sums under all- and clear-sky conditions are derived for the first time, and these maps constitute the main innovation of this work. more
Application Atmosphere CM-SAF Climate Data Records

The sensitivity of primary productivity in Disko Bay, a coastal Arctic ecosystem, to changes in freshwater discharge and sea ice cover

Author(s):
Møller, E.F.; Christensen, A.; Larsen, J.; Mankoff, K.D.; Ribergaard, M.H.; Sejr, M.; Wallhead, P.; Maar, M.
Publication title: Ocean Science
2023
 | Volume: 19 | Issue: 2
2023
DOI: 10.5194/os-19-403-2023
Abstract:
The Greenland ice sheet is melting, and the rate of ice loss has increased 6-fold since the 1980s. At the same time, the Arctic sea ice extent is decr… The Greenland ice sheet is melting, and the rate of ice loss has increased 6-fold since the 1980s. At the same time, the Arctic sea ice extent is decreasing. Meltwater runoff and sea ice reduction both influence light and nutrient availability in the coastal ocean, with implications for the timing, distribution, and magnitude of phytoplankton production. However, the integrated effect of both glacial and sea ice melt is highly variable in time and space, making it challenging to quantify. In this study, we evaluate the relative importance of these processes for the primary productivity of Disko Bay, west Greenland, one of the most important areas for biodiversity and fisheries around Greenland. We use a high-resolution 3D coupled hydrodynamic-biogeochemical model for 2004-2018 validated against in situ observations and remote sensing products. The model-estimated net primary production (NPP) varied between 90-147 C m-2 yr-1 during 2004-2018, a period with variable freshwater discharges and sea ice cover. NPP correlated negatively with sea ice cover and positively with freshwater discharge. Freshwater discharge had a strong local effect within ∼25 km of the source-sustaining productive hot spots during summer. When considering the annual NPP at bay scale, sea ice cover was the most important controlling factor. In scenarios with no sea ice in spring, the model predicted a ∼30% increase in annual production compared to a situation with high sea ice cover. Our study indicates that decreasing ice cover and more freshwater discharge can work synergistically and will likely increase primary productivity of the coastal ocean around Greenland. © 2023 Eva Friis Møller et al. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

The Potential of Lakes for Extracting Renewable Energy—A Case Study of Brates Lake in the South-East of Europe

Author(s):
Rusu, Eugen; Georgescu, Puiu Lucian; Onea, Florin; Yildirir, Victoria; Dragan, Silvia
Publication title: Inventions
2023
 | Volume: 8 | Issue: 6
2023
DOI: 10.3390/inventions8060143
Abstract:
The aim of this work is to provide some details regarding the energy potential of the local wind and solar resources near the Galati area (south-east … The aim of this work is to provide some details regarding the energy potential of the local wind and solar resources near the Galati area (south-east of Romania) by considering the performances of a few recent technologies. Based on 22 years of ERA5 data (2001–2022), a picture concerning the renewable energy resources in the Brates Lake area is provided. Comparing the wind and solar resources with in situ and satellite data, a relatively good agreement was found, especially in regards to the average values. In terms of wind speed conditions at a hub height of 100 m, we can expect a maximum value of 19.28 m/s during the winter time, while for the solar irradiance the energy level can reach up to 932 W/m2 during the summer season. Several generators of 2 MW were considered for evaluation, for which a state-of-the-art system of 6.2 MW was also added. The expected capacity factor of the turbines is in the range of (11.71–21.23)%, with better performances being expected from the Gamesa G90 generator. As a next step, several floating solar units were considered in order to simulate large-scale solar projects that may cover between 10 and 40% of the Brates Lake surface. The amount of the evaporated water saved by these solar panels was also considered, being estimated that the water demand of at least 3.42 km2 of the agricultural areas can be covered on an annual scale. more
Application Atmosphere CM-SAF Climate Data Records

The Impacts of Optimizing Model-Dependent Parameters on the Antarctic Sea Ice Data Assimilation

Author(s):
Luo, H.; Yang, Q.; Mazloff, M.; Nerger, L.; Chen, D.
Publication title: Geophysical Research Letters
2023
 | Volume: 50 | Issue: 22
2023
DOI: 10.1029/2023GL105690
Abstract:
Given the role played by the historical and extensive coverage of sea ice concentration (SIC) observations in reconstructing the long-term variability… Given the role played by the historical and extensive coverage of sea ice concentration (SIC) observations in reconstructing the long-term variability of Antarctic sea ice, and the limited attention given to model-dependent parameters in current sea ice data assimilation studies, this study focuses on enhancing the performance of the Data Assimilation System for the Southern Ocean in assimilating SIC through optimizing the localization and observation error estimate, and two assimilation experiments were conducted from 1979 to 2018. By comparing the results with the sea ice extent of the Southern Ocean and the sea ice thickness in the Weddell Sea, it becomes evident that the experiment with optimizations outperforms that without optimizations due to achieving more reasonable error estimates. Investigating uncertainties of the sea ice volume anomaly modeling reveals the importance of the sea ice-ocean interaction in the SIC assimilation, implying the necessity of assimilating more oceanic and sea-ice observations. © 2023 The Authors. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

The IASI NH3 version 4 product: averaging kernels and improved consistency

Author(s):
Clarisse, L.; Franco, B.; Van Damme, M.; Di Gioacchino, T.; Hadji-Lazaro, J.; Whitburn, S.; Noppen, L.; Hurtmans, D.; Clerbaux, C.; Coheur, P.
Publication title: Atmospheric Measurement Techniques
2023
 | Volume: 16 | Issue: 21
2023
DOI: 10.5194/amt-16-5009-2023
Abstract:
Satellite measurements play an increasingly important role in the study of atmospheric ammonia (NH3). Here, we present version 4 of the Artificial Neu… Satellite measurements play an increasingly important role in the study of atmospheric ammonia (NH3). Here, we present version 4 of the Artificial Neural Network for IASI (ANNI; IASI: Infrared Atmospheric Sounding Interferometer) retrieval of NH3. The main change is the introduction of total column averaging kernels (AVKs), which can be used to undo the effect of the vertical profile shape assumption of the retrieval. While the main equations can be matched term for term with analogous ones used in UV/Vis retrievals for other minor absorbers, we derive the formalism from the ground up, as its applicability to thermal infrared measurements is non-trivial. A large number of other smaller changes were introduced in ANNI v4, most of which improve the consistency of the measurements across time and across the series of IASI instruments. This includes a more robust way of calculating the hyperspectral range index (HRI), explicitly accounting for long-term changes in CO2 in the HRI calculation and the use of a reprocessed cloud product that was specifically developed for climate applications. The NH3 distributions derived with ANNI v4 are very similar to the ones derived with v3, although values are about 10 %-20 % larger due to the improved setup of the HRI. We exclude further large biases of the same nature by showing the consistency between ANNI v4 derived NH3 columns with columns obtained with an optimal estimation approach. Finally, with v4, we revised the uncertainty budget and now report systematic uncertainty estimates alongside random uncertainties, allowing realistic mean uncertainties to be estimated. Copyright: © 2023 Lieven Clarisse et al. more
Application Atmosphere Climate Data Records EUM-Secr

The Arctic Amplification and Its Impact: A Synthesis through Satellite Observations

Author(s):
Esau, Igor; Pettersson, Lasse H.; Cancet, Mathilde; Chapron, Bertrand; Chernokulsky, Alexander; Donlon, Craig; Sizov, Oleg; Soromotin, Andrei; Johannesen, Johnny A.
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 5
2023
DOI: 10.3390/rs15051354
Abstract:
Arctic climate change has already resulted in amplified and accelerated regional warming, or the Arctic amplification. Satellite observations have cap… Arctic climate change has already resulted in amplified and accelerated regional warming, or the Arctic amplification. Satellite observations have captured this climate phenomenon in its development and in sufficient spatial details. As such, these observations have been—and still are—indispensable for monitoring of the amplification in this remote and inhospitable region, which is sparsely covered with ground observations. This study synthesizes the key contributions of satellite observations into an understanding and characterization of the amplification. The study reveals that the satellites were able to capture a number of important environmental transitions in the region that both precede and follow the emergence of the apparent amplification. Among those transitions, we find a rapid decline in the multiyear sea ice and subsequent changes in the surface radiation balance. Satellites have witnessed the impact of the amplification on phytoplankton and vegetation productivity as well as on human activity and infrastructure. Satellite missions of the European Space Agency (ESA) are increasingly contributing to amplification monitoring and assessment. The ESA Climate Change Initiative has become an essential provider of long-term climatic-quality remote-sensing data products for essential climate variables. Still, such synthesis has found that additional efforts are needed to improve cross-sensor calibrations and retrieval algorithms and to reduce uncertainties. As the amplification is set to continue into the 21st century, a new generation of satellite instruments with improved revisiting time and spectral and spatial resolutions are in high demand in both research and stakeholders’ communities. more
Application CM-SAF Climate Data Records Cryosphere OSI-SAF Ocean

Temporal Variation of Sunshine Duration and Its Potential Affecting Factors with Emphasis on Saudi Arabia for the Period 1983-2022

Author(s):
Anwar, Mohammad Ibna; Farhan, Khatib Zada; Alam, M. J. B.; Anwar, Aiyesha
Publication title: International Journal of Environment and Climate Change
2023
 | Volume: 13 | Issue: 12
2023
DOI: 10.9734/ijecc/2023/v13i123705
Abstract:
The rising trend in fossil fuel prices and the depletion of natural resource reserves in the future force the authority of any country to find a more … The rising trend in fossil fuel prices and the depletion of natural resource reserves in the future force the authority of any country to find a more sustainable option for energy sources, so that future energy demand can be ensured for sustainable development. Assessing the trend and availability of sunshine duration (SD) at a spatiotemporal scale and the effect of different metrological parameters on the SD change is crucial to ensure the efficient utilization of solar energy, support the growth of renewable energy systems, and contribute to a sustainable future. In Saudi Arabia, The average monthly SD is 283 ± 18 hm<sup>-1</sup>, and there was a rising trend of SD that increased at a rate of 1.48 hy<sup>-1</sup> with a 95% confidence level. Most of the regions experienced an annual mean of SD between 3375 and 3754 hy<sup>-1</sup>, except for the southwest and the middle-eastern part where SD was between 3072 and 3375 hours in a year.  The highest mean monthly SD was 318 ± 39 hm-1 during the summer season, but the trend of SD changes over the years was downward ( -0.21 hy<sup>-1</sup>). The mean monthly SD was lowest (244 ± 38 hm<sup>-1</sup>) in the winter season, and the changing pattern of SD was on the rise at a rate of 0.26 hy<sup>-1</sup> with a 95% confidence level. There was a decline in SD across the country between 1983 and 1998, whereas from 2000 onward the country experienced an upward trend in SD. Relative humidity (R = -0.53, p < 0.01) and cloud cover (R = -0.42, p < 0.05) as potential factors have a strong negative correlation with SD, whereas wind speed (R = 0.06, p > 0.1) and temperature (R = 0.12, p > 0.1) have a positive correlation with SD in the region. more
Atmosphere CM-SAF Climate Data Records Validation

Ten years of 1 Hz solar irradiance observations at Cabauw, the Netherlands, with cloud observations, variability classifications, and statistics

Author(s):
Mol, W.B.; Knap, W.H.; Van Heerwaarden, C.C.
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 5
2023
DOI: 10.5194/essd-15-2139-2023
Abstract:
Surface solar irradiance varies on scales down to seconds, and detailed long-Term observational datasets of this variable are rare but in high demand.… Surface solar irradiance varies on scales down to seconds, and detailed long-Term observational datasets of this variable are rare but in high demand. Here, we present an observational dataset of global, direct, and diffuse solar irradiance sampled at 1ĝ€¯Hz as well as fully resolved variability until at least 0.1ĝ€¯Hz over a period of 10 years from the Baseline Surface Radiation Network (BSRN) station at Cabauw, the Netherlands. The dataset is complemented with irradiance variability classifications, clear-sky irradiance and aerosol reanalysis, information about the solar position, observations of clouds and sky type, and wind measurements up to 200ĝ€¯m above ground level. Statistics of variability derived from all time series include approximately 185ĝ€¯000 detected events of both cloud enhancement and cloud shadows. Additional observations from the Cabauw measurement site are freely available from the open-data platform of the Royal Netherlands Meteorological Institute. This paper describes the observational site, quality control, classification algorithm with validation, and the processing method of complementary products. Additionally, we discuss and showcase (potential) applications, including limitations due to sensor response time. These observations and derived statistics provide detailed information to aid research into how clouds and atmospheric composition influence solar irradiance variability as well as information to help validate models that are starting to resolve variability at higher fidelity. The main datasets are available at 10.5281/zenodo.7093164 and 10.5281/zenodo.7462362 ; the reader is referred to the "Code and data availability"section of this paper for the complete list. © Copyright: more
Application Atmosphere CM-SAF Climate Data Records

Temporal prediction of shallow landslides exploiting soil saturation degree derived by ERA5-Land products

Author(s):
Bordoni, Massimiliano; Vivaldi, Valerio; Ciabatta, Luca; Brocca, Luca; Meisina, Claudia
Publication title: Bulletin of Engineering Geology and the Environment
2023
 | Volume: 82 | Issue: 8
2023
DOI: 10.1007/s10064-023-03304-2
Abstract:
ERA5-Land service has been released recently as an integral and operational component of Copernicus Climate Change Service. Within its set of climatol… ERA5-Land service has been released recently as an integral and operational component of Copernicus Climate Change Service. Within its set of climatological and atmospheric parameters, it provides soil moisture estimates at different soil depths, represeting an important tool for retrieving saturation degree for predicting natural hazards as shallow landslides. This paper represents an innovative attempt aiming to exploit the use of saturation degree derived from ERA5-Land soil moisture products in a data-driven model to predict the daily probability of occurence of shallow landslides. The study was carried out by investigating a multi-temporal inventory of shallow landslides occurred in Oltrepò Pavese (northern Italy). The achieved results follow: (i) ERA5-Land-derived saturation degree reconstructs well field trends measured in the study area until 1 m from ground; (ii) in agreement with the typical sliding surfaces depth, saturation degree values obtained since ERA5-Land 28–100 cm layer represent a significant predictor for the estimation of temporal probability of occurrence of shallow landslides, able especially to reduce overestimation of triggering events; (iii) saturation degree estimated by ERA5-Land 28–100 cm layer allows to detect soil hydrological conditions leading to triggering in the study area, represented by saturation degree in this layer close to complete saturation. Even if other works of research are required in different geological and geomorphological settings, this study demonstrates that ERA5-Land-derived saturation degree could be implemented to identify triggering conditions and to develop prediction methods of shallow landslides, thanks also to its free availability and constantly updating with a delay of 5 days. more
Application Climate Data Records H-SAF Land Validation

Sudden Stratospheric Warmings in the Northern Hemisphere Observed With IASI

Author(s):
Bouillon, M.; Safieddine, S.; Clerbaux, C.
Publication title: Journal of Geophysical Research: Atmospheres
2023
 | Volume: 128 | Issue: 17
2023
DOI: 10.1029/2023JD038692
Abstract:
Sudden Stratospheric Warming events (SSW) are extreme phenomena during which stratospheric temperature can increase by tens of degrees in a few days. … Sudden Stratospheric Warming events (SSW) are extreme phenomena during which stratospheric temperature can increase by tens of degrees in a few days. They are due to the propagation and breaking of the planetary waves, leading to a perturbation of the polar vortex. SSWs also influence polar ozone concentrations and midlatitude weather. The Infrared Atmospheric Sounding Interferometers (IASI) monitor atmospheric composition and temperature globally since 2007, and they are ideal to observe the changes of temperature and ozone during SSWs. Since the launch of the first IASI, there have been several SSWs in the Northern Hemisphere, including eight major events that are investigated in this study. We find that during major SSWs, the temperature anomaly propagates from 10 hPa to the lower stratosphere and the maximum anomaly at 200 hPa is correlated to the maximum anomaly at 10 hPa. During these events, negative anomalies of temperature in Europe and Russia and positive anomalies in Canada and Greenland are often observed at 750 hPa. The cold air outbreaks that usually follow major SSWs are responsible for anomalies of −15 K. Finally, we look at the evolution of the total ozone column following major events. Major SSWs lead to higher springtime ozone concentrations and the ozone anomaly in March is correlated to the duration of the positive temperature anomaly at 10 hPa. These results show the potential of the IASI mission and its successors, IASI-New Generation, for the study of SSWs and their effects on weather and atmospheric composition. © 2023 The Authors. more
Application Atmosphere Climate Data Records EUM-Secr

Subseasonal Prediction of Regional Antarctic Sea Ice by a Deep Learning Model

Author(s):
Wang, Y.; Yuan, X.; Ren, Y.; Bushuk, M.; Shu, Q.; Li, C.; Li, X.
Publication title: Geophysical Research Letters
2023
 | Volume: 50 | Issue: 17
2023
DOI: 10.1029/2023GL104347
Abstract:
Antarctic sea ice concentration (SIC) prediction at seasonal scale has been documented, but a gap remains at subseasonal scale (1–8 weeks) due to limi… Antarctic sea ice concentration (SIC) prediction at seasonal scale has been documented, but a gap remains at subseasonal scale (1–8 weeks) due to limited understanding of ice-related physical mechanisms. To overcome this limitation, we developed a deep learning model named Sea Ice Prediction Network (SIPNet) that can predict SIC without the need to account for complex physical processes. Compared to mainstream dynamical models like European Centre for Medium-Range Weather Forecasts, National Centers for Environmental Prediction, and Seamless System for Prediction and Earth System Research developed at Geophysical Fluid Dynamics Laboratory, as well as a relatively advanced statistical model like the linear Markov model, SIPNet outperforms them all, effectively filling the gap in subseasonal Antarctic SIC prediction capability. SIPNet results indicate that autumn SIC variability contributes the most to sea ice predictability, whereas spring contributes the least. In addition, the Weddell Sea displays the highest sea ice predictability, while predictability is low in the West Pacific. SIPNet can also capture the signal of ENSO and SAM on sea ice. © 2023. The Authors. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Stratocumulus adjustments to aerosol perturbations disentangled with a causal approach

Author(s):
Fons, E; Runge, J; Neubauer, D; Lohmann, U
Publication title: NPJ CLIMATE AND ATMOSPHERIC SCIENCE
2023
 | Volume: 6 | Issue: 1
2023
DOI: 10.1038/s41612-023-00452-w
Abstract:
A large fraction of the uncertainty around future global warming is due to the cooling effect of aerosol-liquid cloud interactions, and in particular … A large fraction of the uncertainty around future global warming is due to the cooling effect of aerosol-liquid cloud interactions, and in particular to the elusive sign of liquid water path (LWP) adjustments to aerosol perturbations. To quantify this adjustment, we propose a causal approach that combines physical knowledge in the form of a causal graph with geostationary satellite observations of stratocumulus clouds. This allows us to remove confounding influences from large-scale meteorology and to disentangle counteracting physical processes (cloud-top entrainment enhancement and precipitation suppression due to aerosol perturbations) on different timescales. This results in weak LWP adjustments that are time-dependent (first positive then negative) and meteorological regime-dependent. More importantly, the causal approach reveals that failing to account for covariations of cloud droplet sizes and cloud depth, which are, respectively, a mediator and a confounder of entrainment and precipitation influences, leads to an overly negative aerosol-induced LWP response. This would result in an underestimation of the cooling influence of aerosol-cloud interactions. more
Application Atmosphere CM-SAF Climate Data Records

State of the Climate in 2022

Author(s):
Blunden, J.; Boyer, T.; Bartow-Gillies, E.
Publication title: Bulletin of the American Meteorological Society
2023
 | Volume: 104 | Issue: 9
2023
DOI: 10.1175/2023BAMSStateoftheClimate.1
Abstract:
Abstract Editors note: For easy download the posted pdf of the State of the Climate in 2022 is a low-resolution file. A hig… Abstract Editors note: For easy download the posted pdf of the State of the Climate in 2022 is a low-resolution file. A high-resolution copy of the report is available by clicking here . Please be patient as it may take a few minutes for the high-resolution file to download. more
Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Spatiotemporal variability in precipitation-growth association of Betula nana in the Siberian lowland tundra

Author(s):
Magnússon, R.Í.; Sass-Klaassen, U.; Limpens, J.; Karsanaev, S.V.; Ras, S.; van Huissteden, K.; Blok, D.; Heijmans, M.M.P.D.
Publication title: Journal of Ecology
2023
 | Volume: 111 | Issue: 9
2023
DOI: 10.1111/1365-2745.14165
Abstract:
Shrubs are expanding across a warming Arctic, evident from range expansion and increases in biomass, stature and cover. This influences numerous aspec… Shrubs are expanding across a warming Arctic, evident from range expansion and increases in biomass, stature and cover. This influences numerous aspects of Arctic ecosystems. While shrub growth is generally positively associated with summer temperature, tundra ecosystems are characterised by abiotic gradients on small spatial scales (metres), and the Arctic climate and its year-to-year variability are changing rapidly. Hence, it is often unclear to what extent climate-growth associations are scalable to future climate scenarios and across environmental gradients within ecosystems. Here, we investigate the stability of climate–growth associations of Arctic dwarf shrubs across small-scale (metre to kilometre) topographic gradients and decadal timescales. We constructed ring width series (1974–2018) for a common Arctic dwarf shrub (Betula nana) for three representative types of subsites in the Siberian lowland tundra: higher elevation, lower elevation and thermokarst-affected (thaw ponds) terrain. We quantified decadal variability in climate–growth associations across subsites using partial least squares regression and a moving window approach. We found consistently positive association of shrub radial growth with summer temperature, but substantial spatial and temporal variability in precipitation response. Association of shrub growth with summer rainfall increased in recent decades. Shrubs on elevated sites showed particularly strong response to rainfall following drier periods, and a negative association with recent snowfall extremes. Shrubs sampled from thaw ponds showed strong positive association with rainfall, followed by high shrub mortality after an extremely wet summer. This likely resulted from waterlogging due to thermokarst. Synthesis. Our findings imply that the response of shrub growth to changes in Arctic precipitation regimes is regulated by (i) macro- (kilometre-scale) and micro-topographical (metre-scale) gradients, (ii) colimitation between temperature and moisture and (iii) potentially nonlinear responses to precipitation extremes. This suggests that the scalability of precipitation-growth relationships for Arctic shrubs across dynamic tundra landscapes and future climate scenarios is limited. We recommend that future climate–growth studies on Arctic tundra shrubs simulate future precipitation changes across spatial gradients and include detailed microsite and shrub physiological monitoring. © 2023 The Authors. Journal of Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. more
Application Climate Data Records H-SAF Land

Spatial Heterogeneity of Aerosol Effect on Liquid Cloud Microphysical Properties in the Warm Season Over Tibetan Plateau

Author(s):
Zhao, Pengguo; Zhao, Wen; Yuan, Liang; Zhou, Xin; Ge, Fei; Xiao, Hui; Zhang, Peiwen; Wang, Yuting; Zhou, Yunjun
Publication title: Journal of Geophysical Research: Atmospheres
2023
 | Volume: 128 | Issue: 2
2023
DOI: 10.1029/2022JD037738
Abstract:
The effect of aerosol on liquid cloud microphysical properties over the Tibetan Plateau (TP) during the warm season is investigated by using aerosol i… The effect of aerosol on liquid cloud microphysical properties over the Tibetan Plateau (TP) during the warm season is investigated by using aerosol index (AI) and cloud property parameters data. Distinct differences in aerosol effect on liquid cloud microphysical properties have been found between the northern Tibetan Plateau (NTP) and southernTibetan Plateau (STP). The composite liquid cloud droplet effective radius liquid cloud droplet effective radius (LREF) anomalies for positive AI events are positive in the NTP and negative in the STP. In both NTP and STP, when the AI anomalies are positive, the LREF anomalies are also positive, which suggests that the increased aerosol loading reduces the solar radiation reaching the ground and thus enhances the atmospheric stability, which reduces the cloud base height and makes the liquid cloud area thicker, which gives cloud droplets more space to grow by collision-coalescence. This indicates that the aerosol radiative effect is not likely the reason causing the distinct differences of aerosol effects on liquid cloud properties between NTP and STP. Further analysis shows that in the STP, the LREF first increases and then decreases with the increase of AI, while in the NTP, the LREF always increases with the increase of AI, suggesting a spatial difference in aerosol microphysical effect. In the STP, the influence of aerosol on liquid clouds is mainly dependent on liquid water path and convective available potential energy, while in the NTP, the influence of aerosol on liquid cloud is more likely related to large aerosol particles. © 2023. American Geophysical Union. All Rights Reserved. more
Application Atmosphere CM-SAF Climate Data Records

Sources of seasonal sea-ice bias for CMIP6 models in the Hudson Bay Complex

Author(s):
Crawford, Alex D.; Rosenblum, Erica; Lukovich, Jennifer V.; Stroeve, Julienne C.
Publication title: Annals of Glaciology
2023
2023
DOI: 10.1017/aog.2023.42
Abstract:
The seasonal ice-free period in the Hudson Bay Complex (HBC) has grown longer in recent decades in response to warming, both from progressively earlie… The seasonal ice-free period in the Hudson Bay Complex (HBC) has grown longer in recent decades in response to warming, both from progressively earlier sea-ice retreat in summer and later sea-ice advance in fall. Such changes disrupt the HBC ecosystem and ice-based human activities. In this study, we compare 102 simulations from 37 models participating in phase 6 of the Coupled Model Intercomparison Project to the satellite passive microwave record and atmospheric reanalyses. We show that, throughout the HBC, models simulate an ice-free period that averages 30 d longer than in satellite observations. This occurs because seasonal sea-ice advance is unrealistically late and seasonal sea-ice retreat is unrealistically early. We find that much of the ice-season bias can be linked to a warm bias in the atmosphere that is associated with a southerly wind bias, especially in summer. Many models also exhibit an easterly wind bias during winter and spring, which reduces sea-ice convergence on the east side of Hudson Bay and impacts the spatial patterns of summer sea-ice retreat. These results suggest that, for many models, more realistic simulation of atmospheric circulation would improve their simulation of HBC sea ice. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Source mechanisms and transport patterns of tropospheric bromine monoxide: findings from long-term multi-axis differential optical absorption spectroscopy measurements at two Antarctic stations

Author(s):
Friess, U; Kreher, K; Querel, R; Schmithnsen, H; Smale, D; Weller, R; Platt, U
Publication title: ATMOSPHERIC CHEMISTRY AND PHYSICS
2023
 | Volume: 23 | Issue: 5
2023
DOI: 10.5194/acp-23-3207-2023
Abstract:
The presence of reactive bromine in polar regions is a widespread phenomenon that plays an important role in the photochemistry of the Arctic and Anta… The presence of reactive bromine in polar regions is a widespread phenomenon that plays an important role in the photochemistry of the Arctic and Antarctic lower troposphere, including the destruction of ozone, the disturbance of radical cycles, and the oxidation of gaseous elemental mercury. The chemical mechanisms leading to the heterogeneous release of gaseous bromine compounds from saline surfaces are in principle well understood. There are, however, substantial uncertainties about the contribution of different potential sources to the release of reactive bromine, such as sea ice, brine, aerosols, and the snow surface, as well as about the seasonal and diurnal variation and the vertical distribution of reactive bromine. Here we use continuous long-term measurements of the vertical distribution of bromine monoxide (BrO) and aerosols at the two Antarctic sites Neumayer (NM) and Arrival Heights (AH), covering the periods of 2003-2021 and 2012-2021, respectively, to investigate how chemical and physical parameters affect the abundance of BrO. We find the strongest correlation between BrO and aerosol extinction (R=0.56 for NM and R=0.28 for AH during spring), suggesting that the heterogeneous release of Br-2 from saline airborne particles (blowing snow and aerosols) is a dominant source for reactive bromine. Positive correlations between BrO and contact time of air masses, both with sea ice and the Antarctic ice sheet, suggest that reactive bromine is not only emitted by the sea ice surface but by the snowpack on the ice shelf and in the coastal regions of Antarctica. In addition, the open ocean appears to represent a source for reactive bromine during late summer and autumn when the sea ice extent is at its minimum. A source-receptor analysis based on back trajectories and sea ice maps shows that main source regions for BrO at NM are the Weddell Sea and the Filchner-Ronne Ice Shelf, as well as coastal polynyas where sea ice is newly formed. A strong morning peak in BrO frequently occurring during summer and that is particularly strong during autumn suggests a night-time build-up of Br-2 by heterogeneous reaction of ozone on the saline snowpack in the vicinity of the measurement sites. We furthermore show that BrO can be sustained for at least 3 d while travelling across the Antarctic continent in the absence of any saline surfaces that could serve as a source for reactive bromine. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy

Author(s):
Polo, Jesús; García, Redlich J.
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 3
2023
DOI: 10.3390/rs15030567
Abstract:
Solar cadasters are excellent tools for determining the most suitable rooftops and areas for PV deployment in urban environments. There are several op… Solar cadasters are excellent tools for determining the most suitable rooftops and areas for PV deployment in urban environments. There are several open models that are available to compute the solar potential in cities. The Solar Energy on Building Envelopes (SEBE) is a powerful model incorporated in a geographic information system (QGIS). The main input for these tools is the digital surface model (DSM). The accuracy of the DSM can contribute significantly to the uncertainty of the solar potential, since it is the basis of the shading and sky view factor computation. This work explores the impact of two different methodologies for creating a DSM to the solar potential. Solar potential is estimated for a small area in a university campus in Madrid using photogrammetry from google imagery and LiDAR data to compute different DSM. Large differences could be observed in the building edges and in the areas with a more complex and diverse topology that resulted in significant differences in the solar potential. The RSMD at a measuring point in the building rooftop can range from 10% to 50% in the evaluation of results. However, the flat and clear areas are much less affected by these differences. A combination of both techniques is suggested as future work to create an accurate DSM. more
Application Atmosphere CM-SAF Climate Data Records

Smart Approaches for Evaluating Photosynthetically Active Radiation at Various Stations Based on MSG Prime Satellite Imagery

Author(s):
Thomas, Claire; Wandji Nyamsi, William; Arola, Antti; Pfeifroth, Uwe; Trentmann, Jörg; Dorling, Stephen; Laguarda, Agustín; Fischer, Milan; Aculinin, Alexandr
Publication title: Atmosphere
2023
 | Volume: 14 | Issue: 8
2023
DOI: 10.3390/atmos14081259
Abstract:
Photosynthetically active radiation (PAR) is the 400–700 nm portion of the solar radiation spectrum that photoautotrophic organisms including plants, … Photosynthetically active radiation (PAR) is the 400–700 nm portion of the solar radiation spectrum that photoautotrophic organisms including plants, algae, and cyanobacteria use for photosynthesis. PAR is a key variable in global ecosystem and Earth system modeling, playing a prominent role in carbon and water cycling. Alongside air temperature, water availability, and atmospheric CO2 concentration, PAR controls photosynthesis and consequently biomass productivity in general. The management of agricultural and horticultural crops, forests, grasslands, and even grasses at sports venues is a non-exhaustive list of applications for which an accurate knowledge of the PAR resource is desirable. Modern agrivoltaic systems also require a good knowledge of PAR in conjunction with the variables needed to monitor the co-located photovoltaic system. In situ quality-controlled PAR sensors provide high-quality information for specific locations. However, due to associated installation and maintenance costs, such high-quality data are relatively scarce and generally extend over a restricted and sometimes non-continuous period. Numerous studies have already demonstrated the potential offered by surface radiation estimates based on satellite information as reliable alternatives to in situ measurements. The accuracy of these estimations is site-dependent and is related, for example, to the local climate, landscape, and viewing angle of the satellite. To assess the accuracy of PAR satellite models, we inter-compared 11 methods for estimating 30 min surface PAR based on satellite-derived estimations at 33 ground-based station locations over several climate regions in Europe, Africa, and South America. Averaged across stations, the results showed average relative biases (relative to the measurement mean) across methods of 1 to 20%, an average relative standard deviation of 25 to 30%, an average relative root mean square error of 25% to 35% and a correlation coefficient always above 0.95 for all methods. Improved performance was seen for all methods at relatively cloud-free sites, and quality degraded towards the edge of the Meteosat Second Generation viewing area. A good compromise between computational time, memory allocation, and performance was achieved for most locations using the Jacovides coefficient applied to the global horizontal irradiance from HelioClim-3 or the CAMS Radiation Service. In conclusion, satellite estimations can provide a reliable alternative estimation of ground-based PAR for most applications. more
Application Atmosphere CM-SAF Climate Data Records Method

Sensitivity of cloud-phase distribution to cloud microphysics and thermodynamics in simulated deep convective clouds and SEVIRI retrievals

Author(s):
Han, Cunbo; Hoose, Corinna; Stengel, Martin; Coopman, Quentin; Barrett, Andrew
Publication title: Atmospheric Chemistry and Physics
2023
 | Volume: 23 | Issue: 22
2023
DOI: 10.5194/acp-23-14077-2023
Abstract:
The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strong… The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strongly depend on their partitioning between the liquid and ice phases. In this study, we investigated the sensitivities of the cloud phase to the ice-nucleating particle (INP) concentration and thermodynamics. Moreover, passive satellite retrieval algorithms and cloud products were evaluated to identify whether they could detect cloud microphysical and thermodynamical perturbations. Experiments were conducted using the ICOsahedral Nonhydrostatic (ICON) model at the convection-permitting resolution of about 1.2 km on a domain covering significant parts of central Europe, and they were compared to two different retrieval products based on Spinning Enhanced Visible and InfraRed Imager (SEVIRI) measurements. We selected a day with multiple isolated deep convective clouds, reaching a homogeneous freezing temperature at the cloud top. The simulated cloud liquid pixel fractions were found to decrease with increasing INP concentration, both within clouds and at the cloud top. The decrease in the cloud liquid pixel fraction was not monotonic and was stronger in high-INP cases. Cloud-top glaciation temperatures shifted toward warmer temperatures with an increasing INP concentration by as much as 8 ∘C. Moreover, the impact of the INP concentration on cloud-phase partitioning was more pronounced at the cloud top than within the cloud. Furthermore, initial and lateral boundary temperature fields were perturbed with increasing and decreasing temperature increments from 0 to ±3 and ±5 K between 3 and 12 km, respectively. Perturbing the initial thermodynamic state was also found to systematically affect the cloud-phase distribution. However, the simulated cloud-top liquid pixel fraction, diagnosed using radiative transfer simulations as input to a satellite forward operator and two different satellite remote-sensing retrieval algorithms, deviated from one of the satellite products regardless of perturbations in the INP concentration or the initial thermodynamic state for warmer subzero temperatures while agreeing with the other retrieval scheme much better, in particular for the high-INP and high-CAPE (convective available potential energy) scenarios. Perturbing the initial thermodynamic state, which artificially increases the instability of the mid- and upper-troposphere, brought the simulated cloud-top liquid pixel fraction closer to the satellite observations, especially in the warmer mixed-phase temperature range. more
Atmosphere CM-SAF Climate Data Records Validation

Sensitivity of the simulation of extreme precipitation events in China to different cumulus parameterization schemes and the underlying mechanisms

Author(s):
Zhang, SY; Wang, MH; Wang, LN; Liang, XZ; Sun, C; Li, QQ
Publication title: ATMOSPHERIC RESEARCH
2023
 | Volume: 285
2023
DOI: 10.1016/j.atmosres.2023.106636
Abstract:
The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant bias… The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant biases for the simulation of extreme precipitation. To understand the causes of these biases, we used five different cumulus parameterization schemes in the regional Climate-Weather Research and Forecasting (CWRF) model to investigate its performance and biases in the simulation of extreme precipi-tation events in China. In general, the ensemble cumulus parameterization (ECP) scheme was the most skillful in reproducing the spatial distribution of the 95th percentile daily precipitation (P95) and the other four schemes either overestimated (the Kain-Fritsch Eta and Tiedtke schemes) or underestimated (the Betts-Miller-Janjic and New Simplified Arakawa-Schubert schemes) P95. Compared with the observational data, ECP scheme signifi-cantly improved the simulation of extreme precipitation in China and had the highest correlation and the smallest root-mean-square error in most areas and seasons. To clarify the underlying physical processes of P95 simulation biases, we established a regression model of extreme precipitation based on ECP scheme. This showed that P95 in North China is mainly affected by moisture convergence, planetary boundary layer height and lifting condensation level (relative importance 18-32%). In Central China, the vertical upward motion of water vapor, sensible heat flux and planetary boundary layer height (relative importance 18-30%) are main factors associated with P95. In South China, the vertical upward motion and horizontal transport of water vapor are predominant (relative importance 26-37%). In addition, the net surface energy, surface and atmospheric radiation flux, total precipitable water, convective available potential energy and cloud water path also have a high correlation with P95 (the second most important factor; relative importance 14-31%). The influence of each factor on the simulation of P95 is different when using different cumulus parameterization schemes and the interaction among the different factors determines the ability of CWRF model to simulate extreme precipitation. These results provide important references for future model evaluations and improvements. more
Atmosphere CM-SAF Climate Data Records Validation

Seasonal dynamics of sea-ice protist and meiofauna in the northwestern Barents Sea

Author(s):
Marquardt, Miriam; Goraguer, Lucie; Assmy, Philipp; Bluhm, Bodil A.; Aaboe, Signe; Down, Emily; Patrohay, Evan; Edvardsen, Bente; Tatarek, Agnieszka; Smoła, Zofia; Wiktor, Jozef; Gradinger, Rolf
Publication title: Progress in Oceanography
2023
 | Volume: 218
2023
DOI: 10.1016/j.pocean.2023.103128
Abstract:
The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known… The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known seasonality of sea-ice protist and meiofauna community composition, abundance and biomass in the bottom 30 cm of sea ice in relation to ice properties and ice drift trajectories in the northwestern Barents Sea. We expected low abundances during the polar night and highest values during spring prior to ice melt. Sea ice conditions and Chlorophyll a concentrations varied strongly seasonally, while particulate organic carbon concentrations were fairly stable throughout the seasons. In December to May we sampled growing first-year ice, while in July and August melting older sea ice dominated. Low sea-ice biota abundances in March could be related to the late onset of ice formation and short time period for ice algae and uni- and multicellular grazers to establish themselves. Pennate diatoms, such as Navicula spp. and Nitzschia spp., dominated the bottom ice algal communities and were present during all seasons. Except for May, ciliates, dinoflagellates, particularly of the order Gymnodiales, and small-sized flagellates were co-dominant. Ice meiofauna (here including large ciliates and foraminifers) was comprised mainly of harpacticoid copepods, copepod nauplii, rotifers, large ciliates and occasionally acoels and foraminifers, with dominance of omnivore species throughout the seasons. Large ciliates comprised the most abundant meiofauna taxon at all ice stations and seasons (50–90 %) but did not necessarily dominate the biomass. While ice melt might have released and reduced ice algal biomass in July, meiofauna abundance remained high, indicating different annual cycles of protist versus meiofauna taxa. In May highest Chlorophyll a concentrations (29.4 mg m−2) and protist biomass (107 mg C m−2) occurred, while highest meiofauna abundance was found in August (23.9 × 103 Ind. m−2) and biomass in December (0.6 mg C m−2). The abundant December ice biota community further strengthens the emerging notion of an active biota during the dark Arctic winter. The data demonstrated a strong and partially unexpected seasonality in the Barents Sea ice biota, indicating that changes in ice formation, drift and decay will significantly impact the functioning of the ice-associated ecosystem. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Satellite remote sensing of regional and seasonal Arctic cooling showing a multi-decadal trend towards brighter and more liquid clouds

Author(s):
Lelli, L.; Vountas, M.; Khosravi, N.; Burrows, J.P.
Publication title: Atmospheric Chemistry and Physics
2023
 | Volume: 23 | Issue: 4
2023
DOI: 10.5194/acp-23-2579-2023
Abstract:
Two decades of measurements of spectral reflectance of solar radiation at the top of the atmosphere and a complementary record of cloud properties fro… Two decades of measurements of spectral reflectance of solar radiation at the top of the atmosphere and a complementary record of cloud properties from satellite passive remote sensing have been analyzed for their pan-Arctic, regional, and seasonal changes. The pan-Arctic loss of brightness, which is explained by the retreat of sea ice during the current warming period, is not compensated by a corresponding increase in cloud cover. A systematic change in the thermodynamic phase of clouds has taken place, shifting towards the liquid phase at the expense of the ice phase. Without significantly changing the total cloud optical thickness or the mass of condensed water in the atmosphere, liquid water content has increased, resulting in positive trends in liquid cloud optical thickness and albedo. This leads to a cooling trend by clouds being superimposed on top of the pan-Arctic amplified warming, induced by the anthropogenic release of greenhouse gases, the ice-albedo feedback, and related effects. Except over the permanent and parts of the marginal sea ice zone around the Arctic Circle, the rate of surface cooling by clouds has increased, both in spring (-32 % in total radiative forcing for the whole Arctic) and in summer (-14 %). The magnitude of this effect depends on both the underlying surface type and changes in the regional Arctic climate. Copyright: © 2023 Luca Lelli et al. more
Application Atmosphere Climate Data Records EUM-Secr

Satellite signature of the instantaneous wind response to mesoscale oceanic thermal structures

Author(s):
Meroni, Agostino N.; Desbiolles, Fabien; Pasquero, Claudia
Publication title: Quarterly Journal of the Royal Meteorological Society
2023
 | Volume: 149 | Issue: 757
2023
DOI: 10.1002/qj.4561
Abstract:
The thermal air–sea interaction mechanism that modulates the atmospheric mixing due to sea-surface temperature (SST) variability is studied with long-… The thermal air–sea interaction mechanism that modulates the atmospheric mixing due to sea-surface temperature (SST) variability is studied with long-term consistent satellite records. Statistical analyses of daily and instantaneous wind and SST data are performed over the major western boundary currents (WBCs). This wind–SST coupling, which is mediated by atmospheric mixing, is found to be very relevant on daily, and even shorter, time scales. Co-located and simultaneous SST and surface wind fields (from Advanced Very High Resolution Radiometer and Advanced Scatterometer data) reveal that the atmosphere responds instantaneously to the presence of SST structures with a larger coupling coefficient with respect to daily and monthly time-averaged fields. The coupling strength varies seasonally over WBCs in the Northern Hemisphere, with wintertime coupling being the lowest. Reanalysis data show that this behaviour is related to the seasonality of the air–sea temperature difference over the region of interest. Over the Northern Hemisphere WBCs, dry and cold continental air masses drive very unstable conditions, associated with very weak thermal air–sea coupling. more
Application Atmosphere Climate Data Records OSI-SAF Ocean

Satellite Remote Sensing of Surface Winds, Waves, and Currents: Where are we Now?

Author(s):
Hauser, D.; Abdalla, S.; Ardhuin, F.; Bidlot, J.-R.; Bourassa, M.; Cotton, D.; Gommenginger, C.; Evers-King, H.; Johnsen, H.; Knaff, J.; Lavender, S.; Mouche, A.; Reul, N.; Sampson, C.; Steele, E.C.C.; Stoffelen, A.
Publication title: Surveys in Geophysics
2023
2023
DOI: 10.1007/s10712-023-09771-2
Abstract:
This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientifi… This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields. © 2023, The Author(s). more
Atmosphere Climate Data Records NWP-SAF OSI-SAF Software for CDR development Validation

Response of the sea surface temperature to heatwaves during the France 2022 meteorological summer

Author(s):
Guinaldo, T.; Voldoire, A.; Waldman, R.; Saux Picart, S.; Roquet, H.
Publication title: Ocean Science
2023
 | Volume: 19 | Issue: 3
2023
DOI: 10.5194/os-19-629-2023
Abstract:
The summer of 2022 was memorable and record-breaking, ranking as the second hottest summer in France since 1900, with a seasonal surface air temperatu… The summer of 2022 was memorable and record-breaking, ranking as the second hottest summer in France since 1900, with a seasonal surface air temperature average of 22.7C. In particular, France experienced multiple record-breaking heatwaves during the meteorological summer. As the main heat reservoir of the Earth system, the oceans are at the forefront of events of this magnitude which enhance oceanic disturbances such as marine heatwaves (MHWs). In this study, we investigate the sea surface temperature (SST) of French maritime basins using remotely sensed measurements to track the response of surface waters to the atmospheric heatwaves and determine the intensity of such feedback. Beyond the direct relationship between SSTs and surface air temperatures, we explore the leading atmospheric parameters affecting the upper-layer ocean heat budget. Despite some gaps in data availability, the SSTs measured during the meteorological summer of 2022 were record-breaking, the mean SST was between 1.3 and 2.6 C above the long-term average (1982-2011), and the studied areas experienced between 4 and 22d where the basin-averaged SSTs exceeded the maximum recorded basin-averaged SSTs from 1982 to 2011. We found a significant SST response during heatwave periods with maximum temperatures measured locally at 30.8 C in the north-western Mediterranean Sea. Our results show that in August 2022 (31 July to 13 August), France experienced above-average surface solar radiation correlated with below-average total cloud cover and negative wind speed anomalies. Our attribution analysis based on a simplified mixed-layer heat budget highlights the critical role of ocean-atmosphere fluxes in initiating abnormally warm SSTs, while ocean mixing plays a crucial role in the cessation of such periods. We find that the 2m temperatures and specific humidity that are consistently linked to the advection of warm and moist air masses are key variables across all the studied regions. Our results reveal that the influence of wind on heatwaves is variable and of secondary importance. Moreover, we observe that the incident solar radiation has a significant effect only on the Bay of Biscay (BB) and the English Channel (EC) areas. Our study findings are consistent with previous research and demonstrate the vulnerability of the Mediterranean Sea to the increasing frequency of extreme weather events resulting from climate change. Furthermore, our investigation reveals that the recurring heatwave episodes during the summer of 2022 had an undeniable impact on all the surveyed maritime areas in France. Our study therefore provides valuable insights into the complex mechanisms underlying the ocean-atmosphere interaction and demonstrates the need for an efficient and sustainable operational system combining polar-orbiting and geostationary satellites to monitor the alterations that threaten the oceans in the context of climate change. © 2023 Thibault Guinaldo et al. more
Application Climate Data Records OSI-SAF Ocean

River runoff estimation with satellite rainfall in Morocco

Author(s):
Tramblay, Yves; El Khalki, El Mahdi; Ciabatta, Luca; Camici, Stefania; Hanich, Lahoucine; Saidi, Mohamed El Mehdi; Ezzahouani, Abdellatif; Benaabidate, Lahcen; Mahé, Gil; Brocca, Luca
Publication title: Hydrological Sciences Journal
2023
 | Volume: 68 | Issue: 3
2023
DOI: 10.1080/02626667.2023.2171295
Abstract:
In African countries, the lack of observed rainfall data is a major obstacle for efficient water resources management. The objective of this study is … In African countries, the lack of observed rainfall data is a major obstacle for efficient water resources management. The objective of this study is to evaluate satellite rainfall products’ ability to estimate river runoff over 12 basins in Morocco using four hydrological models: IHACRES, MISDc, GR4J, and CREST. Satellite products available with a short latency are compared: EUMETSAT H SAF, SM2RAIN-ASCAT, and IMERG. The best results to reproduce river runoff were obtained with SM2RAIN-ASCAT in combination with the IHACRES model, with the highest Kling-Gupta efficiency criterion and probability of detection of extreme runoff. The hydrological model performances differed across catchments and satellite rainfall products, which highlights the need to carefully select hydrological models for a given application. Thus, it is advisable to evaluate satellite rainfall products with different types of hydrological models. This first evaluation over Moroccan basins suggests that SM2RAIN-ASCAT could be a reliable alternative to observed rainfall for hydrological modelling. more
Atmosphere Climate Data Records H-SAF Validation

Resolving the 21st century temperature trends of the upper troposphere–lower stratosphere with satellite observations

Author(s):
Ladstädter, Florian; Steiner, Andrea K.; Gleisner, Hans
Publication title: Scientific Reports
2023
 | Volume: 13 | Issue: 1
2023
DOI: 10.1038/s41598-023-28222-x
Abstract:
Historically, observational information about atmospheric temperature has been limited due to a lack of suitable measurements. Recent advances in sate… Historically, observational information about atmospheric temperature has been limited due to a lack of suitable measurements. Recent advances in satellite observations provide new insight into the fine structure of the free atmosphere, with the upper troposphere and lower stratosphere comprising essential components of the climate system. This is a prerequisite for understanding the complex processes of this part of the atmosphere, which is also known to have a large impact on surface climate. With unprecedented resolution, latest climate observations reveal a dramatic warming of the atmosphere. The tropical upper troposphere has already warmed about 1 K during the first two decades of the 21st century. The tropospheric warming extends into the lower stratosphere in the tropics and southern hemisphere mid-latitudes, forming a prominent hemispheric asymmetry in the temperature trend structure. Together with seasonal trend patterns in the stratosphere, this indicates a possible change in stratospheric circulation. © 2023, The Author(s). more
Application Atmosphere Climate Data Records ROM-SAF

Relevance of warm air intrusions for Arctic satellite sea ice concentration time series

Author(s):
Rostosky, P.; Spreen, G.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 9
2023
DOI: 10.5194/tc-17-3867-2023
Abstract:
Winter warm air intrusions entering the Arctic region can strongly modify the microwave emission of the snow-covered sea ice system due to temperature… Winter warm air intrusions entering the Arctic region can strongly modify the microwave emission of the snow-covered sea ice system due to temperature-induced snow metamorphism and ice crust formations, e.g., after melt-refreeze events. Common microwave radiometer satellite sea ice concentration retrievals are based on empirical models using the snow-covered sea ice emissivity and thus can be influenced by strong warm air intrusions. Here, we carry out a long-Term study analyzing 41 years of winter sea ice concentration observations from different algorithms to investigate the impact of warm air intrusions on the retrieved ice concentration. Our results show that three out of four algorithms underestimate the sea ice concentration during (and up to 10 d after) warm air intrusions which increase the 2 m air temperature (daily maximum) above-5 C. This can lead to sea ice area underestimations in the order of 104 to 105 km2. If the 2 m temperature during the warm air intrusions crosses-2 C, all algorithms are impacted. Our analysis shows that the strength of these strong warm air intrusions increased in recent years, especially in April. With a further climate change, such warm air intrusions are expected to occur more frequently and earlier in the season, and their influence on sea ice climate data records will become more important. © 2023 Copernicus GmbH. All rights reserved. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Refining the Resolution of DUACS Along-Track Level-3 Sea Level Altimetry Products

Author(s):
Pujol, Marie-Isabelle; Dupuy, Stéphanie; Vergara, Oscar; Sánchez Román, Antonio; Faugère, Yannice; Prandi, Pierre; Dabat, Mei-Ling; Dagneaux, Quentin; Lievin, Marine; Cadier, Emeline; Dibarboure, Gérald; Picot, Nicolas
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 3
2023
DOI: 10.3390/rs15030793
Abstract:
This paper describes the demonstration of a regional high-resolution level-3 (L3) altimeter data unification and altimeter combination system (DUACS) … This paper describes the demonstration of a regional high-resolution level-3 (L3) altimeter data unification and altimeter combination system (DUACS) developed with support from the French space agency (CNES). Deduced from full-rate (20 Hz to 40 Hz) level-2 (L2) altimeter measurements, this product provides sea level anomalies (SLA) and other essential physical variables at a spatial resolution of one sample every ~1 km over the North Atlantic Ocean. This allows us to resolve wavelengths from ~35 km to ~55 km depending on the altimeter considered. This was made possible by recent advances in radar altimeter processing for both synthetic aperture radar (SAR) and low-resolution-mode (LRM) measurements, as well as improvements made to different stages of the DUACS processing chain. Firstly, the new adaptive and low-resolution with range migration correction (LR-RMC) processing techniques were considered for Jason and Sentinel-3 (S3A), respectively. They significantly reduce errors at short wavelengths, and the adaptive processing also reduces possible land contamination near the coast. Next, up-to-date geophysical and environmental corrections were selected for this production. This includes specific corrections intended to reduce the measurement noise on LRM measurements and thus enhance the observability at short wavelengths. Compared with the 1 Hz product, the observable wavelengths reached with the demonstration high-resolution product are reduced by up to one third, or up to half in the northeast Atlantic region. The residual noises were optimally filtered from full-rate measurements, taking into consideration the different observing capabilities of the altimeters processed. A specific data recovery strategy was applied, significantly optimizing the data availability, both in the coastal and open ocean areas. This demonstration L3 product is thus better resolved than the conventional 1 Hz product, especially near the coast, where it is defined up to ~5 km against ~10 km for the 1 Hz version. Multi-mission cross-calibration processing was also optimized with an improved long-wavelength error (LWE) correction, leading to a better consistency between tracks, with a 9–15% reduction in SLA variance at cross-overs. The new L3 product improves the overall consistency with tide gauge measurements, with a reduction in SLA differences variance by 5 and 17% compared with the 1 Hz product from the S3A and Jason-3 (J3) measurements, respectively. Primarily intended for regional applications, this product can significantly contribute to improving high-resolution numerical model output via data assimilation. It also opens new perspectives for a better understanding of regional sea-surface dynamics, with an improved representation of the coastal currents and a refined spectral content revealing the unbalanced signal. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Regime shift in Arctic Ocean sea ice thickness

Author(s):
Sumata, Hiroshi; de Steur, Laura; Divine, Dmitry V.; Granskog, Mats A.; Gerland, Sebastian
Publication title: Nature
2023
 | Volume: 615 | Issue: 7952
2023
DOI: 10.1038/s41586-022-05686-x
Abstract:
Manifestations of climate change are often shown as gradual changes in physical or biogeochemical properties1. Components of the climate system, howev… Manifestations of climate change are often shown as gradual changes in physical or biogeochemical properties1. Components of the climate system, however, can show stepwise shifts from one regime to another, as a nonlinear response of the system to a changing forcing2. Here we show that the Arctic sea ice regime shifted in 2007 from thicker and deformed to thinner and more uniform ice cover. Continuous sea ice monitoring in the Fram Strait over the last three decades revealed the shift. After the shift, the fraction of thick and deformed ice dropped by half and has not recovered to date. The timing of the shift was preceded by a two-step reduction in residence time of sea ice in the Arctic Basin, initiated first in 2005 and followed by 2007. We demonstrate that a simple model describing the stochastic process of dynamic sea ice thickening explains the observed ice thickness changes as a result of the reduced residence time. Our study highlights the long-lasting impact of climate change on the Arctic sea ice through reduced residence time and its connection to the coupled ocean–sea ice processes in the adjacent marginal seas and shelves of the Arctic Ocean. more
Climate Data Records Cryosphere OSI-SAF Ocean

Reducing the Uncertainty in the Satellite Altimetry Estimates of Global Mean Sea Level Trends Using Highly Stable Water Vapor Climate Data Records

Author(s):
Barnoud, A; Picard, B; Meyssignac, B; Marti, F; Ablain, M; Roca, R
Publication title: JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
2023
 | Volume: 128 | Issue: 3
2023
DOI: 10.1029/2022JC019378
Abstract:
The global mean sea level (GMSL) has risen by 3.3 & PLUSMN; 0.2 mm.yr(-1) (68% confidence level) over 1993-2021. The wet troposphere correction (WTC) … The global mean sea level (GMSL) has risen by 3.3 & PLUSMN; 0.2 mm.yr(-1) (68% confidence level) over 1993-2021. The wet troposphere correction (WTC) used to compute the altimetry-based mean sea level data is known to be a large source of error in the GMSL long-term stability. The WTC is derived from the microwave radiometers (MWR) on board the altimetry missions. In order to improve the long-term estimates of the GMSL, we propose an alternative WTC computation based on highly stable climate data records (CDRs) of water vapor derived from independent MWR measurements on board meteorological satellites. A polynomial model is applied to convert water vapor to WTC. The CDR-derived WTC enables reducing the low frequency uncertainty of the WTC applied to the altimetry data, hence reducing the uncertainty of the GMSL trend estimate. Furthermore, over 2016-2021, the comparison of MWR-based with CDR-based WTC shows a likely drift of the Jason-3 MWR WTC on the order of -0.5 mm.yr(-1) that would lead to an overestimation of the GMSL trend from 2016. more
Application Atmosphere CM-SAF Climate Data Records

Rapid fCO2 rise in the northern Barents Sea and Nansen Basin

Author(s):
Ericson, Y.; Fransson, A.; Chierici, M.; Jones, E.M.; Skjelvan, I.; Omar, A.; Olsen, A.; Becker, M.
Publication title: Progress in Oceanography
2023
 | Volume: 217
2023
DOI: 10.1016/j.pocean.2023.103079
Abstract:
Maps of surface water fugacity of CO2 (fCO2) over eastern Fram Strait, south-western Nansen Basin, and the north-western Barents Sea (73–84°N, 5–46°E)… Maps of surface water fugacity of CO2 (fCO2) over eastern Fram Strait, south-western Nansen Basin, and the north-western Barents Sea (73–84°N, 5–46°E) from September 1997 to December 2020 were made and used to investigate seasonal and temporal trends. The mapping utilized a neural network technique, the self-organizing map (SOM), that was trained with different combinations of satellite/observational/model data of sea surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), chlorophyll a (Chl a), sea ice concentration, and atmospheric mole fraction of CO2 (xCO2). The trained SOM was labelled with available surface ocean fCO2 data, and the labelled SOM was subsequently used to map the fCO2. The produced maps reveal that fCO2 in northern Barents Sea, at the border of the Nansen Basin, has increased significantly over the last decades by between 4.2 and 5.5 ± 0.6–1.1 µatm yr−1 over the winter to summer seasons. These rates are twice the rate of atmospheric CO2 increase, which was about 2 µatm yr−1. The spatial pattern coincides with the strongest decreases in sea ice concentration as well as with a salinification of the surface water. The former allows for a prolongation of the air-sea CO2 flux with resultant oceanic CO2 uptake in previously ice-covered waters, and the latter is caused by a shift from Arctic Water dominance to more saline waters containing more dissolved inorganic carbon, most likely of Atlantic Water origin although brine-release influenced deep water may also contribute. © 2023 The Authors more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Quantifying Daytime Heating Biases in Marine Air Temperature Observations from Ships

Author(s):
Cropper, TE; Berry, DI; Cornes, RC; Kent, EC
Publication title: JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY
2023
 | Volume: 40 | Issue: 4
2023
DOI: 10.1175/JTECH-D-22-0080.1
Abstract:
Marine air temperatures recorded on ships during the daytime are known to be biased warm on average due to energy storage by the superstructure of the… Marine air temperatures recorded on ships during the daytime are known to be biased warm on average due to energy storage by the superstructure of the vessels. This makes unadjusted daytime observations unsuitable for many applications including for the monitoring of long-term temperature change over the oceans. In this paper a physics -based approach is used to estimate this heating bias in ship observations from ICOADS. Under this approach, empirically determined coefficients represent the energy transfer terms of a heat budget model that quantifies the heating bias and is applied as a function of cloud cover and the relative wind speed over individual ships. The coefficients for each ship are derived from the anomalous diurnal heating relative to nighttime air temperature. Model coefficients, cloud cover, and relative wind speed are then used to estimate the heating bias ship by ship and generate nighttime-equivalent time series. A variety of methodological approaches were tested. Application of this method enables the inclusion of some daytime observations in climate records based on marine air temperatures, allowing an earlier start date and giving an increase in spatial coverage compared to existing records that exclude daytime observations.SIGNIFICANCE STATEMENT: Currently, the longest available record of air temperature over the oceans starts in 1880. We present an approach that enables observations of air temperatures over the oceans to be used in the creation of long-term climate records that are presently excluded. We do this by estimating the biases inherent in daytime tem-perature reports from ships, and adjust for these biases by implementing a numerical heat-budget model. The adjust-ment can be applied to the variety of ship types present in observational archives. The resulting adjusted temperatures can be used to create a more spatially complete record over the oceans, that extends further back in time, potentially into the late eighteenth century. more
Application Atmosphere CM-SAF Climate Data Records

Radiance Simulations in Support of Climate Services

Author(s):
Poli, P.; Roebeling, R.; John, V.O.; Doutriaux-Boucher, M.; Schulz, J.; Lattanzio, A.; Petraityte, K.; Grant, M.; Hanschmann, T.; Onderwaater, J.; Sus, O.; Huckle, R.; Coppens, D.; Theodore, B.; August, T.; Simmons, A.J.; Bell, B.; Mittaz, J.; Hall, T.; Vidot, J.; Brunel, P.; Johnson, J.E.; Zamkoff, E.B.; Al-Jazrawi, A.F.; Esfandiari, A.E.; Gerasimov, I.V.; Kobayashi, S.
Publication title: Earth and Space Science
2023
 | Volume: 10 | Issue: 10
2023
DOI: 10.1029/2023EA002868
Abstract:
Climate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates ho… Climate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates how the development and the uptake of F(C)DR benefit from radiance simulations, using reanalyses and radiative transfer models. We identify three classes of applications, with examples for each application class. The first application is to validate assumptions during F(C)DR development. Hereto we show the value of applying advanced quality controls to geostationary European (Meteosat) images. We also show the value of a cloud mask to study the spatio-temporal coherence of the impact of the Mount Pinatubo volcanic eruption between Advanced Very High Resolution Radiometer (AVHRR) and the High-resolution Infrared Radiation Sounder (HIRS) data. The second application is to assess the coherence between reanalyses and observations. Hereto we show the capability of reanalyses to reconstruct spectra observed by the Spektrometer Interferometer (SI-1) flown on a Soviet satellite in 1979. We also present a first attempt to estimate the random uncertainties from this instrument. Finally, we investigate how advanced bias correction can help to improve the coherence between reanalysis and Nimbus-3 Medium-Resolution Infrared Radiometer (MRIR) in 1969. The third application is to inform F(C)DR users about particular quality aspects. We show how simulations can help to make a better-informed use of the corresponding F(C)DR, taking as examples the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the Meteosat Second Generation (MSG) imager, and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Water Vapor Profiler (SSM/T-2). © 2023 The Authors. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. more
Application Atmosphere CM-SAF Climate Data Records EUM-Secr NWP-SAF

pvlib iotools—Open-source Python functions for seamless access to solar irradiance data

Author(s):
Jensen, Adam R.; Anderson, Kevin S.; Holmgren, William F.; Mikofski, Mark A.; Hansen, Clifford W.; Boeman, Leland J.; Loonen, Roel
Publication title: Solar Energy
2023
 | Volume: 266
2023
DOI: 10.1016/j.solener.2023.112092
Abstract:
Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radia… Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radiation models, and validating irradiance datasets. However, lack of standardization in data formats and access interfaces across providers constitutes a major barrier to entry for new users. pvlib python’s iotools subpackage aims to solve this issue by providing standardized Python functions for reading local files and retrieving data from external providers. All functions follow a uniform pattern and return convenient data outputs, allowing users to seamlessly switch between data providers and explore alternative datasets. The pvlib package is community-developed on GitHub: https://github.com/pvlib/pvlib-python. As of pvlib python version 0.9.5, the iotools subpackage supports 12 different datasets, including ground measurement, reanalysis, and satellite-derived irradiance data. The supported ground measurement networks include the Baseline Surface Radiation Network (BSRN), NREL MIDC, SRML, SOLRAD, SURFRAD, and the US Climate Reference Network (CRN). Additionally, satellite-derived and reanalysis irradiance data from the following sources are supported: PVGIS (SARAH & ERA5), NSRDB PSM3, and CAMS Radiation Service (including McClear clear-sky irradiance). more
Atmosphere CM-SAF Climate Data Records Software for CDR development

Performance assessment of SM2RAIN-NWF using ASCAT soil moisture via supervised land cover-soil-climate classification

Author(s):
Saeedi, Mohammad; Nabaei, Sina; Kim, Hyunglok; Tavakol, Ameneh; Lakshmi, Venkataraman
Publication title: Remote Sensing of Environment
2023
 | Volume: 285
2023
DOI: 10.1016/j.rse.2022.113393
Abstract:
The SM2RAIN algorithm developed a simple analytical relationship by inverting the soil-water equation to estimate rainfall through the knowledge of so… The SM2RAIN algorithm developed a simple analytical relationship by inverting the soil-water equation to estimate rainfall through the knowledge of soil moisture. The recently developed SM2RAIN-NWF algorithm offers an improvement in estimating rainfall by integrating the SM2RAIN algorithm and the net water flux (NWF) model. The Advanced Scatterometer (ASCAT) soil moisture products were used to estimate rainfall and evaluate the reliability of the SM2RAIN-NWF algorithm compared to the SM2RAIN on a national scale. Besides, the impact of Land cover-Soil texture-Climate (LSC) characteristics and the intensity of rainfall (four classes of intensity) on the performance of algorithms were discussed. Five performance metrics, including Correlation Coefficient (R), Kling–Gupta (KGE), Root Mean Square Error (RMSE), False Alarm Ration (FAR), and Probability of Detection (POD) were used to validate the estimated cumulative 5-, 14-, and 30-day rainfall. Furthermore, the effect of evapotranspiration (ET) and drainage terms were investigated in the performance of rainfall estimation through the SM2RAIN-NWF algorithm for the first time on a national scale. Results showed the rainfall estimations through the SM2RAIN-NWF algorithm improved approximately up to 7.5% in each accumulation (e.g. rainfall aggregation intervals (AGGR) 5 to 14 and 14 to 30) based on R and KGE indices. In addition, the SM2RAIN-NWF improved rainfall estimations up to 50% based on the KGE index in the southern half of Iran (arid and semi-arid climate) compared to the SM2RAIN estimates. The comprehensive evaluation and uncertainty analysis of rainfall estimations under the supervised classification of 11 LSC and 4 rainfall classes also showed the calibration of the SM2RAIN-NWF was highly affected by environmental and climatic circumstances. Uncertainty analysis showed the SM2RAIN-NWF algorithm can estimate rainfall more consistently in the five LSC classes namely 1) barren-clay loam-arid-desert, 2) barren-loam-arid-steppe, 3) barren-clay loam-arid-steppe, 4) urban-clay loam-arid-desert, and 5) urban-loam-arid-steppe. Similarly, estimating rainfall in the region with precipitation under 267 mm/year can be retrieved more reliably through the SM2RAIN-NWF algorithm. Results obtained from the ET analysis revealed an insignificant ( more
Atmosphere Climate Data Records H-SAF Validation

Optimization of weather forecasting for cloud cover over the European domain using the meteorological component of the Ensemble for Stochastic Integration of Atmospheric Simulations version 1.0

Author(s):
Lu, YS; Good, GH; Elbern, H
Publication title: GEOSCIENTIFIC MODEL DEVELOPMENT
2023
 | Volume: 16 | Issue: 3
2023
DOI: 10.5194/gmd-16-1083-2023
Abstract:
We present the largest sensitivity study to date for cloud cover using the Weather Forecasting and Research model (WRF V3.7.1) on the European domain.… We present the largest sensitivity study to date for cloud cover using the Weather Forecasting and Research model (WRF V3.7.1) on the European domain. The experiments utilize the meteorological part of a large-ensemble framework, ESIAS-met (Ensemble for Stochastic Integration of Atmospheric Simulations). This work demonstrates the capability and performance of ESIAS for large-ensemble simulations and sensitivity analysis. The study takes an iterative approach by first comparing over 1000 combinations of microphysics, cumulus parameterization, planetary boundary layer (PBL) physics, surface layer physics, radiation scheme, and land surface models on six test cases. We then perform more detailed studies on the long-term and 32-member ensemble forecasting performance of select combinations. The results are compared to CM SAF (Climate Monitoring Satellite Application Facility) satellite images from EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). The results indicate a high sensitivity of clouds to the chosen physics configuration. The combination of Goddard, WRF single moments 6 (WSM6), or CAM5.1 microphysics with MYNN3 (Mellor-Yamada Nakanishi Niino level 3) or ACM2 (Asymmetrical Convective Model version 2) PBL performed best for simulating cloud cover in Europe. For ensemble-based probabilistic simulations, the combinations of WSM6 and SBU-YLin (Stony Brook University Y. Lin) microphysics with MYNN2 and MYNN3 performed best. more
Atmosphere CM-SAF Climate Data Records Validation

On the Temperature Dependence of the Cloud Ice Particle Effective Radius-A Satellite Perspective

Author(s):
Stengel, M; Meirink, JF; Eliasson, S
Publication title: GEOPHYSICAL RESEARCH LETTERS
2023
 | Volume: 50 | Issue: 6
2023
DOI: 10.1029/2022GL102521
Abstract:
Cloud ice particle effective radius in atmospheric models is usually parametrized. A widely-used parametrization comprises a strong dependence on the … Cloud ice particle effective radius in atmospheric models is usually parametrized. A widely-used parametrization comprises a strong dependence on the temperature. Utilizing available satellite-based estimates of both cloud ice particle effective radius and cloud-top temperature we evaluate if a similar temperature-dependence exists in these observations. We find that for very low cloud-top temperatures the modeled cloud ice particle effective radius generally agrees on average with satellite observations. For high sub-zero temperatures however, the modeled cloud ice particle effective radius becomes very large, which is not seen in the satellite observations. We conclude that the investigated parametrization for the cloud ice particle effective radius, and parametrizations with a similar temperature dependence, likely produce systematic biases at the cloud top. Supporting previous studies, our findings suggest that the vertical structure of clouds should be taken into account as factor in potential future updates of the parametrizations for cloud ice particle effective radius. Plain Language Summary Atmospheric models are often used to diagnose and predict the atmospheric state including clouds. One very important property of clouds that consist of ice particles is the cloud ice particle effective radius. This ice effective radius is based on assumptions about the size and shapes of the ice particles in clouds, and thus parametrized, and is one of the important variables needed for calculating the effect of clouds on electromagnetic radiation, in particular on the solar radiation that enters the Earth's atmosphere. In our study we found that the parametrized ice effective radius agrees well on average and global scale with the ice effective radius inferred from satellite observations for cold clouds. However, we also found that for warmer ice clouds the parametrized ice effective radius is much higher than in satellite observations. Our study suggests that parametrizations of the ice effective radius used in atmospheric models show potential for improvements. more
Atmosphere CM-SAF Climate Data Records Method Validation

On the use of Infrared Atmospheric Sounding Interferometer (IASI) spectrally resolved radiances to test the EC-Earth climate model (v3.3.3) in clear-sky conditions

Author(s):
Della Fera, S; Fabiano, F; Raspollini, P; Ridolfi, M; Cortesi, U; Barbara, F; von Hardenberg, J
Publication title: GEOSCIENTIFIC MODEL DEVELOPMENT
2023
 | Volume: 16 | Issue: 4
2023
DOI: 10.5194/gmd-16-1379-2023
Abstract:
The long-term comparison between simulated and observed spectrally resolved outgoing longwave radiation (OLR) can represent a stringent test for the d… The long-term comparison between simulated and observed spectrally resolved outgoing longwave radiation (OLR) can represent a stringent test for the direct verification and improvement of general circulation models (GCMs), which are regularly tuned by adjusting parameters related to subgrid processes not explicitly represented in the model to constrain the integrated OLR energy fluxes to observed values. However, a good agreement between simulated and observed integrated OLR fluxes may be obtained from the cancellation of opposite-in-sign systematic errors localized in specific spectral ranges.Since the mid-2000s, stable hyperspectral observations of the mid-infrared region (667 to 2750 cm(-1)) of the Earth emission spectrum have been provided by different sensors (e.g. AIRS, IASI and CrIS). Furthermore, the FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) mission, selected to be the ninth ESA Earth Explorer, will measure, starting from 2027, the terrestrial radiation emitted to space at the top of the atmosphere (TOA) from 100 to 1600 cm(-1), filling the observational gap in the far-infrared (FIR) region, from 100 to 667 cm(-1).In this work, in anticipation of FORUM measurements, we compare Infrared Atmospheric Sounding Interferometer (IASI) Metop-A observations to radiances simulated on the basis of the atmospheric fields predicted by the EC-Earth Global Climate Model (version 3.3.3) in clear-sky conditions. To simulate spectra based on the atmospheric and surface state provided by the climate model, the radiative transfer model sigma-IASI has been integrated in the Cloud Feedback Model Intercomparison Project (COSP) package. Therefore, online simulations, provided by the EC-Earth model equipped with the new COSP-sigma-IASI module, have been performed in clear-sky conditions with prescribed sea surface temperature and sea ice concentration, every 6 h, over a time frame consistent with the availability of IASI data.Systematic comparisons between observed and simulated brightness temperature (BT) have been performed in 10 cm(-1) spectral intervals, on a global scale over the ocean, with a specific focus on the latitudinal belt between 30 degrees S and 30 degrees N.The analysis has shown a warm BT bias of about 3.5 K in the core of the CO2 absorption band and a cold BT bias of approximately 1 K in the wing of the CO2 band, due to a positive temperature bias in the stratosphere and a negative temperature bias in the middle troposphere of the climate model, respectively. Finally, considering a warm BT bias in the rotational-vibrational water vapour band, we have highlighted a dry bias of the water vapour concentration in the upper troposphere of the model. more
Application Atmosphere Climate Data Records EUM-Secr

Observing the evolution of summer melt on multiyear sea ice with ICESat-2 and Sentinel-2

Author(s):
Buckley, E.M.; Farrell, S.L.; Herzfeld, U.C.; Webster, M.A.; Trantow, T.; Baney, O.N.; Duncan, K.A.; Han, H.; Lawson, M.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 9
2023
DOI: 10.5194/tc-17-3695-2023
Abstract:
We investigate sea ice conditions during the 2020 melt season, when warm air temperature anomalies in spring led to early melt onset, an extended melt… We investigate sea ice conditions during the 2020 melt season, when warm air temperature anomalies in spring led to early melt onset, an extended melt season, and the second-lowest September minimum Arctic ice extent observed. We focus on the region of the most persistent ice cover and examine melt pond depth retrieved from Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) using two distinct algorithms in concert with a time series of melt pond fraction and ice concentration derived from Sentinel-2 imagery to obtain insights about the melting ice surface in three dimensions. We find the melt pond fraction derived from Sentinel-2 in the study region increased rapidly in June, with the mean melt pond fraction peaking at 16 % ± 6 % on 24 June 2020, followed by a slow decrease to 8 % ± 6 % by 3 July, and remained below 10 % for the remainder of the season through 15 September. Sea ice concentration was consistently high (>95 %) at the beginning of the melt season until 4 July, and as floes disintegrated, it decreased to a minimum of 70 % on 30 July and then became more variable, ranging from 75 % to 90 % for the remainder of the melt season. Pond depth increased steadily from a median depth of 0.40 m ± 0.17 m in early June and peaked at 0.97 m ± 0.51 m on 16 July, even as melt pond fraction had already started to decrease. Our results demonstrate that by combining high-resolution passive and active remote sensing we now have the ability to track evolving melt conditions and observe changes in the sea ice cover throughout the summer season. © Copyright: more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Observationally-constrained projections of an ice-free Arctic even under a low emission scenario

Author(s):
Kim, Yeon-Hee; Min, Seung-Ki; Gillett, Nathan P.; Notz, Dirk; Malinina, Elizaveta
Publication title: Nature Communications
2023
 | Volume: 14 | Issue: 1
2023
DOI: 10.1038/s41467-023-38511-8
Abstract:
The sixth assessment report of the IPCC assessed that the Arctic is projected to be on average practically ice-free in September near mid-century unde… The sixth assessment report of the IPCC assessed that the Arctic is projected to be on average practically ice-free in September near mid-century under intermediate and high greenhouse gas emissions scenarios, though not under low emissions scenarios, based on simulations from the latest generation Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Here we show, using an attribution analysis approach, that a dominant influence of greenhouse gas increases on Arctic sea ice area is detectable in three observational datasets in all months of the year, but is on average underestimated by CMIP6 models. By scaling models’ sea ice response to greenhouse gases to best match the observed trend in an approach validated in an imperfect model test, we project an ice-free Arctic in September under all scenarios considered. These results emphasize the profound impacts of greenhouse gas emissions on the Arctic, and demonstrate the importance of planning for and adapting to a seasonally ice-free Arctic in the near future. more
Climate Data Records Cryosphere OSI-SAF Ocean Validation

New concept of renewable energy priority zones for efficient onshore wind and solar expansion

Author(s):
Sander, Leon; Jung, Christopher; Schindler, Dirk
Publication title: Energy Conversion and Management
2023
 | Volume: 294
2023
DOI: 10.1016/j.enconman.2023.117575
Abstract:
The intensification of climate change impacts requires a fast and efficient transition of energy systems and deployment of renewable energies worldwid… The intensification of climate change impacts requires a fast and efficient transition of energy systems and deployment of renewable energies worldwide. An adequate site assessment strategy forms the basis for expanding installed capacities and energy yield. This study applies a set of meaningful criteria to determine site suitability for Germany's onshore wind and utility-scale solar photovoltaics facilities. An aggregated priority index involving meteorological-technical, economic, and environmental criteria is developed and used in a new concept for identifying renewable energy priority zones, where installations of wind and solar energy facilities should be prioritized. As a novelty, this resource-centered approach does not only analyze the mean energy potential as a meteorological criterion but also accounts for other characteristics such as variability, complementarity, and predictability. The results indicate that reducing legal restrictions substantially facilitates wind and solar energy capacity expansion in prioritized zones. With weak restrictions, up to 22% and 12% of Germany represent priority zones for an efficient and sustainable use of solar and wind energy. However, due to the intermittent nature of wind and solar resources, mismatches between generation potential and electricity demand would persist even with substantial capacity expansion. Future energy systems must advance the expansion of renewable energy capacities just as the flexibilization of demand or an increase of storage capacities to guarantee future energy security and mitigate climate change. The newly developed renewable energy priority zones are a starting point and can be transferred to other study areas by specifically adapting criteria and their weighting. more
Application Atmosphere CM-SAF Climate Data Records

Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers

Author(s):
Piontek, D.; Bugliaro, L.; Müller, R.; Muser, L.; Jerg, M.
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 5
2023
DOI: 10.3390/rs15051247
Abstract:
The newest and upcoming geostationary passive imagers have thermal infrared channels comparable to those of more established instruments, but their sp… The newest and upcoming geostationary passive imagers have thermal infrared channels comparable to those of more established instruments, but their spectral response functions still differ significantly. Therefore, retrievals developed for a certain type of radiometer cannot simply be applied to another imager. Here, a set of spectral band adjustment factors is determined for MSG/SEVIRI, Himawari-8/AHI, and MTG1/FCI from a training dataset based on MetOp/IASI hyperspectral observations. These correction functions allow to turn the observation of one sensor into an analogue observation of another sensor. This way, the same satellite retrieval—that has been usually developed for a specific instrument with a specific spectral response function—can be applied to produce long time series that go beyond one single satellite/satellite series or to cover the entire geostationary ring in a consistent way. It is shown that the mean uncorrected brightness temperature differences between corresponding channels of two imagers can be >1 K, in particular for the channels centered around 13.4 μm in the carbon dioxide absorption band and even when comparing different imager realizations of the same series, such as the four SEVIRI sensors aboard MSG1 to MSG4. The spectral band adjustment factors can remove the bias and even reduce the standard deviation in the brightness temperature difference by more than 80%, with the effect being dependent on the spectral channel and the complexity of the correction function. Further tests include the application of the spectral band adjustment factors in combination with (a) a volcanic ash cloud retrieval to Himawari-8/AHI observations of the Raikoke eruption 2019 and a comparison to an ICON-ART model simulation, and (b) an ice cloud retrieval to simulated MTG1/FCI test data with the outcome compared to the retrieval results using real MSG3/SEVIRI measurements for the same scene. © 2023 by the authors. more
Application Atmosphere NWP-SAF Software for CDR development

Monitoring of Plant Cultivation Conditions Using Ground Measurements and Satellite Products

Author(s):
Kępińska-Kasprzak, Małgorzata; Struzik, Piotr
Publication title: Water
2023
 | Volume: 15 | Issue: 3
2023
DOI: 10.3390/w15030449
Abstract:
The purpose of agrometeorological services conducted by various institutions around the world is to support decisions in the field of planning individ… The purpose of agrometeorological services conducted by various institutions around the world is to support decisions in the field of planning individual farmer works and agrotechnical treatments so as to fully enable the use of the prevailing weather and climatic conditions. However, the not always sufficient spatial distribution of ground measuring stations limits the possibility of the precise determination of meteorological conditions and the state of vegetation in a specific location. The solution may be the simultaneous use of both ground and satellite data, which can improve and enhance the final agrometeorological products. This paper presents examples of the use of meteorological products combining classical ground measurement and data from meteorological radars and satellites, applied in an agrometeorological service provided by the Institute of Meteorology and Water Management in Poland. Selected examples cover Wielkopolskie Province, which is a primarily agricultural region. An analysis of the course of the soil moisture index and HTC as well as differences in the PEI spatial distribution from ground and satellite data for the extremely dry growing season of 2018 are presented. The authors tried to demonstrate that combining data available from different sources may be a necessary condition for modern agriculture in the conditions of climate change. more
Application Climate Data Records H-SAF LSA-SAF Land

Monitoring Arctic thin ice: A comparison between CryoSat-2 SAR altimetry data and MODIS thermal-infrared imagery

Author(s):
Müller, F.L.; Paul, S.; Hendricks, S.; Dettmering, D.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 2
2023
DOI: 10.5194/tc-17-809-2023
Abstract:
Areas of thin sea ice in the polar regions not only are experiencing the highest rate of sea-ice production but also are, therefore, important hot spo… Areas of thin sea ice in the polar regions not only are experiencing the highest rate of sea-ice production but also are, therefore, important hot spots for ocean ventilation as well as heat and moisture exchange between the ocean and the atmosphere. Through co-location of (1) an unsupervised waveform classification (UWC) approach applied to CryoSat-2 radar waveforms with (2) Moderate Resolution Imaging Spectroradiometer-derived (MODIS) thin-ice-thickness estimates and (3) Sentinel-1A/B synthetic-aperture radar (SAR) reference data, thin-ice-based waveform shapes are identified, referenced, and discussed with regard to a manifold of waveform shape parameters. Here, strong linear dependencies are found between binned thin-ice thickness up to 25g cm from MODIS and the CryoSat-2 waveform shape parameters that show the possibility of either developing simple correction terms for altimeter ranges over thin ice or directing adjustments to current retracker algorithms specifically for very thin sea ice. This highlights the potential of CryoSat-2-based SAR altimetry to reliably discriminate between occurrences of thick sea ice, open-water leads, and thin ice within recently refrozen leads or areas of thin sea ice. Furthermore, a comparison to the ESA Climate Change Initiative's (CCI) CryoSat-2 surface type classification with classes sea ice, lead, and unknown reveals that the newly found thin-ice-related waveforms are divided up almost equally between unknown (46.3g %) and lead type (53.4g %) classifications. Overall, the UWC results in far fewer unknown classifications (1.4g % to 38.7g %). Thus, UWC provides more usable information for sea-ice freeboard and thickness retrieval and at the same time reduces range biases from thin-ice waveforms processed as regular sea ice in the CCI classification. © Copyright: more
Application Climate Data Records Cryosphere OSI-SAF Ocean

MIRROR: Methodological Innovation to Remodel the Electric Loads to Reduce Economic OR Environmental Impact of User

Author(s):
Chimienti, Michela; Danzi, Ivan; Impedovo, Donato; Pirlo, Giuseppe; Semeraro, Gianfranco; Veneto, Davide
Publication title: Algorithms
2023
 | Volume: 16 | Issue: 1
2023
DOI: 10.3390/a16010001
Abstract:
Demand for electricity is constantly increasing, and production is facing new constraints due to the current world situation. An alternative to standa… Demand for electricity is constantly increasing, and production is facing new constraints due to the current world situation. An alternative to standard energy production methodologies is based on the use of renewable sources; however, these methodologies do not produce energy consistently due to weather factors. This results in a significant commitment of the user who must appropriately distribute loads in the most productive time slots. In this paper, a comparison is made between two methods of predicting solar energy production, one statistical and the other meteorological. For this work, a system capable of presenting the scheduling of household appliances is tested. The system is able to predict the energy consumption of the users and the energy production of the solar system. The system is tested using data from three different users, and the mean percentage of consumption reduction is about 77.73%. This is achieved through optimized programming of appliance use that also considers user comfort. more
Application Atmosphere CM-SAF Climate Data Records Validation

Minimum detection limits of the TROPOMI satellite sensor across North America and their implications for measuring oil and gas methane emissions

Author(s):
Dubey, Luke; Cooper, Jasmin; Hawkes, Adam
Publication title: Science of The Total Environment
2023
 | Volume: 872
2023
DOI: 10.1016/j.scitotenv.2023.162222
Abstract:
Methane emissions from natural gas are of ever-increasing importance as we struggle to reach Paris climate targets. Locating and measuring emissions f… Methane emissions from natural gas are of ever-increasing importance as we struggle to reach Paris climate targets. Locating and measuring emissions from natural gas can be particularly difficult as they are often widely distributed across supply chains. Satellites are increasingly used to measure these emissions, with some such as TROPOMI giving daily coverage worldwide, making locating and quantifying these emissions easier. However, there is little understanding of the real-world detection limits of TROPOMI, which can cause emissions to go undetected or be misattributed. This paper uses TROPOMI and meteorological data to calculate, and create a map of, the minimum detection limits of the TROPOMI satellite sensor across North America for different campaign lengths. We then compared these to emission inventories to determine the quantity of emissions that can be captured by TROPOMI. We find that minimum detection limits vary from 500–8800 kg/h/pixel in a single overpass to 50–1200 kg/h/pixel for a yearlong campaign. This leads to 0.04 % of a year's emissions being captured in a single (day) measurement to 14.4 % in a 1-year measurement campaign. Assuming gas sites contain super-emitters, emissions of between 4.5 % - 10.1 % from a single measurement and 35.6 % - 41.1 % for a yearlong campaign are captured. more
Application Atmosphere CM-SAF Climate Data Records

Mapping vessel traffic patterns in the ice-covered waters of the Pacific Arctic

Author(s):
Kapsar, Kelly; Gunn, Grant; Brigham, Lawson; Liu, Jianguo
Publication title: Climatic Change
2023
 | Volume: 176 | Issue: 7
2023
DOI: 10.1007/s10584-023-03568-3
Abstract:
Recent climate change has caused declines in ice coverage which have lengthened the open water season in the Arctic and increased access to resources … Recent climate change has caused declines in ice coverage which have lengthened the open water season in the Arctic and increased access to resources and shipping routes. These changes have resulted in more vessel activity in seasonally ice-covered regions. While traffic is increasing in the ice-free season, the amount of vessel activity in the marginal ice zone (ice concentration 15–80%) or in pack ice (>80% concentration) remains unclear. Understanding patterns of vessel activities in ice is important given increased safety challenges and environmental impacts. Here, we couple high-resolution ship tracking information with sea ice thickness and concentration data to quantify vessel activity in ice-covered areas of the Pacific Arctic (northern Bering, Chukchi, and western Beaufort Seas). This region is a geo-strategically critical area that contains globally important commercial fisheries and serves as a corridor for Arctic access for wildlife and vessels. We find that vessel traffic in the marginal ice zone is widely distributed across the study area while vessel traffic in pack ice is concentrated along known shipping routes and in areas of natural resource development. Of the statistically significant relationships between vessel traffic and both sea ice concentration and thickness, over 99% are negative, indicating that increasing sea ice is associated with decreasing vessel traffic on a monthly time scale. Furthermore, there is substantial vessel traffic in areas of high concentration for bowhead whales (Balaena mysticetus), and traffic in these areas increased four-fold during the study period. Fishing vessels dominate vessel traffic at low ice concentrations, but vessels categorized as Other, likely icebreakers, are the most common vessel type in pack ice. These findings indicate that vessel traffic in areas of ice coverage is influenced by distant policy and resource development decisions which should be taken into consideration when trying to predict future vessel-ice interactions in a changing climate. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Mapping Prediction of Surface Solar Radiation with Linear Regression Models: Case Study over Reunion Island

Author(s):
Li, Qi; Bessafi, Miloud; Li, Peng
Publication title: Atmosphere
2023
 | Volume: 14 | Issue: 9
2023
DOI: 10.3390/atmos14091331
Abstract:
This paper presents a novel mapping prediction method for surface solar radiation with linear regression models. The dataset for surface solar radiati… This paper presents a novel mapping prediction method for surface solar radiation with linear regression models. The dataset for surface solar radiation prediction is the daily surface incoming shortwave radiation (SIS) product from CM SAF SARAH-E. The spatial resolution is 0.05° × 0.05° and the temporal coverage is from 2007 to 2016. The first five years (2007–2011) are used as training data, and the remaining five years (2012–2016) are used as test data in the prediction model. Datasets were detrended, de-seasonalized, and normalized before being applied to multiple linear regression (MLR), principal component regression (PCR), stepwise regression (SR), and partial least squares regression (PLSR), which are used to perform prediction mapping. The statistical analysis using MAE, MSE, and RMSE shows that the PCR model had the smallest MAE, MSE, and RMSE as compared to the other three models. The PCR model seems better for SSR mapping prediction over Reunion Island. Although the PCR model provides better prediction results, its MAE, MSE, and RMSE are quite large. more
Application Atmosphere CM-SAF Climate Data Records

Local analytical optimal nudging for assimilating AMSR2 sea ice concentration in a high-resolution pan-Arctic coupled ocean (HYCOM 2.2.98) and sea ice (CICE 5.1.2) model

Author(s):
Wang, K.; Ali, A.; Wang, C.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 10
2023
DOI: 10.5194/tc-17-4487-2023
Abstract:
Local analytical optimal nudging (LAON) is introduced and thoroughly evaluated for assimilating the Advanced Microwave Scanning Radiometer 2 (AMSR2) s… Local analytical optimal nudging (LAON) is introduced and thoroughly evaluated for assimilating the Advanced Microwave Scanning Radiometer 2 (AMSR2) sea ice concentration (SIC) in the Norwegian High-resolution pan-Arctic ocean and sea ice Prediction System (NorHAPS). NorHAPS is a developing high-resolution (3-5 km) pan-Arctic coupled ocean and sea ice modeling and prediction system based on the HYbrid Coordinate Ocean Model (HYCOM version 2.2.98) and the Los Alamos multi-category sea ice model (CICE version 5.1.2), with the LAON for data assimilation. In this study, our focus is on the LAON assimilation of AMSR2 SIC, which is designed to update the model SIC in every time step such that the analysis will eventually reach the optimal estimate. The SIC innovation (observation minus model) is designed to be proportionally distributed to the multiple sea ice categories. A hindcast experiment is performed with and without the LAON assimilation for the period 1 January 2021 to 30 April 2022, in which the extra computational cost for the LAON assimilation is about 5 % of the free run without assimilation. The results show that the LAON assimilation greatly improves the simulated sea ice concentration, extent, area, thickness, and volume, as well as the sea surface temperature (SST). It also produces significantly more accurate sea ice edge and marginal zone (MIZ) than the observed AMSR2 SIC that is assimilated when evaluated against the Norwegian Ice Service (NIS) ice chart. The results are also compared with the Copernicus Marine Environment Monitoring Service (CMEMS) operational SIC analyses from NEMO, TOPAZ4, and neXtSIM, which use ensemble Kalman filters and direct insertion for data assimilation. It is shown that the LAON assimilation produces significantly lower integrated ice edge error (IIEE) and integrated MIZ error (IME) than the CMEMS SIC analyses when evaluated against the NIS ice chart. LAON also produces a continuous and smooth evolution of sub-daily SIC, which avoids abrupt jumps often seen in other assimilated products. This efficient and accurate method is promising for data assimilation in global and high-resolution models. © 2023 Keguang Wang et al. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Linking scales of sea ice surface topography: evaluation of ICESat-2 measurements with coincident helicopter laser scanning during MOSAiC

Author(s):
Ricker, R; Fons, S; Jutila, A; Hutter, N; Duncan, K; Farrell, SL; Kurtz, NT; Hansen, RMF
Publication title: CRYOSPHERE
2023
 | Volume: 17 | Issue: 3
2023
DOI: 10.5194/tc-17-1411-2023
Abstract:
Information about sea ice surface topography and related deformation is crucial for studies of sea ice mass balance, sea ice modeling, and ship naviga… Information about sea ice surface topography and related deformation is crucial for studies of sea ice mass balance, sea ice modeling, and ship navigation through the ice pack. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), part of the National Aeronautics and Space Administration (NASA) Earth Observing System, has been on orbit for over 4 years, sensing the sea ice surface topography with six laser beams capable of capturing individual features such as pressure ridges. To assess the capabilities and uncertainties of ICESat-2 products, coincident high-resolution measurements of sea ice surface topography are required. During the yearlong Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the Arctic Ocean, we successfully carried out a coincident underflight of ICESat-2 with a helicopter-based airborne laser scanner (ALS), achieving an overlap of more than 100 km. Despite the comparably short data set, the high-resolution centimeter-scale measurements of the ALS can be used to evaluate the performance of ICESat-2 products. Our goal is to investigate how the sea ice surface roughness and topography are represented in different ICESat-2 products as well as how sensitive ICESat-2 products are to leads and small cracks in the ice cover. Here, we compare the ALS measurements with ICESat-2's primary sea ice height product, ATL07, and the high-fidelity surface elevation product developed by the University of Maryland (UMD). By applying a ridge-detection algorithm, we find that 16 % (4 %) of the number of obstacles in the ALS data set are found using the strong (weak) center beam in ATL07. Significantly higher detection rates of 42 % (30 %) are achieved when using the UMD product. While only one lead is indicated in ATL07 for the underflight, the ALS reveals many small, narrow, and only partly open cracks that appear to be overlooked by ATL07. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Intraseasonal and synoptic modulation of diurnal surface solar radiation over Reunion island in the South-West Indian Ocean

Author(s):
Tang, Chao; Mialhe, Pauline; Pohl, Benjamin; Morel, Béatrice; Wild, Martin; Koseki, Shunya; Abiodun, Babatunde; Bessafi, Miloud; Lennard, Chris; Kumar Beeharry, Girish; Lollchund, Roddy; Cunden, Tyagaraja S. M.; Singh, Swati
Publication title: Solar Energy
2023
 | Volume: 262
2023
DOI: 10.1016/j.solener.2023.111856
Abstract:
Understanding the space-time variability of Surface Solar Radiation (SSR) is mandatory for the prediction and, eventually, the skillful forecasting of… Understanding the space-time variability of Surface Solar Radiation (SSR) is mandatory for the prediction and, eventually, the skillful forecasting of photovoltaic energy production. This paper addresses the modulation of local-scale SSR over Reunion, a tropical island in the South-West Indian Ocean, by the leading modes of climate variability influencing both regional-scale and local-scale atmospheric convection and its associated cloud cover. Analyses focus on synoptic (tropical cyclones [TCs], synoptic convective regimes, including Tropical-Temperate Troughs [TTTs]) and intraseasonal (Madden-Julian Oscillation [MJO]) timescales. The SSR intra-daily variability is first assessed by a diurnal classification of SARAH-E satellite SSR data, and it is then related to the climate conditions mentioned above. SSR anomalies are found larger (smaller) on the windward (leeward) side of Reunion and in the summer (winter) season. The island-scale “cloudy” conditions can typically last 1 or 2 days. Nearby TCs can strongly reduce SSR by up to 50% on average, depending on their distances from Reunion, their sizes, and particularly, their longitudinal positions, which is observed for the first time. Nearby TCs are associated with significant negative SSR anomaly when located west of Reunion but with less significant or even positive anomaly when located east of the island. Synoptic convective regimes (the intraseasonal MJO) have a relatively weaker impact on SSR, with a value up to 13% (5%) of the mean value. Potential interactions between these SSR modulators are also investigated to understand better and eventually predict the mechanisms likely to modulate SSR (and thus photovoltaic electricity production) at sub-seasonal timescales. more
Application Atmosphere CM-SAF Climate Data Records

Intercomparing the quality of recent reanalyses for offshore wind farm planning in Germany's exclusive economic zone of the North Sea

Author(s):
Spangehl, T.; Borsche, M.; Niermann, D.; Kaspar, F.; Schimanke, S.; Brienen, S.; Möller, T.; Brast, M.
Publication title: Advances in Science and Research
2023
 | Volume: 20
2023
DOI: 10.5194/asr-20-109-2023
Abstract:
In order to facilitate offshore wind farm tenders, Deutscher Wetterdienst (DWD, Germany's national meteorological service) provides reanalysis data an… In order to facilitate offshore wind farm tenders, Deutscher Wetterdienst (DWD, Germany's national meteorological service) provides reanalysis data and quality assessments to Bundesamt für Seeschifffahrt und Hydrographie (BSH, Federal Maritime and Hydrographic Agency). The regional reanalysis COSMO-REA6 is used besides the global reanalysis ERA5. New reanalyses and derived products getting available are (i) the regional reanalysis CERRA (C3S), (ii) COSMO-R6G2, a successor of COSMO-REA6 which is currently produced by DWD and (iii) HoKliSim-De, a convection-permitting climate simulation for Germany with COSMO-CLM as a regional downscaling of ERA5. In the present study, the quality of the different data sets for offshore wind energy application is compared using in-situ measurements of the wind speed and wind direction from the top anemometer and vane of the FINO1 research platform and satellite-based data of the near-surface wind speed from the Copernicus Marine Environment Monitoring Service (CMEMS) and the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Evaluation at FINO1 focuses on the time period prior to the installation of nearby wind farms to avoid wake effects. COSMO-REA6, CERRA and HoKliSim-De show only small biases and resemble the observed distribution of the wind speed at FINO1 whereas ERA5 shows slightly lower values of the wind speed at 100gm. All model-based products tend to slightly underestimate the occurrence of south-westerly wind directions and overestimate wind directions from West to Northwest. Smallest directional biases are analysed for COSMO-REA6. Analysis of the windstorm CHRISTIAN suggests that ensemble information is required for the representation of individual extreme events. Evaluation of the near-surface wind speed using satellite-based data is performed for an area around the German Exclusive Economic Zone (EEZ) of the North Sea. The median bias of ERA5 and COSMO-REA6 is close to zero. CERRA shows a systematic overestimation of the near-surface wind speed compared to the satellite-based reference datasets. By contrast, a slight underestimation is analysed for HoKliSim-De. The bias distribution analysed for a first simulation stream of COSMO-R6G2 is similar to COSMO-REA6 which provides initial indication for the applicability of the new product. © 2023 Thomas Spangehl et al. more
Atmosphere CM-SAF Climate Data Records Ocean

Inter-comparison and validation against in-situ measurements of satellite estimates of incoming solar radiation for Central Africa: From the annual means to the diurnal cycles

Author(s):
Ouhechou, A; Philippon, N; Morel, B; Trentmann, J; Graillet, A; Mariscal, A; Nouvellon, Y
Publication title: ATMOSPHERIC RESEARCH
2023
 | Volume: 287
2023
DOI: 10.1016/j.atmosres.2023.106711
Abstract:
This study pictures for the first time incoming solar radiation mean evolution in Central Africa, intercomparing 8 gridded products (namely CERES-EBAF… This study pictures for the first time incoming solar radiation mean evolution in Central Africa, intercomparing 8 gridded products (namely CERES-EBAF, CERES-SYN1deg, TPDC, CMSAF SARAH-2, CMSAF CLARA-A2, CAMS -JADE satellite products, as well as ERA5 reanalysis and WorldClim 2 interpolated measurements) and station -based estimations (FAOCLIM 2) or measurements. At the mean annual scale, all products picture low levels of global horizontal irradiance (GHI) to the west (SW Cameroon to SW Republic of Congo) and higher levels to-wards the north and south margins of the region. However, GHI levels in the CMSAF products are much higher than in CERES and TPDC. The mean annual cycles of GHI extracted for 6 sub-regions are bimodal, with two maxima during the two rainy seasons (March-May and September-November) and two minima during the two dry seasons (December-February and June-August). These seasonal cycles are well reproduced by most products except their amplitude which is dampened in TPDC. At the daily and sub-daily time-scales, products were compared with in-situ measurements from ten meteorological stations located in the western part of Central Africa. The products' performance is assessed through scores as bias and RMSE but also by considering the diurnal cycles' shape, amplitude and frequency of occurrence along the annual cycle. The products properly reproduce the shape of the four types of diurnal cycles with nonetheless noticeable differences in the cycle's frequencies of occurrence. more
Atmosphere CM-SAF Climate Data Records Validation

Influences of Using Different Satellite Soil Moisture Products on SM2RAIN for Rainfall Estimation Across the Tibetan Plateau

Author(s):
Miao, Linguang; Wei, Zushuai; Hu, Fengmin; Duan, Zheng
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2023
 | Volume: 16
2023
DOI: 10.1109/JSTARS.2023.3296455
Abstract:
The SM2RAIN (soil moisture to rain) model has been widely used for rainfall estimation worldwide. However, due to the lack of sufficient ground observ… The SM2RAIN (soil moisture to rain) model has been widely used for rainfall estimation worldwide. However, due to the lack of sufficient ground observation, the SM2RAIN model driven by different passive microwave soil moisture products over the Tibetan Plateau has not been fully validated. In this article, four widely used satellite microwave soil moisture products (including SMAP, ASCAT, SMOS, and AMSR2) were used as input data for rainfall estimation. Rainfall data from eight ground observation stations during 2016–2018 were used to evaluate the overall performance of the SM2RAIN algorithm under various soil moisture products at different time aggregation scales. In addition, different satellite soil moisture products were merged to evaluate whether the combined soil moisture products could improve the performance of the SM2RAIN model. Finally, the rainfall estimates with different soil moisture data were further evaluated and compared with two benchmark rainfall products (IMERG and ERA5). Results indicate that: 1) Overall, SM2RAIN-SMAP has the highest rainfall estimation accuracy, but with the time aggregation scale up to 30 days, the mean R of the four rainfall estimates could reach above 0.8 and the mean value of Kling–Gupta efficiency could reach above 0.8. 2) Combined satellite soil moisture products can significantly improve the rainfall estimates. The SM2RAIN model performed the best when SMAP and ASCAT soil moisture products were combined. 3) Using the SMAP product or combined soil moisture products yielded more accurate rainfall estimates than the two benchmark rainfall products (IMERG and ERA5). more
Atmosphere Climate Data Records H-SAF Land Validation

Influence of Air Mass Advection on the Amount of Global Solar Radiation Reaching the Earth’s Surface in Poland, Based on the Analysis of Backward Trajectories (1986–2015)

Author(s):
Kulesza, Kinga
Publication title: Meteorology
2023
 | Volume: 2 | Issue: 1
2023
DOI: 10.3390/meteorology2010003
Abstract:
The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth’s surface in Poland and the dir… The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth’s surface in Poland and the direction of air mass advection, using 72-h backward trajectories (1986–2015). The study determined average daily sums of GSR related to groups of trajectories with certain similarities in shape. It was found that the average daily sums of GSR during air mass inflow from all the directions (clusters) identified were significantly different from the average daily sum in the multi-year period. A significant increase in the amount of GSR over Poland is accompanied by air mass inflow from the north and east. The frequency of these advection directions is 27% of all days. The western directions of advection prompt different GSR sums: from slightly increased during advection from the north-west, to significantly decreased during advection from the west (from the central and western part of the North Atlantic). Special attention was given to days with extremely large (above the 0.95 percentile) and with the largest (above the 0.99 percentile) GSR sums. These are prompted by two main types of synoptic conditions: the Azores High ridge covering Central and Southern Europe; and the high-pressure areas which appear in Northern and Central Europe. more
Application Atmosphere CM-SAF Climate Data Records

Impacts of Observation Forward Operator on Infrared Radiance Data Assimilation with Fine Model Resolutions

Author(s):
Zhou, L.; Lei, L.; Tan, Z.-M.; Zhang, Y.; Di, D.
Publication title: Monthly Weather Review
2023
 | Volume: 151 | Issue: 1
2023
DOI: 10.1175/MWR-D-22-0084.1
Abstract:
All-sky radiance assimilation often has non-Gaussian observation error distributions, which can be exacerbated by high model spatial resolutions due t… All-sky radiance assimilation often has non-Gaussian observation error distributions, which can be exacerbated by high model spatial resolutions due to better resolved nonlinear physical processes. For ensemble Kalman filters, observation ensemble perturbations can be approximated by the linearized observation operator (LinHx) that uses the observation operator Jacobian of ensemble mean rather than the full observation operator (FullHx). The impact of observation operator on infrared radiance data assimilation is examined here by assimilating synthetic radiance observations from channel 1025 of GIIRS with increased model spatial resolutions from 7.5 km to 300 m. A tropical cyclone is used, while the findings are expected to be generally applied. Compared to FullHx, LinHx provides larger magnitudes of correlations and stronger corrections around observation locations, especially when all-sky radiances are assimilated at fine model resolutions. For assimilating clear-sky radiances with increasing model resolutions, LinHx has smaller errors and improved vortex intensity and structure than FullHx. But when all-sky radiances are assimilated, FullHx has advantages over LinHx. Thus, for regimes with more linearity, LinHx provides stronger correlations and imposes more corrections than FullHx; but for regimes with more nonlinearity, LinHx provides detrimental non-Gaussian prior error distributions in observation space, unrealistic correlations, and overestimated corrections, compared to FullHx. © 2023 American Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

Impact of policies on residential multi-energy systems for consumers and prosumers

Author(s):
Brodnicke, Linda; Gabrielli, Paolo; Sansavini, Giovanni
Publication title: Applied Energy
2023
 | Volume: 344
2023
DOI: 10.1016/j.apenergy.2023.121276
Abstract:
Multi-energy systems can improve the performance of traditional energy systems, where energy carriers and sectors are decoupled, in terms of economic,… Multi-energy systems can improve the performance of traditional energy systems, where energy carriers and sectors are decoupled, in terms of economic, environmental, and social sustainability, measured as the total cost of energy, emissions per energy demand, and self-sufficiency, respectively. This study assesses the impact that policy mechanisms can have in enabling these sustainability benefits. A mixed-integer linear problem is implemented, which optimizes the design and operation of multi-energy systems to minimize the total annual cost of supplying energy to residential end-users. Four policy types are tested for a Swiss case study, namely a feed-in tariff, an investment support mechanism, a carbon tax, and a regulation-based carbon cap. To assess how the policy impact varies between different end-users, we distinguish between passive consumers, that cannot access subsidies, and prosumers, who can. In our case study, subsidies, such as a feed-in tariff and an investment support mechanism, decrease the cost of energy for prosumers by up to 10%, but increase the cost for consumers by up to 33%, which points to the need of including energy equity considerations when designing policies. The carbon cap and the carbon tax impact all end-users equally, and tend to perform better in terms of reducing emissions. Emission reductions of up to 60% and 39% are observed for the carbon cap and carbon tax, respectively. The feed-in tariff and carbon cap perform best in fostering self-sufficiency and achieve balanced energy autonomy for high policy levels, revealing a trade-off between the different sustainability dimensions. more
Application Atmosphere CM-SAF Climate Data Records

Impact of land surface processes on convection over West Africa in convection-permitting ensemble forecasts: A case study using the MOGREPS ensemble

Author(s):
Semeena, VS; Klein, C; Taylor, CM; Webster, S
Publication title: ATMOSPHERIC SCIENCE LETTERS
2023
 | Volume: 24 | Issue: 8
2023
DOI: 10.1002/asl.1167
Abstract:
Soil moisture (SM) affects weather through its impact on surface flux partitioning, influencing vertical atmospheric profiles and circulations driven … Soil moisture (SM) affects weather through its impact on surface flux partitioning, influencing vertical atmospheric profiles and circulations driven by differential surface heating. In West Africa, observational studies point to a dominant negative SM-precipitation feedback, where dry soils help to initiate and maintain convection. In this context, serious concerns exist about the ability of models with parameterised convection to simulate this observed sensitivity of daytime convection to SM. Here, we evaluate the effect of initial SM perturbations in a short-range ensemble forecast over West Africa, comparing the UK Met Office Global and Regional Ensemble Prediction System (MOGREPS) with parameterised convection (GLOB-ENS) to its regional convection-permitting counterpart (CP-ENS). Results from both models suggest SM perturbations introduce considerable spread into daytime evaporative fraction (EF) and near-surface temperatures. This spread is still evident on Day 3 of the forecast. Both models also show a tendency to increased afternoon rainfall frequency over negative EF anomalies, reproducing the observed feedback. However, this effect is more pronounced in CP-ENS than GLOB-ENS, which illustrates the potential for process-based forecast improvements at convection-permitting scales. Finally, we identify persistent biases in rainfall caused by land cover mapping issues in the operational GLOB-ENS setup, emphasising the need for careful evaluation of different mapping strategies for land cover. more
Application Climate Data Records LSA-SAF Land

How adequately are elevated moist layers represented in reanalysis and satellite observations?

Author(s):
Prange, Marc; Buehler, Stefan A.; Brath, Manfred
Publication title: Atmospheric Chemistry and Physics
2023
 | Volume: 23 | Issue: 1
2023
DOI: 10.5194/acp-23-725-2023
Abstract:
We assess the representation of elevated moist layers (EMLs) in ERA5 reanalysis, the Infrared Atmospheric Sounding Interferometer (IASI) L2 retrieval … We assess the representation of elevated moist layers (EMLs) in ERA5 reanalysis, the Infrared Atmospheric Sounding Interferometer (IASI) L2 retrieval Climate Data Record (CDR) and the Atmospheric Infrared Sounder (AIRS)-based Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)-Aqua L2 retrieval. EMLs are free-tropospheric moisture anomalies that typically occur in the vicinity of deep convection in the tropics. EMLs significantly affect the spatial structure of radiative heating, which is considered a key driver for meso-scale dynamics, in particular convective aggregation. To our knowledge, the representation of EMLs in the mentioned data products has not been explicitly studied - a gap we start to address in this work. We assess the different datasets' capability of capturing EMLs by collocating them with 2146 radiosondes launched from Manus Island within the western Pacific warm pool, a region where EMLs occur particularly often. We identify and characterise moisture anomalies in the collocated datasets in terms of moisture anomaly strength, vertical thickness and altitude. By comparing the distributions of these characteristics, we deduce what specific EML characteristics the datasets are capturing well and what they are missing. Distributions of ERA5 moisture anomaly characteristics match those of the radiosonde dataset quite well, and remaining biases can be removed by applying a 1km moving average to the radiosonde profiles. We conclude that ERA5 is a suitable reference dataset for investigating EMLs. We find that the IASI L2 CDR is subject to stronger smoothing than ERA5, with moisture anomalies being on average 13% weaker and 28% thicker than collocated ERA5 anomalies. The CLIMCAPS L2 product shows significant biases in its mean vertical humidity structure compared to the other investigated datasets. These biases manifest as an underestimation of mean moist layer height of about 1.3km compared to the three other datasets that yields a general mid-tropospheric moist bias and an upper-tropospheric dry bias. Aside from these biases, the CLIMCAPS L2 product shows a similar, if not better, capability of capturing EMLs compared to the IASI L2 CDR. More nuanced evaluations of CLIMCAPS' capabilities may be possible once the underlying cause for the identified biases has been found and fixed. Biases found in the all-sky scenes do not change significantly when limiting the analysis to clear-sky scenes. We calculate radiatively driven vertical velocities ωrad derived from longwave heating rates to estimate the dynamical effect of the moist layers. Moist-layer-associated ωrad values derived from Global Climate Observing System Reference Upper-Air Network (GRUAN) soundings range between 2 and 3hPah-1, while mean meso-scale pressure velocities from the EUREC4A (Elucidating the Role of Clouds-Circulation Coupling in Climate) field campaign range between 1 and 2hPah-1, highlighting the dynamical significance of EMLs. Subtle differences in the representation of moisture and temperature structures in ERA5 and the satellite datasets create large relative errors in ωrad on the order of 40% to 80% with reference to GRUAN, indicating limited usefulness of these datasets to assess the dynamical impact of EMLs. © 2023 Marc Prange et al. more
Atmosphere Climate Data Records EUM-Secr Validation

Hourly global horizontal irradiance over West Africa: A case study of one-year satellite- and reanalysis-derived estimates vs. in situ measurements

Author(s):
Sawadogo, Windmanagda; Bliefernicht, Jan; Fersch, Benjamin; Salack, Seyni; Guug, Samuel; Diallo, Belko; Ogunjobi, Kehinde. O.; Nakoulma, Guillaume; Tanu, Michael; Meilinger, Stefanie; Kunstmann, Harald
Publication title: Renewable Energy
2023
 | Volume: 216
2023
DOI: 10.1016/j.renene.2023.119066
Abstract:
Estimates of global horizontal irradiance (GHI) from reanalysis and satellite-based data are the most important information for the design and monitor… Estimates of global horizontal irradiance (GHI) from reanalysis and satellite-based data are the most important information for the design and monitoring of PV systems in Africa, but their quality is unknown due to the lack of in situ measurements. In this study, we evaluate the performance of hourly GHI from state-of-the-art reanalysis and satellite-based products (ERA5, MERRA-2, CAMS, and SARAH-2) with 37 quality-controlled in situ measurements from novel meteorological networks established in Burkina Faso and Ghana under different weather conditions for the year 2020. The effects of clouds and aerosols are also considered in the analysis by using common performance measures for the main quality attributes and a new overall performance value for the joint assessment. The results show that satellite data performs better than reanalysis data under different atmospheric conditions. Nevertheless, both data sources exhibit significant bias of more than 150 W/m2 in terms of RMSE under cloudy skies compared to clear skies. The new measure of overall performance clearly shows that the hourly GHI derived from CAMS and SARAH-2 could serve as viable alternative data for assessing solar energy in the different climatic zones of West Africa. more
Atmosphere CM-SAF Climate Data Records Validation

GNSS radio occultation excess-phase processing for climate applications including uncertainty estimation

Author(s):
Innerkofler, J.; Kirchengast, G.; Schwärz, M.; Marquardt, C.; Andres, Y.
Publication title: Atmospheric Measurement Techniques
2023
 | Volume: 16 | Issue: 21
2023
DOI: 10.5194/amt-16-5217-2023
Abstract:
Earth observation from space provides a highly valuable basis for atmospheric and climate science, in particular also through climate benchmark data f… Earth observation from space provides a highly valuable basis for atmospheric and climate science, in particular also through climate benchmark data from suitable remote sensing techniques. Measurements by global navigation satellite system (GNSS) radio occultation (RO) qualify to produce such benchmark data records as they globally provide accurate and long-Term stable datasets for essential climate variables (ECVs) such as temperature. This requires a rigorous processing of the raw RO measurements to ECVs, with narrow uncertainties. In order to fully exploit this potential, Wegener Center's Reference Occultation Processing System (rOPS) Level 1a (L1a) processing subsystem includes uncertainty estimation in both precise orbit determination (POD) and excess-phase profile derivation. Here we introduce the new rOPS L1a excess-phase processing, the first step in the RO profiles retrieval down to atmospheric profiles, which extracts the atmospheric excess phase from raw SI-Traceable RO measurements. This excess-phase processing, for itself algorithmically concise, includes integrated quality control and uncertainty estimation, requiring a complex framework of various subsystems that we first introduce before describing the implementation of the core algorithms. The quality control and uncertainty estimation, computed per RO event, are supported by reliable forward-modeled excess-phase profiles based on the POD orbit arcs and collocated short-range forecast profiles of the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5). The quality control removes or alternatively flags excess-phase profiles of insufficient or degraded quality. The uncertainty estimation accounts both for relevant random-and systematic-uncertainty components, and the resulting (total) uncertainty profiles serve as a starting point for the subsequent uncertainty propagation through the retrieval processing chain down to the atmospheric ECV profiles. We also evaluated the quality and reliability of the resulting excess-phase profiles based on Metop-A/B/C (Meteorological Operational) RO datasets for three 3-month periods in 2008, 2013, and 2020 by way of a sensitivity analysis for three representative atmospheric layers (tropo-, strato-, mesosphere), investigating consistency with ERA5-derived profiles, influences of different orbit and clock inputs, and consistency across the different Metop satellites. These consistencies range from centimeter to submillimeter levels, indicating that the new processing can provide highly accurate and robust excess-phase profiles. Furthermore, cross-evaluation and intercomparison with excess-phase data from the established data providers EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) and UCAR (University Corporation for Atmospheric Research) revealed subtle discrepancies but overall very close agreement, with larger differences compared to UCAR in the boundary layer. The new rOPS L1a processing can hence be considered capable of producing reliable long-Term data records including uncertainty estimation for the benefit of climate applications. © Copyright: more
Atmosphere Climate Data Records EUM-Secr Validation

Global Mapping of Microwave Emissivity and Emitting Depth in Arid Areas Using GMI Observations

Author(s):
Favrichon, S.; Prigent, C.; Jimenez, C.; Vogt, R.
Publication title: Earth and Space Science
2023
 | Volume: 10 | Issue: 11
2023
DOI: 10.1029/2022EA002756
Abstract:
Over arid areas, observations of brightness temperatures by passive microwave radiometers are affected by the variation of the emitting depth with wav… Over arid areas, observations of brightness temperatures by passive microwave radiometers are affected by the variation of the emitting depth with wavelengths. When this variation is unaccounted for, it limits the assimilation of passive microwaves over deserts in Numerical Weather Prediction models and it causes large errors in passive microwave retrievals of land surface temperatures. The emitting depths, along with the corresponding emissivities, are estimated from 10 to 89 GHz, using the non-Sun-synchronous observations of the Global Precipitation Mission Microwave Imager to reconstruct the monthly diurnal cycle of brightness temperature. The soil temperature profile is modeled using a two-term Fourier decomposition based on the ERA5 surface temperature. The combination of the observation and the modeled temperature allows for an estimation of the microwave effective emitting depth. The emitting depth is estimated to be up to 25 cm at 36 GHz, resulting in large differences between the surface temperature and the effective emitting temperature. The variation of emitting depth with frequency is parameterized, and a companion data set provides the necessary parameters to calculate the emitting depth for arid areas between 10 and 89 GHz, globally. The benefit of this parameterization is quantified, with an application to the modeling of observations from the Special Sensor Microwave Imager Sounder over arid areas. © 2023 The Authors. more
Application CM-SAF Climate Data Records Land

Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns

Author(s):
Chan, K.L.; Valks, P.; Heue, K.-P.; Lutz, R.; Hedelt, P.; Loyola, D.; Pinardi, G.; Van Roozendael, M.; Hendrick, F.; Wagner, T.; Kumar, V.; Bais, A.; Piters, A.; Irie, H.; Takashima, H.; Kanaya, Y.; Choi, Y.; Park, K.; Chong, J.; Cede, A.; Frieß, U.; Richter, A.; Ma, J.; Benavent, N.; Holla, R.; Postylyakov, O.; Rivera Cárdenas, C.; Wenig, M.
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 4
2023
DOI: 10.5194/essd-15-1831-2023
Abstract:
We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheri… We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products 10.15770/EUM-SAF-AC-0048, ; monthly products 10.15770/EUM-SAF-AC-0049, ). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public. © Copyright: more
AC-SAF Atmosphere Climate Data Records Validation

Global Cloudiness and Cloud Top Information from AVHRR in the 42-Year CLARA-A3 Climate Data Record Covering the Period 1979–2020

Author(s):
Karlsson, Karl-Göran; Devasthale, Abhay; Eliasson, Salomon
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 12
2023
DOI: 10.3390/rs15123044
Abstract:
This paper investigates the quality of global cloud fraction and cloud-top height products provided by the third edition of the CM SAF cLoud, Albedo a… This paper investigates the quality of global cloud fraction and cloud-top height products provided by the third edition of the CM SAF cLoud, Albedo and surface RAdiation dataset from the AVHRR data (CLARA-A3) climate data record (CDR) produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). Compared with with CALIPSO–CALIOP cloud lidar data and six other cloud CDRs, including the predecessor CLARA-A2, CLARA-A3 has improved cloud detection, especially over ocean surfaces, and improved geographical variation and cloud detection efficiency. In addition, CLARA-A3 exhibits remarkable improvements in the accuracy of its global cloud-top height measurements. For example, in tropical regions, previous underestimations for high-level clouds are reduced by more than 2 km. By taking advantage of more realistic descriptions of global cloudiness, this study attempted to estimate trends in the observable fraction of low-level clouds, acknowledging their importance in producing a net climate cooling effect. The results were generally inconclusive in the tropics, mainly due to the interference of El Nino modes during the period under study. However, the analysis found small negative trends over oceanic surfaces outside the core tropical region. Further studies are needed to verify the significance of these results. more
Atmosphere CM-SAF Climate Data Records Validation

Generation of Typical Meteorological Sequences to Simulate Growth and Production of Biological Systems

Author(s):
Wane, Ousmane; Zarzalejo, Luis F.; Ferrera-Cobos, Francisco; Navarro, Ana A.; Rodríguez-López, Alberto; Valenzuela, Rita X.
Publication title: Applied Sciences
2023
 | Volume: 13 | Issue: 8
2023
DOI: 10.3390/app13084826
Abstract:
Numerical simulation applied to agriculture or wastewater treatment (WWT) is a complementary tool to understand, a priori, the impact of meteorologica… Numerical simulation applied to agriculture or wastewater treatment (WWT) is a complementary tool to understand, a priori, the impact of meteorological parameters on productivity under limiting environmental conditions or even to guide investments towards other more relevant circular economic objectives. This work proposes a new methodology to calculate Typical Meteorological Sequences (TMS) that could be used as input data to simulate the growth and productivity of photosynthetic organisms in different biological systems, such as a High-Rate Algae Pond (HRAP) for WWT or in agriculture for crops. The TMS was established by applying Finkelstein-Schafer statistics and represents the most likely meteorological sequence in the long term for each meteorological season. In our case study, 18 locations in the Madrid (Spain) region are estimated depending on climate conditions represented by solar irradiance and temperature. The parameters selected for generating TMS were photosynthetically active radiation, solar day length, maximum, minimum, mean, and temperature range. The selection of potential sequences according to the growth period of the organism is performed by resampling the available meteorological data, which, in this case study, increases the number of candidate sequences by 700%. more
Application Atmosphere CM-SAF Climate Data Records

Forced and internal components of observed Arctic sea-ice changes

Author(s):
Dörr, J.S.; Bonan, D.B.; Årthun, M.; Svendsen, L.; Wills, R.C.J.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 9
2023
DOI: 10.5194/tc-17-4133-2023
Abstract:
The Arctic sea-ice cover is strongly influenced by internal variability on decadal timescales, affecting both short-term trends and the timing of the … The Arctic sea-ice cover is strongly influenced by internal variability on decadal timescales, affecting both short-term trends and the timing of the first ice-free summer. Several mechanisms of variability have been proposed, but how these mechanisms manifest both spatially and temporally remains unclear. The relative contribution of internal variability to observed Arctic sea-ice changes also remains poorly quantified. Here, we use a novel technique called low-frequency component analysis to identify the dominant patterns of winter and summer decadal Arctic sea-ice variability in the satellite record. The identified patterns account for most of the observed regional sea-ice variability and trends, and they thus help to disentangle the role of forced and internal sea-ice changes over the satellite record. In particular, we identify a mode of decadal ocean-atmosphere-sea-ice variability, characterized by an anomalous atmospheric circulation over the central Arctic, that accounts for approximately 30 % of the accelerated decline in pan-Arctic summer sea-ice area between 2000 and 2012 but accounts for at most 10 % of the decline since 1979. For winter sea ice, we find that internal variability has dominated decadal trends in the Bering Sea but has contributed less to trends in the Barents and Kara seas. These results, which detail the first purely observation-based estimate of the contribution of internal variability to Arctic sea-ice trends, suggest a lower estimate of the contribution from internal variability than most model-based assessments. © Copyright: more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Filter Likelihood as an Observation-Based Verification Metric in Ensemble Forecasting

Author(s):
Ekblom, M.; Tuppi, L.; Räty, O.; Ollinaho, P.; Laine, M.; Järvinen, H.
Publication title: Tellus, Series A: Dynamic Meteorology and Oceanography
2023
 | Volume: 75 | Issue: 1
2023
DOI: 10.16993/tellusa.96
Abstract:
In numerical weather prediction (NWP), ensemble forecasting aims to quantify the flow-dependent forecast uncertainty. The focus here is on observation… In numerical weather prediction (NWP), ensemble forecasting aims to quantify the flow-dependent forecast uncertainty. The focus here is on observation-based verification of the reliability of ensemble forecasting systems. In particular, at short forecast lead times, forecast errors tend to be relatively small compared to observation errors and hence it is very important that the verification metric also accounts for observational uncertainties. This paper studies the so-called filter likelihood score which is deep-rooted in Bayesian estimation theory and fits naturally to the filtering setup of NWP. The filter likelihood score considers observation errors, ensemble mean skill, and ensemble spread in one metric. Importantly, it can be made multivariate and effortlessly expanded to simultaneous verification against all observation types through the observation operators contained in the parental data assimilation scheme. Here observations from the global radiosonde network and satellites (AMSU-A channel 5) are included in the verification of OpenIFS-based ensemble forecasts using different types of initial state perturbations. Our results show that the filter likelihood score is sensitive to the ensemble prediction system quality and compares consistently with other verification metrics such as the relationships between ensemble spread and ensemble mean forecast error, and Dawid-Sebastiani score. Our conclusion is that the filter likelihood score provides a very well-behaving verification metric, that can be made truly multivariate by including covariances, for ensemble prediction systems with a strong foundation in estimation theory. © 2023, Stockholm University Press. All rights reserved. more
Application Atmosphere NWP-SAF Software for CDR development

Features of the optical properties of the upper layer of Lake Teletskoye according to the OLCI Level-2 data

Author(s):
Suslin, V.V.; Sutorikhin, I.A.; Latushkin, A.A.; Kudinov, O.B.; Korchemkina, E.N.; Dontsov, A.A.; Martynov, O.V.
2023
 | Volume: 12780
2023
DOI: 10.1117/12.2685989
Abstract:
This work precedes the field experiment on Lake Teletskoye, which is scheduled for August 10-20, 2023. The main goal of the work is to get an informat… This work precedes the field experiment on Lake Teletskoye, which is scheduled for August 10-20, 2023. The main goal of the work is to get an information of the regional features and seasonal variability of the optically active characteristics of the water upper layer of Lake Teletskoye based on the Level-2 standard products of the OLCI optical scanner. © 2023 SPIE. more
Application Climate Data Records EUM-Secr Ocean

Explicitly determined sea ice emissivity and emission temperature over the Arctic for surface-sensitive microwave channels

Author(s):
Kang, E.-J.; Sohn, B.-J.; Tonboe, R.T.; Noh, Y.-C.; Kwon, I.-H.; Kim, S.-W.; Maturilli, M.; Kim, H.-C.; Liu, C.
Publication title: Quarterly Journal of the Royal Meteorological Society
2023
 | Volume: 149 | Issue: 754
2023
DOI: 10.1002/qj.4492
Abstract:
Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, t… Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, the use of surface-sensitive microwave-sounding channel measurements for data assimilation or retrieval has been limited, especially during winter, due to the poorly constrained sea ice emissivity. In this study, aiming at more use of those channel measurements in the data assimilation, we propose an explicit method for specifying the surface radiative boundary conditions (namely emissivity and emitting layer temperature of snow and ice). These were explicitly determined with a radiative transfer model for snow and ice and with snow/ice physical parameters (i.e. snow/ice depths and vertical distributions of temperature, density, salinity, and grain size) simulated from the thermodynamically driven snow/ice growth model. We conducted 1D-Var experiments in order to examine whether this approach can help to use the surface-sensitive microwave temperature channel measurements over the Arctic sea ice region for data assimilation. Results show that (1) the surface-sensitive microwave channels can be used in the 1D-Var retrieval, and (2) the specification of the radiative boundary condition at the surface using the snow/sea ice emission model can significantly improve the atmospheric temperature retrieval, especially in the lower troposphere (500 hPa to surface). The successful retrieval suggests that useful information can be extracted from surface-sensitive microwave-sounding channel radiances over sea ice surfaces through the explicit determination of snow/ice emissivity and emitting layer temperature. © 2023 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

Evaluation of tropospheric water vapour and temperature profiles retrieved from MetOp-A by the Infrared and Microwave Sounding scheme

Author(s):
Trent, T; Siddans, R; Kerridge, B; Schröer, M; Scott, NA; Remedios, J
Publication title: ATMOSPHERIC MEASUREMENT TECHNIQUES
2023
 | Volume: 16 | Issue: 6
2023
DOI: 10.5194/amt-16-1503-2023
Abstract:
Since 2007, the Meteorological Operational satellite (MetOp) series of platforms operated by the European Organisation for the Exploitation of Meteoro… Since 2007, the Meteorological Operational satellite (MetOp) series of platforms operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) has provided valuable observations of the Earth's surface and atmosphere for meteorological and climate applications. With 15 years of data already collected, the next generation of MetOp satellites will see this measurement record extend to and beyond 2045. Although a primary role is in operational meteorology, tropospheric temperature and water vapour profiles will be key data products produced using infrared and microwave sounding instruments on board. Considering the MetOp data record that will span 40 years, these profiles will form an essential climate data record (CDR) for studying long-term atmospheric changes. Therefore, the performance of these products must be characterized to support the robustness of any current or future analysis. In this study, we validate 9.5 years of profile data produced using the Infrared and Microwave Sounding (IMS) scheme with the European Space Agency (ESA) Water Vapour Climate Change Initiative (WV_cci) project against radiosondes from two different archives. The Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and Analyzed RadioSoundings Archive (ARSA) data records were chosen for the validation exercise to provide the contrast between global observations (ARSA) with sparser characterized climate measurements (GRUAN). Results from this study show that IMS temperature and water vapour profile biases are within 0.5 K and 10 % of the reference for "global" scales. We further demonstrate the difference between diurnal sampling and cloud amount match-ups on observed biases and discuss the implications that sampling also plays on attributing these effects. Finally, we present the first look at the profile bias stability from the IMS product, where we observe global stabilities ranging from -0.32 +/- 0.18 to 0.1 +/- 0.27 K per decade and -1.76 +/- 0.19 to 0.79 +/- 0.83 % ppmv (parts per million by volume) per decade for temperature and water vapour profiles, respectively. We further break down the profile stability into diurnal and latitudinal values and relate all observed results to required climate performance. Overall, we find the results from this study demonstrate the real potential for tropospheric water vapour and temperature profile CDRs from the MetOp series of platforms. more
Atmosphere Climate Data Records EUM-Secr Validation

Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)

Author(s):
Iovino, D.; Fogli, P.G.; Masina, S.
Publication title: Geoscientific Model Development
2023
 | Volume: 16 | Issue: 21
2023
DOI: 10.5194/gmd-16-6127-2023
Abstract:
This paper describes the global eddying ocean-sea ice simulation produced at the Euro-Mediterranean Center on Climate Change (CMCC) obtained following… This paper describes the global eddying ocean-sea ice simulation produced at the Euro-Mediterranean Center on Climate Change (CMCC) obtained following the experimental design of the Ocean Model Intercomparison Project phase 2 (OMIP2). The eddy-rich model (GLOB16) is based on the NEMOv3.6 framework, with a global horizontal resolution of 1/16 and 98 vertical levels and was originally designed for an operational short-term ocean forecasting system. Here, it is driven by one multi-decadal cycle of the prescribed JRA55-do atmospheric reanalysis and runoff dataset in order to perform a long-term benchmarking experiment. To assess the accuracy of simulated 3D ocean fields and highlight the relative benefits of resolving mesoscale processes, the GLOB16 performances are evaluated via a selection of key climate metrics against observational datasets and two other NEMO configurations at lower resolutions: an eddy-permitting resolution (ORCA025) and a non-eddying resolution (ORCA1) designed to form the ocean-sea ice component of the fully coupled CMCC climate model. The well-known biases in the low-resolution simulations are significantly improved in the high-resolution model. The evolution and spatial pattern of large-scale features (such as sea surface temperature biases and winter mixed-layer structure) in GLOB16 are generally better reproduced, and the large-scale circulation is remarkably improved compared to the low-resolution oceans. We find that eddying resolution is an advantage in resolving the structure of western boundary currents, the overturning cells, and flow through key passages. GLOB16 might be an appropriate tool for ocean climate modeling efforts, even though the benefit of eddying resolution does not provide unambiguous advances for all ocean variables in all regions. © 2023 Doroteaciro Iovino et al. more
Climate Data Records Cryosphere OSI-SAF Ocean Validation

Evaluation of the convection-permitting regional climate model CNRM-AROME41t1 over Northwestern Europe

Author(s):
Lucas-Picher, Philippe; Brisson, E.; Caillaud, C.; Alias, A.; Nabat, P.; Lemonsu, A.; Poncet, N.; Cortés Hernandez, V. E.; Michau, Y.; Doury, A.; Monteiro, D.; Somot, S.
Publication title: Climate Dynamics
2023
2023
DOI: 10.1007/s00382-022-06637-y
Abstract:
Since a decade, convection-permitting regional climate models (CPRCM) have emerged showing promising results, especially in improving the simulation o… Since a decade, convection-permitting regional climate models (CPRCM) have emerged showing promising results, especially in improving the simulation of precipitation extremes. In this article, the CPRCM CNRM-AROME developed at the Centre National de Recherches Météorologiques (CNRM) since a few years is described and evaluated using a 2.5-km 19-year long hindcast simulation over a large northwestern European domain using different observations through an added-value analysis in which a comparison with its driving 12-km RCM CNRM-ALADIN is performed. The evaluation is challenging due to the lack of high-quality observations at both high temporal and spatial resolutions. Thus, a high spatio-temporal observed gridded precipitation dataset was built from the collection of seven national datasets that helped the identification of added value in CNRM-AROME. The evaluation is based on a series of standard climatic features that include long-term means and mean annual cycles of precipitation and near-surface temperature where CNRM-AROME shows little improvements compared to CNRM-ALADIN. Additional indicators such as the summer diurnal cycle and indices of extreme precipitation show, on the contrary, a more realistic behaviour of the CNRM-AROME model. Moreover, the analysis of snow cover shows a clear added-value in the CNRM-AROME simulation, principally due to the improved description of the orography with the CPRCM high resolution. Additional analyses include the evaluation of incoming shortwave radiation, and cloud cover using satellite estimates. Overall, despite some systematic biases, the evaluation indicates that CNRM-AROME is a suitable CPRCM that is superior in many aspects to the RCM CNRM-ALADIN. more
Atmosphere CM-SAF Climate Data Records Validation

Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982-2018

Author(s):
Kouki, K.; Luojus, K.; Riihelä, A.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 12
2023
DOI: 10.5194/tc-17-5007-2023
Abstract:
Seasonal snow cover of the Northern Hemisphere (NH) greatly influences surface energy balance; hydrological cycle; and many human activities, such as … Seasonal snow cover of the Northern Hemisphere (NH) greatly influences surface energy balance; hydrological cycle; and many human activities, such as tourism and agriculture. Monitoring snow cover at a continental scale is only possible from satellites or using reanalysis data. This study aims to analyze the time series of snow water equivalent (SWE), snow cover extent (SCE), and surface albedo in spring in ERA5 and ERA5-Land reanalysis data and to compare the time series with several satellite-based datasets. As reference data for the SWE intercomparison, we use bias-corrected SnowCCI v1 data for non-mountainous regions and the mean of Brown, MERRA-2, and Crocus v7 datasets for the mountainous regions. For surface albedo, we use the black-sky albedo datasets CLARA-A2 SAL, based on AVHRR data, and MCD43D51, based on MODIS data. Additionally, we use Rutgers and JAXA JASMES SCE products. Our study covers land areas north of 40N and the period between 1982 and 2018 (spring season from March to May). The analysis shows that both ERA5 and ERA5-Land overestimate total NH SWE by 150% to 200% compared to the SWE reference data. ERA5-Land shows larger overestimation, which is mostly due to very high SWE values over mountainous regions. The analysis revealed a discontinuity in ERA5 around the year 2004 since adding the Interactive Multisensor Snow and Ice Mapping System (IMS) from the year 2004 onwards considerably improves SWE estimates but makes the trends less reliable. The negative NH SWE trends in ERA5 range from-249 to-236Gt per decade in spring, which is 2 to 3 times larger than the trends detected by the other datasets (ranging from-124 to-77Gt per decade). SCE is accurately described in ERA5-Land, whereas ERA5 shows notably larger SCE than the satellite-based datasets. Albedo estimates are more consistent between the datasets, with a slight overestimation in ERA5 and ERA5-Land. The negative trends in SCE and albedo are strongest in May, when the albedo trend varies from-0.011 to-0.006 per decade depending on the dataset. The negative SCE trend detected by ERA5 in May (-1.22×106km2 per decade) is about twice as large as the trends detected by all other datasets (ranging from-0.66 to-0.50×106km2 per decade). The analysis also shows that there is a large spatial variability in the trends, which is consistent with other studies. © 2023 Kerttu Kouki et al. more
CM-SAF Climate Data Records Land Validation

Evaluation of PERSIANN-CCS-CDR, ERA5, and SM2RAIN-ASCAT rainfall products for rainfall and drought assessment in a semi-arid watershed, Morocco

Author(s):
Najmi, Adam; Igmoullan, Brahim; Namous, Mustapha; El Bouazzaoui, Imane; Brahim, Yassine Ait; El Khalki, El Mahdi; Saidi, Mohamed El Mehdi
Publication title: Journal of Water and Climate Change
2023
 | Volume: 14 | Issue: 5
2023
DOI: 10.2166/wcc.2023.461
Abstract:
Satellite-based precipitation products, with simultaneously high spatial and temporal resolutions, are mostly needed to assess climate change repercus… Satellite-based precipitation products, with simultaneously high spatial and temporal resolutions, are mostly needed to assess climate change repercussions. Previous research used datasets neglecting either good temporal or good spatial resolution, PERSIANN-CCSCDR, ERA5, and SM2RAIN-ASCAT are some of the projects aiming to remedy these limitations. This study's goal is to evaluate the accuracy of the PERSIANN-CCS-CDR, ERA5, and SM2RAIN-ASCAT at a monthly scale and their suitability for drought assessment in a Moroccan semiarid watershed. Several statistical indices were computed, the drought SPI was calculated using PERSIANN-CCS-CDR estimates, ERA5 products, and observed records as an input in the SPI formula using Gamma distribution to simulate drought from 1983 to 2017. The preliminary comparison and evaluation results of PERSIANN-CCS-CDR estimates and ERA5 datasets showed good CC on a basin scale for monthly precipitation, with a slight overestimation of the observed precipitation shown by the PBIAS. The NSE scored 0.41 for PERSIANN-CCS-CDR and 0.72 for ERA5. The results for SM2RAIN-ASCAT showed an overestimation of the observed precipitation data. At the basin scale, the SPI3 correlation coefficients between the PERSIANN-CCS-CDR monthly estimates and observed gauge rainfall data were greater than 0.67, and the RMSE was closer to 0, outperforming ERA5 in the SPI3 evaluation. more
Atmosphere Climate Data Records H-SAF Validation

Evaluation and intercomparison of multiple satellite-derived and reanalysis downward shortwave radiation products in China

Author(s):
Tong, Liu; He, Tao; Ma, Yichuan; Zhang, Xiaotong
Publication title: International Journal of Digital Earth
2023
 | Volume: 16 | Issue: 1
2023
DOI: 10.1080/17538947.2023.2212918
Abstract:
Downward shortwave radiation (DSR) is a critical variable in energy balance driving Earth’s surface processes. Satellite-derived and reanalysis DSR pr… Downward shortwave radiation (DSR) is a critical variable in energy balance driving Earth’s surface processes. Satellite-derived and reanalysis DSR products have been developed and continuously improved during the last decades. However, as those products have different temporal resolutions, their performances in different time scales have not been well-documented, particularly in China. This study intended to evaluate several DSR products across multiple time scales (i.e. instantaneous, 1-hourly, daily, and monthly average) and ecosystems in China. Six DSR products, including GLASS, BESS, CLARA-A2, MCD18A1, ERA5 and MERRA-2, were evaluated against ground measurements at Chinese Ecosystem Research Network (CERN) and integrated land-atmosphere interaction observation (TPDC) sites from 2009 to 2012. The instantaneous DSR of MCD18 showed a root mean square error (RMSE) of 146.02 W/m2. The hourly RMSE of ERA5 (155.52 W/m2) was largely smaller than MERRA-2 (188.53 W/m2). On the daily and monthly scale, BESS had the most optimized accuracy among the six products (RMSE of 36.82 W/m2). For the satellite-derived DSR products, the monthly accuracy at CERN can meet the threshold accuracy requirement set by World Meteorological Organization (WMO) for Global Numerical Weather Prediction (20 W/m2). more
Atmosphere CM-SAF Climate Data Records Validation

EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset

Author(s):
Overeem, A; van den Besselaar, E; van der Schrier, G; Meirink, JF; van der Plas, E; Leijnse, H
Publication title: EARTH SYSTEM SCIENCE DATA
2023
 | Volume: 15 | Issue: 3
2023
DOI: 10.5194/essd-15-1441-2023
Abstract:
The European climatological high-resolution gauge-adjusted radar precipitation dataset, EURADCLIM, addresses the need for an accurate (sub)daily preci… The European climatological high-resolution gauge-adjusted radar precipitation dataset, EURADCLIM, addresses the need for an accurate (sub)daily precipitation product covering 78 % of Europe at a high spatial resolution. A climatological dataset of 1 and 24 h precipitation accumulations on a 2 km grid is derived for the period 2013 through 2020. The starting point is the European Meteorological Network (EUMETNET) Operational Program on the Exchange of Weather Radar Information (OPERA) gridded radar dataset of 15 min instantaneous surface rain rates, which is based on data from, on average, 138 ground-based weather radars. First, methods are applied to further remove non-meteorological echoes from these composites by applying two statistical methods and a satellite-based cloud-type mask. Second, the radar composites are merged with the European Climate Assessment & Dataset (ECA&D) with potentially similar to 7700 rain gauges from National Meteorological and Hydrological Services (NMHSs) in order to substantially improve its quality. Characteristics of the radar, rain gauge and satellite datasets are presented, as well as a detailed account of the applied algorithms. The clutter-removal algorithms are effective while removing few precipitation echoes. The usefulness of EURADCLIM for quantitative precipitation estimation (QPE) is confirmed by comparison against rain gauge accumulations employing scatter density plots, statistical metrics and a spatial verification. These show a strong improvement with respect to the original OPERA product. The potential of EURADCLIM to derive pan-European precipitation climatologies and to evaluate extreme precipitation events is shown. Specific attention is given to the remaining artifacts in and limitations of EURADCLIM. Finally, it is recommended to further improve EURADCLIM by applying algorithms to 3D instead of 2D radar data and by obtaining more rain gauge data for the radar-gauge merging. The EURADCLIM 1 and 24 h precipitation datasets are publicly available at https://doi.org/10.21944/7ypj-wn68 (Overeem et al., 2022a) and https://doi.org/10.21944/1a54-gg96 (Overeem et al., 2022b). more
Application Atmosphere CM-SAF Climate Data Records

Estimating the Impact of Assimilating Cirrus Cloud–Contaminated Hyperspectral Infrared Radiances for Numerical Weather Prediction

Author(s):
Marquis, J.W.; Dolinar, E.K.; Garnier, A.; Campbell, J.R.; Ruston, B.C.; Yang, P.; Zhang, J.
Publication title: Journal of Atmospheric and Oceanic Technology
2023
 | Volume: 40 | Issue: 3
2023
DOI: 10.1175/JTECH-D-21-0165.1
Abstract:
The assimilation of hyperspectral infrared sounders (HIS) observations aboard Earth-observing satellites has become vital to numerical weather predict… The assimilation of hyperspectral infrared sounders (HIS) observations aboard Earth-observing satellites has become vital to numerical weather prediction, yet this assimilation is predicated on the assumption of clear-sky obser-vations. Using collocated assimilated observations from the Atmospheric Infrared Sounder (AIRS) and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), it is found that nearly 7.7% of HIS observations assimilated by the Naval Research Laboratory Variational Data Assimilation System–Accelerated Representer (NAVDAS-AR) are contaminated by cirrus clouds. These contaminating clouds primarily exhibit visible cloud optical depths at 532 nm (COD532nm) below 0.10 and cloud-top temperatures between 240 and 185 K as expected for cirrus clouds. These contamination statistics are consistent with simulations from the Radiative Transfer for TOVS (RTTOV) model showing a cirrus cloud with a COD532nm of 0.10 imparts brightness temperature differences below typical innovation thresholds used by NAVDAS-AR. Using a one-dimensional variational (1DVar) assimilation system coupled with RTTOV for forward and gradient radiative transfer, the analysis temperature and moisture impact of assimilating cirrus-contaminated HIS observations is estimated. Large differences of 2.5 K in temperature and 11 K in dewpoint are possible for a cloud with COD532nm of 0.10 and cloud-top temperature of 210 K. When normalized by the contamination statistics, global differences of nearly 0.11 K in temperature and 0.34 K in dewpoint are possible, with temperature and dewpoint tropospheric root-mean-squared errors (RMSDs) as large as 0.06 and 0.11 K, respectively. While in isolation these global estimates are not particularly concerning, differences are likely much larger in regions with high cirrus frequency. © 2023 American Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

Efficiency of the NWC SAF Version 2021 CRRPh Precipitation Product: Comparison against Previous NWC SAF Precipitation Products and the Influence of Topography

Author(s):
Karagiannidis, A.; Lahuerta, J.A.; Calbet, X.; Lliso, L.; Lagouvardos, K.; Kotroni, V.; Ripodas, P.
Publication title: Climate
2023
 | Volume: 11 | Issue: 2
2023
DOI: 10.3390/cli11020034
Abstract:
The algorithm of the Convective Rainfall Rate with Microphysical Properties (CRRPh) product of the 2021 version of the Nowcasting and Very Short Range… The algorithm of the Convective Rainfall Rate with Microphysical Properties (CRRPh) product of the 2021 version of the Nowcasting and Very Short Range Forecasting Satellite Application Facility (NWC SAF) presents innovative characteristics. It was developed employing principal components analysis to reduce the number of utilized parameters and uses the same mathematical scheme for day and night, simulating the missing visual channels and satellite-derived cloud water path information that is unavailable during nighttime. Applying adequate statistical methodologies and scores and using rain gauge data as ground truth, it is shown that the new algorithm appears to be significantly improved compared to its predecessors in regard to the delineation of the precipitation areas. In addition, it minimizes the day–night difference in the estimation efficiency, which is a remarkable achievement. The new product suffers from slightly higher errors in the precipitation accumulations. Finally, it is shown that topography does not seem to affect the estimation efficiency of the product. In light of these results, it is argued that, overall, the new algorithm outperforms its predecessors and, possibly after adequate adaptations, can be used as a real-time total precipitation product. © 2023 by the authors. more
Application Atmosphere NWC-SAF Software for CDR development Validation

Drivers of Antarctic sea ice advance

Author(s):
Himmich, Kenza; Vancoppenolle, Martin; Madec, Gurvan; Sallée, Jean-Baptiste; Holland, Paul R.; Lebrun, Marion
Publication title: Nature Communications
2023
 | Volume: 14 | Issue: 1
2023
DOI: 10.1038/s41467-023-41962-8
Abstract:
Antarctic sea ice is mostly seasonal. While changes in sea ice seasonality have been observed in recent decades, the lack of process understanding rem… Antarctic sea ice is mostly seasonal. While changes in sea ice seasonality have been observed in recent decades, the lack of process understanding remains a key challenge to interpret these changes. To address this knowledge gap, we investigate the processes driving the ice season onset, known as sea ice advance, using remote sensing and in situ observations. Here, we find that seawater freezing predominantly drives advance in the inner seasonal ice zone. By contrast, in an outer band a few degrees wide, advance is due to the import of drifting ice into warmer waters. We show that advance dates are strongly related to the heat stored in the summer ocean mixed layer. This heat is controlled by the timing of sea ice retreat, explaining the tight link between retreat and advance dates. Such a thermodynamic linkage strongly constrains the climatology and interannual variations, albeit with less influence on the latter. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Difference between WMO Climate Normal and Climatology: Insights from a Satellite-Based Global Cloud and Radiation Climate Data Record

Author(s):
Devasthale, Abhay; Karlsson, Karl-Göran; Andersson, Sandra; Engström, Erik
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 23
2023
DOI: 10.3390/rs15235598
Abstract:
The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e., 1991–2020, be used to compute the climate normals of… The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e., 1991–2020, be used to compute the climate normals of geophysical variables. A unique aspect of this recent 30-year period is that the satellite-based observations of many different essential climate variables are available during this period, thus opening up new possibilities to provide a robust, global basis for the 30-year reference period in order to allow climate-monitoring and climate change studies. Here, using the satellite-based climate data record of cloud and radiation properties, CLARA-A3, for the month of January between 1981 and 2020, we illustrate the difference between the climate normal, as defined by guidelines from WMO on calculations of 30 yr climate normals, and climatology. It is shown that this difference is strongly dependent on the climate variable in question. We discuss the impacts of the nature and availability of satellite observations, variable definition, retrieval algorithm and programmatic configuration. It is shown that the satellite-based climate data records show enormous promise in providing a climate normal for the recent 30-year period (1991–2020) globally. We finally argue that the holistic perspectives from the global satellite community should be increasingly considered while formulating the future WMO guidelines on computing climate normals. more
Atmosphere CM-SAF Climate Data Records Validation

Direct observation of Earth’s spectral long-wave feedback parameter

Author(s):
Roemer, Florian E.; Buehler, Stefan A.; Brath, Manfred; Kluft, Lukas; John, Viju O.
Publication title: Nature Geoscience
2023
 | Volume: 16 | Issue: 5
2023
DOI: 10.1038/s41561-023-01175-6
Abstract:
Abstract The spectral long-wave feedback parameter represents how Earth’s outgoing long-wave radiation adjusts to temperature changes and … Abstract The spectral long-wave feedback parameter represents how Earth’s outgoing long-wave radiation adjusts to temperature changes and directly impacts Earth’s climate sensitivity. Most research so far has focused on the spectral integral of the feedback parameter. Spectrally resolving the feedback parameter permits inferring information about the vertical distribution of long-wave feedbacks, thus gaining a better understanding of the underlying processes. However, investigations of the spectral long-wave feedback parameter have so far been limited mostly to model studies. Here we show that it is possible to directly observe the global mean all-sky spectral long-wave feedback parameter using satellite observations of seasonal and interannual variability. We find that spectral bands subject to strong water-vapour absorption exhibit a substantial stabilizing net feedback. We demonstrate that part of this stabilizing feedback is caused by the change of relative humidity with warming, the radiative fingerprints of which can be directly observed. Therefore, our findings emphasize the importance of better understanding processes affecting the present distribution and future trends in relative humidity. This observational constraint on the spectral long-wave feedback parameter can be used to evaluate the representation of long-wave feedbacks in global climate models and to better constrain Earth’s climate sensitivity. more
Application Atmosphere EUM-Secr NWP-SAF Software for CDR development

Deep learning methods for intra-day cloudiness prediction using geostationary satellite images in a solar forecasting framework

Author(s):
Marchesoni-Acland, F; Herrera, A; Mozo, F; Camiruaga, I; Castro, A; Alonso-Suarez, R
Publication title: SOLAR ENERGY
2023
 | Volume: 262
2023
DOI: 10.1016/j.solener.2023.111820
Abstract:
Accurate solar resource forecasting remains a challenge. Electricity grid applications require both days-ahead and intra-day prediction. Satellite-bas… Accurate solar resource forecasting remains a challenge. Electricity grid applications require both days-ahead and intra-day prediction. Satellite-based methods are known to be the best option for hourly intra-day solar forecasts up to some hours ahead. An adapted Deep Learning (DL) method has been recently reported to outperform the traditional Cloud Motion Vectors (CMV) strategy. This article analyzes the utilization of a well-documented computer vision DL architecture, the U-Net in various forms, for the satellite Earth albedo forecast problem (cloudiness), a straightforward proxy for solar irradiance forecast. It is shown that the U -Net performs better than advanced and optimized CMV techniques and previous art IrradianceNet, setting it at the state-of-the-art. The tests are done over the Pampa Humeda region of southeast South America, an area in which challenging cloud conditions are frequent. The data for this study are GOES-16 visible channel images. These images present a finer spatial (& SIME; 1 km/pixel) and temporal (10 min) resolution than previously explored data sources for solar forecasting. Moreover, the image size used here is x4 bigger (1024 x 1024 pixels) and the predictions reach further into the future (5 h) than in previous works. The analysis includes several ablation studies, involving different architectures, optimization objectives, inputs, and network sizes. The U-Net is optimized for direct and differential image prediction, being the latter a better-performing option. More notably, the U-Net models are shown to be able to predict cloud extinction, something that has been a barrier for CMV methods. more
Application Atmosphere CM-SAF Climate Data Records

Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records

Author(s):
Devasthale, Abhay; Karlsson, Karl-Göran
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 15
2023
DOI: 10.3390/rs15153819
Abstract:
Forty years of cloud observations are available globally from satellites, allowing derivation of climate data records (CDRs) for climate change studie… Forty years of cloud observations are available globally from satellites, allowing derivation of climate data records (CDRs) for climate change studies. The aim of this study is to investigate how stable these cloud CDRs are and whether they qualify stability requirements recommended by the WMO’s Global Climate Observing System (GCOS). We also investigate robust trends in global total cloud amount (CA) and cloud top temperature (CTT) that are significant and common across all CDRs. The latest versions of four global cloud CDRs, namely CLARA-A3, ESA Cloud CCI, PATMOS-x, and ISCCP-HGM are analysed. This assessment finds that all three AVHRR-based cloud CDRs (i.e., CLARA-A3, ESA Cloud CCI and PATMOS-x) satisfy even the strictest GCOS stability requirements for CA and CTT when averaged globally. While CLARA-A3 is most stable in global averages when tested against MODIS-Aqua, PATMOS-x offers the most stable CDR spatially. While we find these results highly encouraging, there remain, however, large spatial differences in the stability of and across the CDRs. All four CDRs continue to agree on the statistically significant decrease in global cloud amount over the last four decades, although this decrease is now weaker compared to the previous assessments. This decreasing trend has been stabilizing or even reversing in the last two decades; the latter is seen also in MODIS-Aqua and CALIPSO GEWEX datasets. Statistically significant trends in CTT are observed in global averages in the AVHRR-based CDRs, but the spatial agreement in the sign and the magnitude of the trends is weaker compared to those in CA. We also present maps of Common Stability Coverage and Common Trend Coverage that could provide a valuable metric to carry out an ensemble-based analysis of the CDRs. more
Atmosphere CM-SAF Climate Data Records Validation

Deep Learning-Based Seasonal Forecast of Sea Ice Considering Atmospheric Conditions

Author(s):
Zhu, Y.; Qin, M.; Dai, P.; Wu, S.; Fu, Z.; Chen, Z.; Zhang, L.; Wang, Y.; Du, Z.
Publication title: Journal of Geophysical Research: Atmospheres
2023
 | Volume: 128 | Issue: 24
2023
DOI: 10.1029/2023JD039521
Abstract:
The ongoing decline of sea ice in the Arctic has heightened the need for accurate sea-ice forecasts to support environmental protection and resource d… The ongoing decline of sea ice in the Arctic has heightened the need for accurate sea-ice forecasts to support environmental protection and resource development in the region and beyond. While deep learning has shown promise in seasonal sea-ice forecasting, most of the existing models overlook the crucial influence of atmospheric factors, thereby limiting their ability to capture the intricate characteristics of the sea-ice system and improve forecast accuracy. To address this deficiency, we propose an attention convolutional long short-term memory ensemble network named Atsicn, which integrates atmospheric factors to enhance the precision of multi-step seasonal sea-ice concentration forecasts. Our findings reveal that Atsicn outperforms state-of-the-art dynamic and statistical models, and demonstrates remarkable reliability in extreme years. Furthermore, the impact of atmospheric factors on sea-ice forecasts exhibits significant seasonality, with a relatively minimal impact on forecasts from March to June, a growing impact from July to October, and a persistent yet diminishing impact from November to February. This study provides a practical approach for seasonal sea-ice forecasts and contributes a new perspective to the understanding of the intricate interplay between sea ice and atmospheric factors. © 2023. American Geophysical Union. All Rights Reserved. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Daily satellite-based sunshine duration estimates over Brazil: validation and intercomparison

Author(s):
Gava, Maria Lívia L. M.; Costa, Simone M. S.; Porfírio, Anthony C. S.
Publication title: Atmospheric Measurement Techniques
2023
 | Volume: 16 | Issue: 21
2023
DOI: 10.5194/amt-16-5429-2023
Abstract:
The broad geographical coverage and high temporal and spatial resolution of geostationary satellite data provide an excellent opportunity to collect i… The broad geographical coverage and high temporal and spatial resolution of geostationary satellite data provide an excellent opportunity to collect information on variables whose spatial distribution and temporal variability are not adequately represented by in situ networks. This study focuses on assessing the effectiveness of two geostationary satellite-based sunshine duration (SDU) datasets over Brazil, given the relevance of SDU to various fields, such as agriculture and the energy sector, to ensure reliable SDU data over the country. The analyzed datasets are the operational products provided by the Satellite Application Facility on Climate Monitoring (CMSAF) that uses data achieved with the Meteorological Satellite (Meteosat) series and by the Satellite and Meteorological Sensors Division of the National Institute for Space Research (DISSM–INPE) that employs Geostationary Operational Environmental Satellite (GOES) data. The analyzed period ranges from September 2013 to December 2017. The mean bias error (MBE), mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (r), and scatterplots between satellite products and in situ daily SDU measurements provided by the National Institute of Meteorology (INMET) were used to access the performance of the products. They were calculated on a monthly basis and grouped into climate regions. The statistical parameters exhibited a uniform spatial distribution, indicating homogeneity within a given region. Except for the tropical northeast oriental (TNO) region, there were no significant seasonal dependencies observed. The MBE values for both satellite products were generally low across most regions in Brazil, mainly between 0 and 1 h. The correlation coefficient (r) results indicated a strong agreement between the estimated values and the observed data, with an overall r value exceeding 0.8. Nevertheless, there were notable discrepancies in specific areas. The CMSAF product showed a tendency to overestimate observations in the TNO region, with the MBE consistently exceeding 1 h for all months, while the DISSM product exhibited a negative gradient of the MBE values in the west–east direction in the northern portion of Brazil. The scatterplots for the TNO region revealed that the underestimation pattern observed in the DISSM product was influenced by the sky condition, with more accurate estimations observed under cloudy skies. Additional analysis suggested that the biases observed might be attributed to the misrepresentation of clear-sky reflectance. In the case of the CMSAF product, the overestimation tendency observed in the TNO region appeared to be a result of systematic underestimation of the effective cloud albedo. The findings indicated that both satellite-based SDU products generally exhibited good agreement with the ground observations across Brazil, although their performance varied across different regions and seasons. The analyzed operational satellite products present a reliable source of data to several applications, which is an asset due to its high spatial resolution and low time latency. more
Atmosphere CM-SAF Climate Data Records Validation

Current-climate sea ice amount and seasonality as constraints for future Arctic amplification

Author(s):
Linke, Olivia; Feldl, Nicole; Quaas, Johannes
Publication title: Environmental Research: Climate
2023
 | Volume: 2 | Issue: 4
2023
DOI: 10.1088/2752-5295/acf4b7
Abstract:
The recent Arctic sea ice loss is a key driver of the amplified surface warming in the northern high latitudes, and simultaneously a major source of u… The recent Arctic sea ice loss is a key driver of the amplified surface warming in the northern high latitudes, and simultaneously a major source of uncertainty in model projections of Arctic climate change. Previous work has shown that the spread in model predictions of future Arctic amplification (AA) can be traced back to the inter-model spread in simulated long-term sea ice loss. We demonstrate that the strength of future AA is further linked to the current climate’s, observable sea ice state across the multi-model ensemble of the 6th Coupled Model Intercomparison Project (CMIP6). The implication is that the sea-ice climatology sets the stage for long-term changes through the 21st century, which mediate the degree by which Arctic warming is amplified with respect to global warming. We determine that a lower base-climate sea ice extent and sea ice concentration (SIC) in CMIP6 models enable stronger ice melt in both future climate and during the seasonal cycle. In particular, models with lower Arctic-mean SIC project stronger future ice loss and a more intense seasonal cycle in ice melt and growth. Both processes systemically link to a larger future AA across climate models. These results are manifested by the role of climate feedbacks that have been widely identified as major drivers of AA. We show in particular that models with low base-climate SIC predict a systematically stronger warming contribution through both sea-ice albedo feedback and temperature feedbacks in the future, as compared to models with high SIC. From our derived linear regressions in conjunction with observations, we estimate a 21st-century AA over sea ice of 2.47–3.34 with respect to global warming. Lastly, from the tight relationship between base-climate SIC and the projected timing of an ice-free September, we predict a seasonally ice-free Arctic by mid-century under a high-emission scenario. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Combining Landsat TIR-imagery data and ERA5 reanalysis information with different calibration strategies to improve simulations of streamflow and river temperature in the Canadian Subarctic

Author(s):
Rincón, E.; St-hilaire, A.; Bergeron, N.E.; Dugdale, S.J.
Publication title: Hydrological Processes
2023
 | Volume: 37 | Issue: 10
2023
DOI: 10.1002/hyp.15008
Abstract:
Arctic and Subarctic environments are among the most vulnerable regions to climate change. Increases in liquid precipitation and changes in snowmelt o… Arctic and Subarctic environments are among the most vulnerable regions to climate change. Increases in liquid precipitation and changes in snowmelt onset are cited as the main drivers of change in streamflow and water temperature patterns in some of the largest rivers of the Canadian Arctic. However, in spite of this evidence, there is still a lack of research on water temperature, particularly in the eastern Canadian Arctic. In this paper, we use the CEQUEAU hydrological-water temperature model to derive consistent long-term daily flow and stream temperature time series in Aux Mélèzes River, a non-regulated basin (41 297 km2) in the eastern Canadian subarctic. The model was forced using reanalysis data from the fifth-generation ECMWF atmospheric reanalyses (ERA5) from 1979 to 2020. We used water temperature derived from thermal infrared (TIR) images as reference data to calibrate CEQUEAU's water temperature model, with calibration performed using single-site, multi-site, and upscaling factors approaches. Our results indicate that the CEQUEAU model can simulate streamflow patterns in the river and shows excellent spatiotemporal performance with Kling-Gupta Efficiency (KGE) metric >0.8. Using the best-performing flow simulation as one of the inputs allowed us to produce synthetic daily water temperature time series throughout the basin, with the multi-site calibration approach being the most accurate with root mean square errors (RMSE) <2.0°C. The validation of the water temperature simulations with a three-year in situ data logger dataset yielded an RMSE = 1.38°C for the summer temperatures, highlighting the robustness of the calibrated parameters and the chosen calibration strategy. This research demonstrates the reliability of TIR imagery and ERA5 as sources of model calibration data in data-sparse environments and underlines the CEQUEAU model as an assessment tool, opening the door to its use to assess climate change impact on the arctic regions of Canada. © 2023 The Authors. Hydrological Processes published by John Wiley & Sons Ltd. more
Application CM-SAF Climate Data Records Land

Cloud Climatologies from Global Climate Models-A Comparison of CMIP5 and CMIP6 Models with Satellite Data

Author(s):
Lauer, Axel; Bock, Lisa; Hassler, Birgit; Schröder, Marc; Stengel, Martin
Publication title: Journal of Climate
2023
 | Volume: 36 | Issue: 2
2023
DOI: 10.1175/JCLI-D-22-0181.1
Abstract:
Simulating clouds with global climate models is challenging as the relevant physics involves many nonlinear processes covering a wide range of spatial… Simulating clouds with global climate models is challenging as the relevant physics involves many nonlinear processes covering a wide range of spatial and temporal scales. As key components of the hydrological cycle and the climate system, an evaluation of clouds from models used for climate projections is an important prerequisite for assessing the confidence in the results from these models. Here, we compare output from models contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6) with satellite data and with results from their predecessors (CMIP5). We use multiproduct reference datasets to estimate the observational uncertainties associated with different sensors and with internal variability on a per-pixel basis. Selected cloud properties are also analyzed by region and by dynamical regime and thermodynamic conditions. Our results show that for parameters such as total cloud cover, cloud water path, and cloud radiative effect, the CMIP6 multimodel mean performs slightly better than the CMIP5 ensemble mean in terms of mean bias, pattern correlation, and relative root-mean square deviation. The intermodel spread in CMIP6, however, is not reduced compared to CMIP5. Compared with CALIPSO-ICECLOUD data, the CMIP5/6 models overestimate cloud ice, particularly in the lower and middle troposphere, partly due to too high ice fractions for given temperatures. This bias is reduced in the CMIP6 multimodel mean. While many known biases such as an underestimation in cloud cover in stratocumulus regions remain in CMIP6, we find that the CMIP5 problem of too few but too reflective clouds over the Southern Ocean is significantly improved. © 2022 American Meteorological Society. more
Atmosphere CM-SAF Climate Data Records

Climatology of Tropical Cyclone Precipitation in the S2S Models

Author(s):
García-Franco, J.L.; Lee, C.-Y.; Camargo, S.J.; Tippett, M.K.; Kim, D.; Molod, A.; Lim, Y.-K.
Publication title: Weather and Forecasting
2023
 | Volume: 38 | Issue: 9
2023
DOI: 10.1175/WAF-D-23-0029.1
Abstract:
This study evaluates the representation of tropical cyclone precipitation (TCP) in reforecasts from the Subseasonal to Seasonal (S2S) Prediction Proje… This study evaluates the representation of tropical cyclone precipitation (TCP) in reforecasts from the Subseasonal to Seasonal (S2S) Prediction Project. The global distribution of precipitation in S2S models shows relevant biases in the multimodel mean ensemble that are characterized by wet biases in total precipitation and TCP, except for the Atlantic. The TCP biases can contribute more than 50% of the total precipitation biases in basins such as the southern Indian Ocean and South Pacific. The magnitude and spatial pattern of these biases exhibit little variation with lead time. The origins of TCP biases can be attributed to biases in the frequency of tropical cyclone occurrence. The S2S models sim-ulate too few TCs in the Atlantic and western North Pacific and too many TCs in the Southern Hemisphere and eastern North Pacific. At the storm scale, the average peak precipitation near the storm center is lower in the models than observations due to a too high proportion of weak TCs. However, this bias is offset in some models by higher than observed precipitation rates at larger radii (300–500 km). An analysis of the mean TCP for each TC at each grid point reveals an overestimation of TCP rates, particularly in the near-equatorial Indian and western Pacific Oceans. These findings suggest that the simulation of TC occurrence and the storm-scale precipitation require better representation in order to reduce TCP biases and enhance the subseasonal prediction skill of mean and extreme total precipitation. © 2023 American Meteorological Society. more
Application Atmosphere CM-SAF Climate Data Records

Climate-induced decline in the quality and quantity of European hops calls for immediate adaptation measures

Author(s):
Mozny, M.; Trnka, M.; Vlach, V.; Zalud, Z.; Cejka, T.; Hajkova, L.; Potopova, V.; Semenov, M.A.; Semeradova, D.; Büntgen, U.
Publication title: Nature Communications
2023
 | Volume: 14 | Issue: 1
2023
DOI: 10.1038/s41467-023-41474-5
Abstract:
A recent rise in the global brewery sector has increased the demand for high-quality, late summer hops. The effects of ongoing and predicted climate c… A recent rise in the global brewery sector has increased the demand for high-quality, late summer hops. The effects of ongoing and predicted climate change on the yield and aroma of hops, however, remain largely unknown. Here, we combine meteorological measurements and model projections to assess the climate sensitivity of the yield, alpha content and cone development of European hops between 1970 and 2050 CE, when temperature increases by 1.4 °C and precipitation decreases by 24 mm. Accounting for almost 90% of all hop-growing regions, our results from Germany, the Czech Republic and Slovenia show that hop ripening started approximately 20 days earlier, production declined by almost 0.2 t/ha/year, and the alpha content decreased by circa 0.6% when comparing data before and after 1994 CE. A predicted decline in hop yield and alpha content of 4–18% and 20–31% by 2050 CE, respectively, calls for immediate adaptation measures to stabilize an ever-growing global sector. © 2023, Springer Nature Limited. more
Application Atmosphere CM-SAF Climate Data Records

Climate of Syria Based on Cordex Simulations: Present and Future

Author(s):
Naaouf, N.; Torma, C.Z.
Publication title: Earth Systems and Environment
2023
 | Volume: 7 | Issue: 3
2023
DOI: 10.1007/s41748-023-00351-3
Abstract:
Regional climate models are widely used to assess current and future impacts of climate change. In this study, we evaluate the performance of regional… Regional climate models are widely used to assess current and future impacts of climate change. In this study, we evaluate the performance of regional climate models from the Coordinated Regional Climate Downscaling Experiment programme integrated over the following three CORDEX domains: AFR, MNA and WAS. Four meteorological variables (temperature, precipitation, solar radiation and cloud cover) were evaluated over Syria at a grid spacing of 0.44°. The performance of five models in simulating the present climate characteristics (1989–2008) is evaluated with respect to the observations: CRU, ERA5 reanalysis and SARA and CLARA satellite data. We find that the mini-ensemble captures well the general spatial patterns and annual cycles of the selected variables. Anotheraim of this study was to assess the expected change of the mentioned four climate variables over Syria under the moderate emission scenario (RCP4.5) and the high emission scenario (RCP8.5) in the near future (2031–2050) and in the far future (2080–2099) with respect to the present climate (1989–2008). The simulations show a decreasing trend in cloud cover (between 6% and 10%) and precipitation (up to 9%) by mid and late century, regardless of the forcing scenarios. The simulations show a pronounced warming over Syria, which is expected to reach 6 °C by the end of the twenty-first century following the high greenhouse gas concentration scenario (RCP8.5). Furthermore, such an increase, combined with a decrease in precipitation, will shift Syria’s climate towards a more arid one. © 2023, The Author(s). more
Atmosphere CM-SAF Climate Data Records Validation

CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023

Author(s):
Karlsson, Karl-Göran; Stengel, Martin; Meirink, Jan Fokke; Riihelä, Aku; Trentmann, Jörg; Akkermans, Tom; Stein, Diana; Devasthale, Abhay; Eliasson, Salomon; Johansson, Erik; Håkansson, Nina; Solodovnik, Irina; Benas, Nikos; Clerbaux, Nicolas; Selbach, Nathalie; Schröder, Marc; Hollmann, Rainer
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 11
2023
DOI: 10.5194/essd-15-4901-2023
Abstract:
This paper presents the third edition of The Satellite Application Facility on Climate Monitoring's (CM SAF) cloud, albedo, and surface radiation data… This paper presents the third edition of The Satellite Application Facility on Climate Monitoring's (CM SAF) cloud, albedo, and surface radiation dataset from advanced very-high-resolution radiometer (AVHRR) data, CLARA-A3. The content of earlier CLARA editions, namely cloud, surface albedo, and surface radiation products, has been extended with two additional surface albedo products (blue- and white-sky albedo), three additional surface radiation products (net shortwave and longwave radiation, and surface radiation budget), and two top of atmosphere radiation budget products (reflected solar flux and outgoing longwave radiation). The record length is extended to 42 years (1979–2020) by also incorporating results from the first version of the advanced very high resolution radiometer imager (AVHRR/1). A continuous extension of the climate data record (CDR) has also been implemented by processing an interim climate data record (ICDR) based on the same set of algorithms but with slightly changed ancillary input data. All products are briefly described together with validation results and intercomparisons with currently existing similar CDRs. The extension of the product portfolio and the temporal coverage of the data record, together with product improvements, is expected to enlarge the potential of using CLARA-A3 for climate change studies and, in particular, studies of potential feedback effects between clouds, surface albedo, and radiation. The CLARA-A3 data record is hosted by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) CM SAF and is freely available at https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V003 (Karlsson et al., 2023b). more
Atmosphere CM-SAF Climate Data Records EUM-Secr Land Method OSI-SAF Validation

CLAAS-3: The third edition of the CM SAF cloud data record based on SEVIRI observations

Author(s):
Benas, N.; Solodovnik, I.; Stengel, M.; Huser, I.; Karlsson, K.-G.; Hakansson, N.; Johansson, E.; Eliasson, S.; Schroder, M.; Hollmann, R.; Meirink, J.F.
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 11
2023
DOI: 10.5194/essd-15-5153-2023
Abstract:
CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI (Spinning Enhanced Visible and InfraRed Imager), was released in December 2022. … CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI (Spinning Enhanced Visible and InfraRed Imager), was released in December 2022. It is based on observations from SEVIRI, on board geostationary satellites Meteosat-8, 9, 10 and 11, which are operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). CLAAS-3 was produced and released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF), which aims to provide high-quality satellite-based data records suitable for climate monitoring applications. Compared to previous CLAAS releases, CLAAS-3 is expanded in terms of both temporal extent and cloud properties included, and it is based on partly updated retrieval algorithms. The available data span the period from 2004 to present, covering Europe; Africa; the Atlantic Ocean; and parts of South America, the Middle East and the Indian Ocean. They include cloud fractional coverage, cloud-top height, phase (liquid or ice) and optical and microphysical properties (water path, optical thickness, effective radius and droplet number concentration), from instantaneous data (every 15min) to monthly averages. In this study we present an extensive evaluation of CLAAS-3 cloud properties, based on independent reference data sets. These include satellite-based retrievals from active and passive sensors, ground-based observations and in situ measurements from flight campaigns. Overall results show very good agreement, with small biases attributable to different sensor characteristics, retrieval/sampling approaches and viewing/illumination conditions. These findings demonstrate the fitness of CLAAS-3 to support the intended applications, which include evaluation of climate models, cloud characterisation and process studies focusing especially on the diurnal cycle and cloud filtering for other applications. The CLAAS-3 data record is publicly available via the CM SAF website at 10.5676/EUM_SAF_CM/CLAAS/V003 (Meirink et al., 2022). © 2023 Copernicus GmbH. All rights reserved. more
Atmosphere CM-SAF Climate Data Records Validation

Calibration and Validation of Global Horizontal Irradiance Clear Sky Models against McClear Clear Sky Model in Morocco

Author(s):
Mendyl, Abderrahmane; Mabasa, Brighton; Bouzghiba, Houria; Weidinger, Tamás
Publication title: Applied Sciences
2023
 | Volume: 13 | Issue: 1
2023
DOI: 10.3390/app13010320
Abstract:
This study calibrated and compared the capabilities of hourly global horizontal irradiance (GHI) clear sky models for six Moroccan locations, using th… This study calibrated and compared the capabilities of hourly global horizontal irradiance (GHI) clear sky models for six Moroccan locations, using the McClear clear sky model as a reference. Complex clear sky models, namely Bird, Simplified Solis, Ineichen and Perez, and simple clear sky models, namely Adnot–Bourges–Campana–Gicquel (ABCG), Berger–Duffie, and Haurwitz were tested. The SOLCAST satellite-based dataset estimates were validated against the McClear clear sky model. pvlib python was used to configure the models, and ERA5 hourly fractional cloud cover was used to identify clear-sky days. The study period was from 2014 to 2021, and the study sites were in different climatic regions in Morocco. Bar graphs, tables, and quantitative statistical metrics, namely relative mean bias error (rMBE), relative root mean square error (rRMSE), relative mean absolute error (rMAE), and the coefficient of determination (R2), were used to quantify the skill of the clear sky model at different sites. The overall rMBE was negative in 5/6 sites, indicating consistent overestimation of GHI, and positive in Tantan (14.4%), indicating frequent underestimation of GHI. The overall rRMSE varied from 6 to 22%, suggesting strong agreement between clear sky models and the McClear clear sky model. The overall correlation was greater than 0.96, indicating a very strong relationship. Overall, the Bird clear sky model proved to be the most feasible. Complex clear sky models outperformed simple clear sky models. The SOLCAST satellite-based dataset and ERA5 cloud fraction information could well be used with quantifiable certainty as an accurate clear sky model in the study region and in other areas where complex clear sky models’ inputs are not available. more
Application Atmosphere CM-SAF Climate Data Records

Causes for Atlantic Freshwater Content Variability in the GECCO3 Ocean Synthesis

Author(s):
Liu, Xin; Köhl, Armin; Stammer, Detlef
Publication title: Journal of Geophysical Research: Oceans
2023
 | Volume: 128 | Issue: 1
2023
DOI: 10.1029/2022JC018796
Abstract:
Regional freshwater content (FWC) changes are studied over the period 1961–2018 using the GECCO3 ocean synthesis. In four dynamically distinct regions… Regional freshwater content (FWC) changes are studied over the period 1961–2018 using the GECCO3 ocean synthesis. In four dynamically distinct regions of the Atlantic, the study identifies causes for FWC variability with a focus on interannual and decadal time-scale changes. Results show that in each region, it is a combination of the surface freshwater flux and the net freshwater transport across the region's boundaries that act jointly in changing the respective FWC. Surface flux mainly contributes to the FWC variability on multi-decadal time scales. The impact of surface flux also increases toward the tropics. On shorter time scales, it is especially horizontal transport fluctuations, leading to FWC changes in mid and high latitudes. Going from north to the south, the transport across a single meridional boundary becomes less correlated with the FWC changes but the net transport across both boundaries plays an increasingly important role. Moreover, the subpolar box is mainly gyre driven, which differs from the other two, essentially overturning driven, North Atlantic boxes. In the tropical Atlantic, the shallow overturning cell and the deep overturning contribute about equal amounts to the freshwater variations. © 2022. The Authors. more
Atmosphere CM-SAF Climate Data Records Validation

Benefits of pairing floating solar photovoltaics with hydropower reservoirs in Europe

Author(s):
Kakoulaki, G.; Gonzalez Sanchez, R.; Gracia Amillo, A.; Szabo, S.; De Felice, M.; Farinosi, F.; De Felice, L.; Bisselink, B.; Seliger, R.; Kougias, I.; Jaeger-Waldau, A.
Publication title: Renewable and Sustainable Energy Reviews
2023
 | Volume: 171
2023
DOI: 10.1016/j.rser.2022.112989
Abstract:
Achieving carbon-neutrality is increasing the demand of renewable electricity which is raising the competition for land and associated acquisition cos… Achieving carbon-neutrality is increasing the demand of renewable electricity which is raising the competition for land and associated acquisition costs. Installation of floating photovoltaic (FPV) on existing hydropower reservoirs offers one solution to limited land availability while providing solar electricity, leveraging water bodies, and reducing water evaporation losses. This work assesses the potential electricity output of FPVs at regional and national levels on 337 hydropower reservoirs in the EU27 considering four scenarios and two types of floaters. Evaporation, water losses and water savings due to FPVs installation are also estimated using climatic parameters for the year 2018. The reservoirs' total water losses are estimated at 9380 mcm. The installation of FPVs of equal installed capacity as the hydropower plants, has the potential to generate 42.31 TWh covering 2.3% of the total reservoir area. In this case, up to 557 mcm could be saved by installing FPV. The FPVs' multiple benefits and the potential offered by existing hydropower reservoirs are compatible with the EU's goals for net zero emissions and more autonomy from imported fossil fuels and energy transformation. more
Application Atmosphere CM-SAF Climate Data Records

Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard

Author(s):
Röhrs, J.; Gusdal, Y.; Rikardsen, E.S.U.; Durán Moro, M.; Brændshøi, J.; Kristensen, N.M.; Fritzner, S.; Wang, K.; Sperrevik, A.K.; Idžanović, M.; Lavergne, T.; Debernard, J.B.; Christensen, K.H.
Publication title: Geoscientific Model Development
2023
 | Volume: 16 | Issue: 18
2023
DOI: 10.5194/gmd-16-5401-2023
Abstract:
An operational ocean and sea ice forecast model, Barents-2.5, is implemented for short-term forecasting at the coast off northern Norway, the Barents … An operational ocean and sea ice forecast model, Barents-2.5, is implemented for short-term forecasting at the coast off northern Norway, the Barents Sea, and the waters around Svalbard. Primary forecast parameters are sea ice concentration (SIC), sea surface temperature (SST), and ocean currents. The model also provides input data for drift modeling of pollutants, icebergs, and search-and-rescue applications in the Arctic domain. Barents-2.5 has recently been upgraded to include an ensemble prediction system with 24 daily realizations of the model state. SIC, SST, and in situ hydrography are constrained through the ensemble Kalman filter (EnKF) data assimilation scheme executed in daily forecast cycles with a lead time up to 66gh. Here, we present the model setup and validation in terms of SIC, SST, in situ hydrography, and ocean and ice velocities. In addition to the model's forecast capabilities for SIC and SST, the performance of the ensemble in representing the model's uncertainty and the performance of the EnKF in constraining the model state are discussed. © 2023 Johannes Röhrs et al. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Assimilation of ASCAT Radar Backscatter Coefficients over Southwestern France

Author(s):
Corchia, Timothée; Bonan, Bertrand; Rodríguez-Fernández, Nemesio; Colas, Gabriel; Calvet, Jean-Christophe
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 17
2023
DOI: 10.3390/rs15174258
Abstract:
In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (… In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (ISBA) land surface model using Meteo-France’s global Land Data Assimilation System (LDAS-Monde) tool in order to jointly analyse soil moisture and leaf area index (LAI). For the first time, observation operators based on neural networks (NNs) are trained with ISBA simulations and LAI observations from the PROBA-V satellite to predict the ASCAT backscatter signal. The trained NN-based observation operators are implemented in LDAS-Monde, which allows the sequential assimilation of backscatter observations. The impact of the assimilation is evaluated over southwestern France. The simulated and analysed backscatter signal, surface soil moisture, and LAI are evaluated using satellite observations from ASCAT and PROBA-V as well as in situ soil moisture observations. An overall improvement in the variables is observed when comparing the analysis with the open-loop simulation. The impact of the assimilation is greater over agricultural areas. more
Application Climate Data Records H-SAF Land

Assimilating FY3D-MWRI 23.8 GHz observations in the CMA-GFS 4DVAR system based on a pseudo All-Sky data assimilation method

Author(s):
Xie, H.; Han, W.; Bi, L.
Publication title: Quarterly Journal of the Royal Meteorological Society
2023
2023
DOI: 10.1002/qj.4544
Abstract:
In the current operational four-dimensional variational (4DVar) data assimilation (DA) system of the Global Forecast System developed by the China Met… In the current operational four-dimensional variational (4DVar) data assimilation (DA) system of the Global Forecast System developed by the China Meteorology Administration (CMA-GFS), all microwave observation data in cloud and precipitation regions are discarded during pre-processing. This study implemented a Pseudo All-Sky DA (referred to as PAS-DA hereafter) subsystem in the operational cycle version of the CMA-GFS (CMA-GFS v3.2). The term “pseudo” in this study indicates that the Jacobians of brightness temperature with respect to hydrometeors from the adjoint radiative transfer model were temporarily neglected. Specifically, a liquid hydrometeor sensitive channel (23.8 GHz V pol.) of the MicroWave Radiation Imager on the platform of FengYun-3D (FY3D-MWRI) was selected to assess the impact of the all-sky assimilation approach using the PAS-DA subsystem. In the observation error model, we proposed a new cumulative distribution function (CDF) bias correction method for the cloud proxy in consideration of large discrepancies between the probability density functions (PDFs) of the observed-cloud-proxy and simulated-cloud-proxy (known as “cloud bias”). Results of single-observation experiments justified that the present PAS-DA subsystem could extend analysis increments to cloud regions, meanwhile correcting the errors of humidity analysis according to the mislocation of cloud distributions. In addition, the forecast experiments that were run for 1 month of the 6 hr PAS-DA cycle in July and August 2021 demonstrate obvious superiority of the PAS-DA over the current operational clear-sky DA cycle: (a) root-mean-square errors (RMSEs) of humidity analysis were reduced by about 10% in the tropics, (b) significant improvements in humidity forecasts could be sustained for 96 hr and (c) many other forecast scores in the tropics and Southern Hemisphere also benefit from the PAS-DA approach. Therefore, the PAS-DA could be used for all-sky assimilation studies and particularly for understanding how the all-sky assimilation approach works, although the PAS-DA serves as a transition scheme from the clear-sky to “true” all-sky DA. © 2023 Royal Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

Assimilating CryoSat-2 freeboard to improve Arctic sea ice thickness estimates

Author(s):
Sievers, I.; Rasmussen, T.A.S.; Stenseng, L.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 9
2023
DOI: 10.5194/tc-17-3721-2023
Abstract:
In this study, a new method to assimilate freeboard (FB) derived from satellite radar altimetry is presented with the goal of improving the initial st… In this study, a new method to assimilate freeboard (FB) derived from satellite radar altimetry is presented with the goal of improving the initial state of sea ice thickness predictions in the Arctic. In order to quantify the improvement in sea ice thickness gained by assimilating FB, we compare three different model runs: one reference run (refRun), one that assimilates only sea ice concentration (SIC) (sicRun), and one that assimilates both SIC and FB (fbRun). It is shown that estimates for both SIC and FB can be improved by assimilation, but only fbRun improved the FB. The resulting sea ice thickness is evaluated by comparing sea ice draft measurements from the Beaufort Gyre Exploration Project (BGEP) and sea ice thickness measurements from 19 ice mass balance (IMB) buoys deployed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The sea ice thickness of fbRun compares better than refRun and sicRun to the longer BGEP observations more poorly to the shorter MOSAiC observations. Further, the three model runs are compared to the Alfred Wegener Institute (AWI) weekly CryoSat-2 sea ice thickness, which is based on the same FB observations as those that were assimilated in this study. It is shown that the FB and sea ice thickness from fbRun are closer to the AWI CryoSat-2 values than the ones from refRun or sicRun. Finally, comparisons of the abovementioned observations and both the fbRun sea ice thickness and the AWI weekly CryoSat-2 sea ice thickness were performed. At the BGEP locations, both fbRun and the AWI CryoSat-2 sea ice thickness perform equally. The total root-mean-square error (RMSE) at the BGEP locations equals 30gcm for both sea ice thickness products. At the MOSAiC locations, fbRun's sea ice thickness performs significantly better, with a total 11gcm lower RMSE. © 2023 Imke Sievers et al. more
Application Climate Data Records OSI-SAF Ocean

Assessment of the Pan-Arctic Accelerated Rate of Sea Ice Decline in CMIP6 Historical Simulations

Author(s):
Lee, Y.J.; Watts, M.; Maslowski, W.; Kinney, J.C.; Osinski, R.
Publication title: Journal of Climate
2023
 | Volume: 36 | Issue: 17
2023
DOI: 10.1175/JCLI-D-21-0539.1
Abstract:
Arctic sea ice loss in response to a warming climate is assessed in 42 models participating in phase 6 of the Coupled Model Intercomparison Project (C… Arctic sea ice loss in response to a warming climate is assessed in 42 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Sea ice observations show a significant acceleration in the rate of decline commencing near the turn of the twenty-first century. It is our assertion that state-of-the-art climate models should qualitatively reflect this accelerated trend within the limitations of internal variability and observational uncertainty. Our analysis shows that individual CMIP6 simulations of sea ice depict a wide range of model spread on biases and anomaly trends both across models and among their ensemble members. While the CMIP6 multimodel mean captures the observed sea ice area (SIA) decline relatively well, an individual model’s ability to represent the acceleration in sea ice decline remains a challenge. Seventeen (40%) out of 42 CMIP6 models and 37 (13%) out of the total 286 ensemble members reasonably capture the observed trends and acceleration in SIA decline. In addition, a larger ensemble size appears to increase the odds for a model to include at least one ensemble member skillfully representing the accelerated SIA trends. Simulations of sea ice volume (SIV) show much larger spread and uncertainty than SIA; however, due to limited availability of sea ice thickness data, these are not as well constrained by observations. Finally, we find that models with more ocean heat transport simulate larger sea ice declines, which suggests an emergent constraint in CMIP6 ensembles. This relationship points to the need for better understanding and modeling of ice–ocean interactions, especially with respect to frazil ice growth. © 2023 American Meteorological Society. All rights reserved. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Assessment of isoprene and near-surface ozone sensitivities to water stress over the Euro-Mediterranean region

Author(s):
Strada, S.; Pozzer, A.; Giuliani, G.; Coppola, E.; Solmon, F.; Jiang, X.; Guenther, A.; Bourtsoukidis, E.; Serça, D.; Williams, J.; Giorgi, F.
Publication title: Atmospheric Chemistry and Physics
2023
 | Volume: 23 | Issue: 20
2023
DOI: 10.5194/acp-23-13301-2023
Abstract:
Plants emit biogenic volatile organic compounds (BVOCs) in response to changes in environmental conditions (e.g. temperature, radiation, soil moisture… Plants emit biogenic volatile organic compounds (BVOCs) in response to changes in environmental conditions (e.g. temperature, radiation, soil moisture). In the large family of BVOCs, isoprene is by far the strongest emitted compound and plays an important role in ozone chemistry, thus affecting both air quality and climate. In turn, climate change may alter isoprene emissions by increasing temperature as well as the occurrence and intensity of severe water stresses that alter plant functioning. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) provides different parameterizations to account for the impact of water stress on isoprene emissions, which essentially reduces emissions in response to the effect of soil moisture deficit on plant productivity. By applying the regional climate-chemistry model RegCM4chem coupled to the Community Land Model CLM4.5 and MEGAN2.1, we thus performed sensitivity simulations to assess the effects of water stress on isoprene emissions and near-surface ozone levels over the Euro-Mediterranean region and across the drier and wetter summers over the 1992-2016 period using two different parameterizations of the impact of water stress implemented in the MEGAN model. Over the Euro-Mediterranean region and across the simulated summers, water stress reduces isoprene emissions on average by nearly 6 %. However, during the warmest and driest selected summers (e.g. 2003, 2010, 2015) and over large isoprene-source areas (e.g. the Balkans), decreases in isoprene emissions range from -20 % to -60 % and co-occur with negative anomalies in precipitation, soil moisture and plant productivity. Sustained decreases in isoprene emissions also occur after prolonged or repeated dry anomalies, as observed for the summers of 2010 and 2012. Although the decrease in isoprene emissions due to water stress may be important, it only reduces near-surface ozone levels by a few percent due to a dominant VOC-limited regime over southern Europe and the Mediterranean Basin. Overall, over the selected analysis region, compared to the old MEGAN parameterization, the new one leads to localized and 25 %-50 % smaller decreases in isoprene emissions and 3 %-8 % smaller reductions in near-surface ozone levels. © 2023 Copernicus GmbH. All rights reserved. more
Application Atmosphere CM-SAF Climate Data Records

Assessment of H SAF satellite snow products in hydrological applications over the Upper Euphrates Basin

Author(s):
Şensoy, Aynur; Uysal, Gökçen; Şorman, A. Arda
Publication title: Theoretical and Applied Climatology
2023
 | Volume: 151 | Issue: 1
2023
DOI: 10.1007/s00704-022-04292-1
Abstract:
Satellite technology offers alternative products for hydrological applications; however, products should be validated with benchmark models and/or dat… Satellite technology offers alternative products for hydrological applications; however, products should be validated with benchmark models and/or data sets for operational purposes. This study assesses the performance of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF) snow products of snow detection, SE-E-SEVIRI(H10), and snow water equivalent, SWE-E(H13), data sets over a mountainous catchment in the Upper Euphrates, Turkey. Moderate Resolution Imaging Spectroradiometer (MODIS) snow extent is used as a benchmark. Two different conceptual hydrological models are employed to obtain reliable results over the period 2008–2020. First, the spatio-temporal assessment of satellite-derived snow cover area (SCA) data is evaluated, followed by the calibration/validation of hydrological models, SRM and HBV, for impact analysis and hydro-validation of satellite snow products, respectively. SRM, demanding SCA as one of the primary forcings, reveals high Kling Gupta Efficiency, KGE, (0.75–0.89) in the impact analysis of satellite data. In hydro-validation analysis, noteworthy Nash–Sutcliffe Efficiency, NSE (0.89–0.92), values are obtained for SCA derived by SE-E-SEVIRI(H10) and MODIS as compared to simulated HBV model results. SWE-E(H13) product is also valuable since snow water equivalent (SWE) values are rarely available for mountainous areas. However, this product seems to need further attention. Overall results show the degree of applicability and usefulness of H SAF snow data in hydrological applications; thus, the strong need to disseminate the products is highlighted. more
Climate Data Records Cryosphere H-SAF Validation

Assessing the Fitness of Satellite Albedo Products for Monitoring Snow Albedo Trends

Author(s):
Urraca, R; Lanconelli, C; Cappucci, F; Gobron, N
Publication title: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2023
 | Volume: 61
2023
DOI: 10.1109/TGRS.2023.3281188
Abstract:
Accurate monitoring of albedo trends over snow is essential to evaluate the consequences of the global snow cover retreat on Earth's energy budget. Sa… Accurate monitoring of albedo trends over snow is essential to evaluate the consequences of the global snow cover retreat on Earth's energy budget. Satellite observations provide the best way to monitor these trends globally, but their uncertainty increases over snow. Besides, different products sometimes show diverging trends. A better assessment of the fitness of satellite products for monitoring snow albedo trends is needed. We analyze the consistency of black-sky albedo estimates from global long-term products over snow: advanced very-high-resolution radiometer (AVHRR)-based (CLARA-A2.1, GLASS-v4.2), moderate resolution imaging spectroradiometer (MODIS)-based (MCD43C3-v6.1/v6, GLASS-v4.2), multiangle imaging spectro radiometer (MISR)-based (MIL3MLSN-v4), and multisensor (C3S-v1/v2). We use MCD43C3-6.1 as the reference based on a previous comparison against in situ measurements. CLARA-A2.1 is the one most consistent with MCD43C3, but has a low coverage in high latitudes and an artificial albedo decrease since 2015. The study shows the limitations of MIL3MLSN, Global Land Surface Satellite (GLASS), and Copernicus Climate Change Service (C3S) multisensor products over snow. MIL3MLSN has a too-low coverage of albedo over snow. GLASS-AVHRR overestimates albedo in regions with seasonal snow due to delayed snowmelt and underestimates it in permanently snow-covered regions. GLASS-MODIS is more consistent with MCD43C3 at mid-latitudes, and also underestimates albedo in regions with permanent snow and has an increase in missing values after 2011. Both the GLASS datasets are temporally inconsistent with the other products. Despite the improvements from v1 to v2, C3S-v2 has the largest negative bias over snow and discontinuities in the transitions between sensors. The study evidences the difficulties of AVHRR products to provide stable snow albedo estimates in polar regions, particularly before 2000. more
CM-SAF Climate Data Records Land Validation

Application of the Pseudo-Global Warming Approach in a Kilometer-Resolution Climate Simulation of the Tropics

Author(s):
Heim, C.; Leutwyler, D.; Schär, C.
Publication title: Journal of Geophysical Research: Atmospheres
2023
 | Volume: 128 | Issue: 5
2023
DOI: 10.1029/2022JD037958
Abstract:
Clouds over tropical oceans are an important factor in the Earth's response to increased greenhouse gas concentrations, but their representation in cl… Clouds over tropical oceans are an important factor in the Earth's response to increased greenhouse gas concentrations, but their representation in climate models is challenging due to the small-scale nature of the involved convective processes. We perform two 4-year-long simulations at kilometer-resolution (3.3 km horizontal grid spacing) with the limited-area model COSMO over the tropical Atlantic on a 9,000 × 7,000 km2 domain: A control simulation under current climate conditions driven by the ERA5 reanalysis, and a climate change scenario simulation using the Pseudo-Global Warming approach. We compare these results to the changes projected in the CMIP6 scenario ensemble. Validation shows a good representation of the annual cycle of albedo, in particular for trade-wind clouds, even compared to the ERA5 reanalysis. Also, the vertical structure and annual cycle of the intertropical convergence zone (ITCZ) is accurately simulated, and the simulation does not suffer from the double ITCZ problem commonly present in global climate models (GCMs). The response to global warming differs between the COSMO simulation and the analyzed GCMs. While both exhibit an overall weakening of the Hadley circulation, the narrowing of the ITCZ (known as the deep-tropics squeeze) is not so pronounced in the kilometer-resolution simulation, likely due to the absence of a double ITCZ bias. Also, there is a more pronounced intensification of the ITCZ at the equator in the kilometer-resolution COSMO simulation, and a stronger associated increase in the anvil cloud fraction. © 2023. The Authors. more
Atmosphere CM-SAF Climate Data Records Validation

An overview of the enhanced cloud and water vapour products from EUMETSAT new generation imagers

Author(s):
Spezzi, L.; Bozzo, A.; Jackson, J.; Lutz, H.J.; do Couto, A.B.; Watts, P.; August, T.; Fougnie, B.; Bojkov, B.
2023
 | Volume: 12730
2023
DOI: 10.1117/12.2679703
Abstract:
The EUMETSAT Central Facility retrieves and disseminates several near-real time geophysical products from both geostationary and polar VIS/IR imagers.… The EUMETSAT Central Facility retrieves and disseminates several near-real time geophysical products from both geostationary and polar VIS/IR imagers. The primary scope of these missions is to serve numerical weather prediction (NWP), nowcasting and climate monitoring. In this contribution, we focus on the cloud and water vapour (WV) imaging products from the new generation EUMETSAT imagers i.e., the Flexible Combined Imager (FCI) on board of Meteosat Third Generation (MTG-I, launched in Dec 2022) and METimage on board EUMETSAT Polar System Second Generation (EPS-SG, expected 2024+). These instruments provide unprecedented spatial resolution (down to 500m at Nadir), temporal sampling (10min for the geostationary FCI), and wider spectral range (approximately 0.4-13µm) including WV (~0.9µm, 1.38µm, ~6.7µm, ~7.3µm), O2 A-band (0.762µm), and CO2 (~13.3µm) absorption channels. We present the retrieval and validation approach chosen for these products and the challenges presented by the near-real time operational processing. We explore, in particular, the expected improvements based on the enhanced instrument’s capabilities (i.e., more accurate cloud detection, layering, altitude and spatial inhomogeneity), while maintaining continuity with the legacy products from their predecessor satellites. In particular, the new ~0.9µm channel allows improved daytime estimates of WV amount near the surface. We show preliminary cloud and WV products retrieved from early FCI measurements, including their validation strategy against independent cloud observations from the ground-based ACTRIS network and humidly measurements from IGRA radiosondes. © 2023 SPIE. more
Atmosphere Climate Data Records EUM-Secr Method NWP-SAF

All-sky infrared radiance assimilation of a geostationary satellite in the Japan Meteorological Agency's global system

Author(s):
Okamoto, K.; Ishibashi, T.; Okabe, I.
Publication title: Quarterly Journal of the Royal Meteorological Society
2023
 | Volume: 149 | Issue: 755
2023
DOI: 10.1002/qj.4516
Abstract:
All-sky assimilation of infrared (IR) radiances has been developed for water vapor bands of the geostationary satellite Himawari-8 in the operational … All-sky assimilation of infrared (IR) radiances has been developed for water vapor bands of the geostationary satellite Himawari-8 in the operational global data assimilation system. Cloud-dependent quality control, bias correction, and observation error modeling are essential developments to effectively utilize the all-sky radiances (ASRs). ASR assimilation increases the assimilated number of observations by 2.8 times and improves the coverage relative to the traditional clear-sky radiance (CSR) assimilation. The additional observations better alleviate model dry biases in the middle and upper tropospheric humidity. ASR assimilation brings statistically significant improvements in the background (first guess) in humidity, temperature, and wind over the CSR assimilation. It also better improves short-range forecasts of the middle and upper tropospheric temperature and humidity up to day 3 in the Tropics. A mixed impact in the stratospheric temperature is under investigation. The impacts of various aspects of the ASR assimilation configuration are evaluated with sensitivity assimilation experiments. The interband correlation and cloud-dependent standard deviation of the observation error are crucial, whereas the cloud dependency of the correlation is not so important. Although ASRs at a single band were assimilated in many previous studies targeting severe weather using research-based regional assimilation systems due to decreasing independent information in the presence of clouds, they are distinctly inferior to not only ASRs at multiple bands but also CSRs at multiple bands in a global data assimilation system that contains fewer cloud-affected scenes. The cloud-dependent bias correction predictors are essential in the presence of observation-minus-background bias that increases with cloud effects. © 2023 Royal Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

A three-dimensional simulation and process analysis of tropospheric ozone depletion events (ODEs) during the springtime in the Arctic using CMAQ (Community Multiscale Air Quality Modeling System)

Author(s):
Cao, L.; Li, S.; Gu, Y.; Luo, Y.
Publication title: Atmospheric Chemistry and Physics
2023
 | Volume: 23 | Issue: 5
2023
DOI: 10.5194/acp-23-3363-2023
Abstract:
The tropospheric ozone depletion event (ODE), first observed at Barrow (now known as Utqiagvik), Alaska, is a phenomenon that frequently occurs during… The tropospheric ozone depletion event (ODE), first observed at Barrow (now known as Utqiagvik), Alaska, is a phenomenon that frequently occurs during the springtime in the Arctic. In this study, we performed a three-dimensional model study on ODEs occurring at Barrow and its surrounding areas between 28 March and 6 April 2019 using a 3-D multi-scale air quality model, CMAQ (Community Multiscale Air Quality Modeling System). Several ODEs observed at Barrow were captured, and two of them were thoroughly analyzed using the process analysis method to estimate contributions of horizontal transport, vertical transport, dry deposition, and the overall chemical process to the variations in ozone and bromine species during ODEs. We found that the ODE occurring between 30 and 31 March 2019 (referred to as ODE1) was primarily caused by the horizontal transport of low-ozone air from the Beaufort Sea to Barrow. The formation of this low-ozone air over the sea was largely attributed to a release of sea-salt aerosols from the Bering Strait under strong wind conditions, stemming from a cyclone generated on the Chukotka Peninsula. It was also discovered that the surface ozone dropped to less than 5 ppb over the Beaufort Sea, and the overall chemical process contributed up to 10 ppb to the ozone loss. Moreover, BrO over the sea reached a maximum of approximately 80 ppt. This low-ozone air over the sea was then horizontally transported to Barrow, leading to the occurrence of ODE1. Regarding another ODE on 2 April (ODE2), we found that its occurrence was also dominated by the horizontal transport from the sea, but under the control of an anticyclone. The termination of this ODE was mainly attributed to the replenishment of ozone-rich air from the free troposphere by a strong vertical transport. Copyright: © 2023 Le Cao et al. more
AC-SAF Application Atmosphere Climate Data Records

A sensor-agnostic albedo retrieval method forrealistic sea ice surfaces: model and validation

Author(s):
Zhou, YZ; Li, W; Chen, N; Fan, YZ; Stamnes, K
Publication title: CRYOSPHERE
2023
 | Volume: 17 | Issue: 2
2023
DOI: 10.5194/tc-17-1053-2023
Abstract:
A framework was established for remote sensing of sea ice albedo that integrates sea ice physics with high computational efficiency and that can be ap… A framework was established for remote sensing of sea ice albedo that integrates sea ice physics with high computational efficiency and that can be applied to optical sensors that measure appropriate radiance data. A scientific machine learning (SciML) approach was developed and trained on a large synthetic dataset (SD) constructed using a coupled atmosphere-surface radiative transfer model (RTM). The resulting RTM-SciML framework combines the RTM with a multi-layer artificial neural network SciML model. In contrast to the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43 albedo product, this framework does not depend on observations from multiple days and can be applied to single angular observations obtained under clear-sky conditions. Compared to the existing melt pond detection (MPD)-based approach for albedo retrieval, the RTM-SciML framework has the advantage of being applicable to a wide variety of cryosphere surfaces, both heterogeneous and homogeneous. Excellent agreement was found between the RTM-SciML albedo retrieval results and measurements collected from airplane campaigns. Assessment against pyranometer data (N=4144) yields RMSE = 0.094 for the shortwave albedo retrieval, while evaluation against albedometer data (N=1225) yields RMSE = 0.069, 0.143, and 0.085 for the broadband albedo in the visible, near-infrared, and shortwave spectral ranges, respectively. more
CM-SAF Climate Data Records Cryosphere Validation

A reduced latency regional gap-filling method for SMAP using random forest regression

Author(s):
Wang, Xiaoyi; Lü, Haishen; Crow, Wade T.; Corzo, Gerald; Zhu, Yonghua; Su, Jianbin; Zheng, Jingyao; Gou, Qiqi
Publication title: iScience
2023
 | Volume: 26 | Issue: 1
2023
DOI: 10.1016/j.isci.2022.105853
Abstract:
The soil moisture active/passive (SMAP) mission represents a significant advance in measuring soil moisture from satellites. However, its large spatia… The soil moisture active/passive (SMAP) mission represents a significant advance in measuring soil moisture from satellites. However, its large spatial-temporal data gaps limit the use of its values in near-real-time (NRT) applications. Considering this, the study uses NRT operational metadata (precipitation and skin temperature), together with some surface parameterization information, to feed into a random forest model to retrieve the missing values of the SMAP L3 soil moisture product. This practice was tested in filling the missing points for both SMAP descending (6:00 AM) and ascending orbits (6:00 PM) in a crop-dominated area from 2015 to 2019. The trained models with optimized hyper-parameters show the goodness of fit (R2 ≥ 0.86), and their resulting gap-filled estimates were compared against a range of competing products with in situ and triple collocation validation. This gap-filling scheme driven by low-latency data sources is first attempted to enhance NRT spatiotemporal support for SMAP L3 soil moisture. more
Application Climate Data Records H-SAF Land Validation

A New Sea Ice Concentration Retrieval Algorithm Based on Relationship Between AMSR2 89-GHz Polarization and Landsat 8 Observations

Author(s):
Tanaka, Y; Lu, JS
Publication title: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2023
 | Volume: 61
2023
DOI: 10.1109/TGRS.2023.3257401
Abstract:
A newly developed linear sea ice concentration (SIC) retrieval algorithm based on passive microwave Advanced Microwave Scanning Radiometer 2 (AMSR2) m… A newly developed linear sea ice concentration (SIC) retrieval algorithm based on passive microwave Advanced Microwave Scanning Radiometer 2 (AMSR2) measurements is proposed. SIC is retrieved by a linear function of the polarization ratio (PR) at 89 GHz (PR89) corrected for atmospheric influence. We use Landsat 8 SIC data to derive the coefficients of the linear function. Results using this linear algorithm are compared to those of ASI2 developed by Lu et al. (2018), which is a nonlinear 89-GHz algorithm with polarization difference (PD) at 89 GHz (PD89) that also includes a correction for atmospheric influence. Both algorithms are compared with independent SIC data derived from Landsat 8, ship-based observation, and synthetic aperture radar (SAR) and both tend to underestimate the ship-based and Landsat 8 SICs, particularly over thin ice. However, the proposed algorithm tends to provide results with lower bias and root-mean-square error (RMSE) for different ice categories. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

A monthly 1° resolution dataset of daytime cloud fraction over the Arctic during 2000–2020 based on multiple satellite products

Author(s):
Liu, Xinyan; He, Tao; Liang, Shunlin; Li, Ruibo; Xiao, Xiongxin; Ma, Rui; Ma, Yichuan
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 8
2023
DOI: 10.5194/essd-15-3641-2023
Abstract:
The low accuracy of satellite cloud fraction (CF) data over the Arctic seriously restricts the accurate assessment of the regional and global radiativ… The low accuracy of satellite cloud fraction (CF) data over the Arctic seriously restricts the accurate assessment of the regional and global radiative energy balance under a changing climate. Previous studies have reported that no individual satellite CF product could satisfy the needs of accuracy and spatiotemporal coverage simultaneously for long-term applications over the Arctic. Merging multiple CF products with complementary properties can provide an effective way to produce a spatiotemporally complete CF data record with higher accuracy. This study proposed a spatiotemporal statistical data fusion framework based on cumulative distribution function (CDF) matching and the Bayesian maximum entropy (BME) method to produce a synthetic 1∘ × 1∘ CF dataset in the Arctic during 2000–2020. The CDF matching was employed to remove the systematic biases among multiple passive sensor datasets through the constraint of using CF from an active sensor. The BME method was employed to combine adjusted satellite CF products to produce a spatiotemporally complete and accurate CF product. The advantages of the presented fusing framework are that it not only uses the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of passive sensor products benchmarked with reference data, i.e., active sensor product and ground-based observations. The inconsistencies of Arctic CF between passive sensor products and the reference data were reduced by about 10 %–20 % after fusing, with particularly noticeable improvements in the vicinity of Greenland. Compared with ground-based observations, R2 increased by about 0.20–0.48, and the root mean square error (RMSE) and bias reductions averaged about 6.09 % and 4.04 % for land regions, respectively; these metrics for ocean regions were about 0.05–0.31, 2.85 %, and 3.15 %, respectively. Compared with active sensor data, R2 increased by nearly 0.16, and RMSE and bias declined by about 3.77 % and 4.31 %, respectively, in land; meanwhile, improvements in ocean regions were about 0.3 for R2, 4.46 % for RMSE, and 3.92 % for bias. The results of the comparison with ERA5 and the Meteorological Research Institute – Atmospheric General Circulation model version 3.2S (MRI-AGCM3-2-S) climate model suggest an obvious improvement in the consistency between the satellite-observed CF and the reanalysis and model data after fusion. This serves as a promising indication that the fused CF results hold the potential to deliver reliable satellite observations for modeling and reanalysis data. Moreover, the fused product effectively supplements the temporal gaps of Advanced Very High Resolution Radiometer (AVHRR)-based products caused by satellite faults and the data missing from MODIS-based products prior to the launch of Aqua, and it extends the temporal range better than the active product; it addresses the spatial insufficiency of the active sensor data and the AVHRR-based products acquired at latitudes greater than 82.5∘ N. A continuous monthly 1∘ CF product covering the entire Arctic during 2000–2020 was generated and is freely available to the public at https://doi.org/10.5281/zenodo.7624605 (Liu and He, 2022). This is of great importance for reducing the uncertainty in the estimation of surface radiation parameters and thus helps researchers to better understand the Earth's energy imbalance. more
Atmosphere CM-SAF Climate Data Records Validation

A Machine Learning Approach to the Observation Operator for Satellite Radiance Data Assimilation

Author(s):
Liang, J.; Terasaki, K.; Miyoshi, T.
Publication title: Journal of the Meteorological Society of Japan
2023
 | Volume: 101 | Issue: 1
2023
DOI: 10.2151/jmsj.2023-005
Abstract:
The observation operator (OO) is essential in data assimilation (DA) to derive the model equivalent of observations from the model variables. In the s… The observation operator (OO) is essential in data assimilation (DA) to derive the model equivalent of observations from the model variables. In the satellite DA, the OO for satellite microwave brightness temperature (BT) is usually based on the radiative transfer model (RTM) with a bias correction procedure. To explore the possibility to obtain OO without using physically based RTM, this study applied machine learning (ML) as OO (MLOO) to assimilate BT from Advanced Microwave Sounding Unit-A (AMSU-A) channels 6 and 7 over oceans and channel 8 over both land and oceans under clear-sky conditions. We used a reference system, consisting of the nonhydrostatic icosahedral atmospheric model (NICAM) and the local ensemble transform Kalman filter (LETKF). The radiative transfer for TOVS (RTTOV) was implemented in the system as OO, combined with a separate bias correction procedure (RTTOV-OO). The DA experiment was performed for 1 month to assimilate conventional observations and BT using the reference system. Model forecasts from the experiment were paired with observations for training the ML models to obtain ML-OO. In addition, three DA experiments were conducted, which revealed that DA of the conventional observations and BT using ML-OO was slightly inferior, compared to that of RTTOV-OO, but it was better than the assimilation based on only conventional observations. Moreover, ML-OO treated bias internally, thereby simplifying the overall system framework. The proposed ML-OO has limitations due to (1) the inability to treat bias realistically when a significant change is present in the satellite characteristics, (2) inapplicability for many channels, (3) deteriorated performance, compared with that of RTTOV-OO with respect to accuracy and computational speed, and (4) physically based RTM is still used to train the ML-OO. Future studies can alleviate these drawbacks, thereby improving the proposed ML-OO. © The Author(s) 2023. more
Application Atmosphere NWP-SAF Software for CDR development

A global analysis of water storage variations from remotely sensed soil moisture and daily satellite gravimetry

Author(s):
Blank, D.; Eicker, A.; Jensen, L.; Güntner, A.
Publication title: Hydrology and Earth System Sciences
2023
 | Volume: 27 | Issue: 13
2023
DOI: 10.5194/hess-27-2413-2023
Abstract:
Water storage changes in the soil can be observed on a global scale with different types of satellite remote sensing. While active or passive microwav… Water storage changes in the soil can be observed on a global scale with different types of satellite remote sensing. While active or passive microwave sensors are limited to the upper few centimeters of the soil, satellite gravimetry can detect changes in the terrestrial water storage (TWS) in an integrative way, but it cannot distinguish between storage variations in different compartments or soil depths. Jointly analyzing both data types promises novel insights into the dynamics of subsurface water storage and of related hydrological processes. In this study, we investigate the global relationship of (1) several satellite soil moisture products and (2) non-standard daily TWS data from the Gravity Recovery and Climate Experiment/Follow-On (GRACE/GRACE-FO) satellite gravimetry missions on different timescales. The six soil moisture products analyzed in this study differ in the post-processing and the considered soil depth. Level 3 surface soil moisture data sets of the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) missions are compared to post-processed Level 4 data products (surface and root zone soil moisture) and the European Space Agency Climate Change Initiative (ESA CCI) multi-satellite product. On a common global 1 grid, we decompose all TWS and soil moisture data into seasonal to sub-monthly signal components and compare their spatial patterns and temporal variability. We find larger correlations between TWS and soil moisture for soil moisture products with deeper integration depths (root zone vs. surface layer) and for Level 4 data products. Even for high-pass filtered sub-monthly variations, significant correlations of up to 0.6 can be found in regions with a large, high-frequency storage variability. A time shift analysis of TWS versus soil moisture data reveals the differences in water storage dynamics with integration depth. © 2023 Daniel Blank et al. more
Application Climate Data Records H-SAF Land

A Comprehensive Methodology for the Statistical Characterization of Solar Irradiation: Application to the Case of Morocco

Author(s):
Bouhorma, Naoufal; Martín, Helena; de la Hoz, Jordi; Coronas, Sergio
Publication title: Applied Sciences
2023
 | Volume: 13 | Issue: 5
2023
DOI: 10.3390/app13053365
Abstract:
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, … The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the solar resource. In this study, a simple but comprehensive methodology for characterizing the solar resource for a project is presented. It is based on the determination of the best probability distribution function (PDF) of the solar irradiation for a specific location, assuming that the knowledge of statistical techniques may be more widely extended than other more complex mathematical methods. The presented methodology was tested on 23 cities across Morocco, given the high interest in solar investments in the country. As a result, a new database for solar irradiation values depending on historical data is provided for Morocco. The results show the great existing variety of PDFs for the solar irradiation data at the different months and cities, which demonstrates the need for undertaking a proper characterization of the irradiation when the assessment of solar energy projects is involved. When it is simply needed to embed the radiation uncertainty in the analysis, as is the case of the techno-economic valuation of solar energy assets, the presented methodology can reach this objective with much less complexity and less demanding input data. Moreover, its application is not limited to solar resource assessment, but can also be easily used in other fields, such as meteorology and climate change studies. more
Atmosphere CM-SAF Climate Data Records Validation

A comparative study of long-time series of global-scale albedo products

Author(s):
Mengyao, Li; Qiang, Liu; Ying, Qu
Publication title: International Journal of Digital Earth
2023
 | Volume: 16 | Issue: 1
2023
DOI: 10.1080/17538947.2023.2168773
Abstract:
Albedo is a key variable in the study of global or regional earth system models. High-quality albedo products are helpful for the accurate analysis an… Albedo is a key variable in the study of global or regional earth system models. High-quality albedo products are helpful for the accurate analysis and prediction of the Earth’s environment and climate. This paper analyzes the similarities and differences in several global-scale albedo products. The conclusions are as follows: (1) Ignoring the downward radiation weight leads to a maximum deviation of ±0.2 in the mean albedo in space and time; (2) Most of the products have good consistency at the global scale, especially after 2000, the consistency in the middle latitudes is better than that in the low latitudes and high latitudes; (3) Although there are obvious inter-annual variations and zonal differences in global mean albedo data from 2000 to 2020, the overall trend is not significant. The complex spatio-temporal variation of albedo requires high-quality remote sensing products to characterize its details. However, existing datasets do not show good agreement in these details, and more efforts are needed in this area. more
CM-SAF Climate Data Records Land Validation

A Bayesian machine learning method to explain the error characteristics of global-scale soil moisture products

Author(s):
Kim, Hyunglok; Crow, Wade T.; Wagner, Wolfgang; Li, Xiaojun; Lakshmi, Venkataraman
Publication title: Remote Sensing of Environment
2023
 | Volume: 296
2023
DOI: 10.1016/j.rse.2023.113718
Abstract:
Estimating accurate surface soil moisture (SM) dynamics from space, and knowing the error characteristics of these estimates, is of great importance f… Estimating accurate surface soil moisture (SM) dynamics from space, and knowing the error characteristics of these estimates, is of great importance for the application of satellite-based SM data throughout many Earth Science/Environmental Engineering disciplines. Here, we introduce the Bayesian inference approach to analyze the error characteristics of widely used passive and active microwave satellite-derived SM data sets, at different overpass times, acquired from the Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Advanced Scatterometer (ASCAT) missions. In particular, we apply Bayesian hierarchical modeling (BHM) and triple collocation analysis (TCA) to investigate the relative importance of different environmental factors and human activities on the accuracy of satellite-based data. To start, we compare the BHM-based sensitivity analysis method to the classic multiple regression models using a frequentist approach, which includes complete pooling and no-pooling models that have been widely used for sensitivity analysis in the field of remote sensing and demonstrate the BHM's adaptability and great potential for providing insight into sensitivity analysis that can be used by various remote sensing research communities. Next, we conduct an uncertainty analysis on BHM's model parameters using a full range of uncertainties to assess the association of various environmental factors with the accuracy of satellite-derived SM data. We focus on investigating human-induced error sources such as disturbed surface soil layers caused by irrigation activities on microwave satellite systems, naturally introduced error sources such as vegetation and soil organic matter, and errors related to the disregard of SM retrieval algorithmic assumptions - such as the thermal equilibrium passive microwave systems. Based on the BHM-based sensitivity analysis, we find that assessments of SM data quality with a single variable should be avoided, since numerous other factors simultaneously influence their quality. As such, this provides a useful framework for applying Bayesian theory to the investigation of the error characteristics of satellite-based SM data and other time-varying geophysical variables. more
Climate Data Records H-SAF Land Validation

A 16-year global climate data record of total column water vapour generated from OMI observations in the visible blue spectral range

Author(s):
Borger, C.; Beirle, S.; Wagner, T.
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 7
2023
DOI: 10.5194/essd-15-3023-2023
Abstract:
We present a long-term data set of 1×1 monthly mean total column water vapour (TCWV) based on global measurements of the Ozone Monitoring Instrument (… We present a long-term data set of 1×1 monthly mean total column water vapour (TCWV) based on global measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. In comparison to the retrieval algorithm of , several modifications and filters have been applied accounting for instrumental issues (such as OMI's "row anomaly") or the inferior quality of solar reference spectra. For instance, to overcome issues related to low-quality reference spectra, the daily solar irradiance spectrum is replaced by an annually varying mean earthshine radiance obtained in December over Antarctica. For the TCWV data set, we only consider measurements with an effective cloud fraction less than 20 %, an air mass factor (AMF) greater than 0.1, a snow- and ice-free ground pixel, and an OMI row that is not affected by the row anomaly over the complete time range of the data set. The individual TCWV measurements are then gridded to a regular 1×1 lattice, from which the monthly means are calculated. The investigation of sampling errors in the OMI TCWV data set shows that these are dominated by the clear-sky bias and cause on average deviations of around -10 %, which is consistent with the findings of previous studies. However, the spatiotemporal sampling errors and those due to the row-anomaly filter are negligible. In a comprehensive intercomparison study, we demonstrate that the OMI TCWV data set is in good agreement with the global reference data sets of ERA5 (fifth-generation ECMWF atmospheric reanalysis), RSS SSM/I (Remote Sensing Systems Special Sensor Microwave Imager), and CM SAF/CCI TCWV-global (COMBI): over ocean the orthogonal distance regressions indicate slopes close to unity with very small offsets and high coefficients of determination of around 0.96. However, over land, distinctive positive deviations of more than +10 kg m-2 are obtained for high TCWV values. These overestimations are mainly due to extreme overestimations of high TCWV values in the tropics, likely caused by uncertainties in the retrieval input data (surface albedo, cloud information) due to frequent cloud contamination in these regions. Similar results are found from intercomparisons with in situ radiosonde measurements from version 2 of the Integrated Global Radiosonde Archive (IGRA2) data set. Nevertheless, for TCWV values smaller than 25 kg m-2, the OMI TCWV data set shows very good agreement with the global reference data sets. Furthermore, a temporal stability analysis proves that the OMI TCWV data set is consistent with the temporal changes in the reference data sets and shows no significant deviation trends. As the TCWV retrieval can be easily applied to further satellite missions, additional TCWV data sets can be created from past missions, such as the Global Ozone Monitoring Experiment-1 (GOME-1) or the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY); under consideration of systematic differences (e.g. due to different observation times), these data sets can be combined with the OMI TCWV data set in order to create a data record that would cover a time span from 1995 to the present. Moreover, the TCWV retrieval will also work for all missions dedicated to NO2 in the future, such as Sentinel-5 on MetOp-SG. The Max Planck Institute for Chemistry (MPIC) OMI total column water vapour (TCWV) climate data record (CDR) is available at 10.5281/zenodo.7973889 . © 2023 Christian Borger et al. more
Atmosphere CM-SAF Climate Data Records Validation

Which gridded irradiance data is best for modelling photovoltaic power production in Germany?

Author(s):
Kenny, Darragh; Fiedler, Stephanie
Publication title: SOLAR ENERGY
2022
 | Volume: 232
2022
DOI: 10.1016/j.solener.2021.12.044
Abstract:
Model estimates of expected photovoltaic (PV) power production rely on accurate irradiance data. Reanalysis and satellite products freely provide irra… Model estimates of expected photovoltaic (PV) power production rely on accurate irradiance data. Reanalysis and satellite products freely provide irradiance data with a high temporal and spatial resolution including locations for which no ground-based measurements are available. We assess differences in such gridded irradiance data and quantify the subsequent bias propagation from individual radiation components to capacity factors in a contemporary PV model. PV power production is simulated based on four reanalysis (ERAS, COSMO-REA6, COSMO-REA6pp, COSMO-REA2) and three satellite products (CAMS, SARAH-2, CERES Syn1Deg). The results are compared against simulations using measurements from 30 weather stations of the German Weather Service. We compute metrics characterizing biases in seasonal and annual means, day-to-day variability and extremes in PV power. Our results highlight a bias of -1.4% (COSMO-REA6) to +8.2% (ERAS) in annual and spatial means of PV power production for Germany. No single data set is best in all metrics, although SARAH-2 and the postprocessed COSMO-REA6 data (COSMO-REA6pp) outperform the other products for many metrics. SARAH-2 yields good results in summer, but overestimates PV output in winter by 16% averaged across all stations. COSMO-REA6pp represents day-to-day variability in the PV power production of a simulated PV fleet best and has a particularly small bias of 0.5% in annual means. This is at least in parts due to compensating biases in local and seasonal means. Our results imply that gridded irradiance data should be used with caution for site assessments and ideally be complemented by local measurements. more
Atmosphere CM-SAF Climate Data Records Validation

Wind Energy Assessment for Renewable Energy Communities

Author(s):
Araveti, Sandeep; Quintana, Cristian Aguayo; Kairisa, Evita; Mutule, Anna; Adriazola, Juan Pablo Sepulveda; Sweeney, Conor; Carroll, Paula
Publication title: Wind
2022
 | Volume: 2 | Issue: 2
2022
DOI: 10.3390/wind2020018
Abstract:
Renewable and local energy communities are viewed as a key component to the success of the energy transition. In this paper, we estimate wind power po… Renewable and local energy communities are viewed as a key component to the success of the energy transition. In this paper, we estimate wind power potential for such communities. Acquiring the most accurate weather data is important to support decision-making. We identify the most reliable publicly available wind speed data and demonstrate a case study for typical energy community scenarios such as a single commercial turbine at coastal and inland locations in Ireland. We describe our assessment methodology to evaluate the quality of the wind source data by comparing it with meteorological observations. We make recommendations on which publicly available wind data sources, such as reanalysis data sources (MERRA-2, ERA-5), PVGIS, and NEWA are best suited to support Renewable Energy Communities interested in exploring the possibilities of renewable wind energy. ERA5 is deemed to be the most suitable wind data source for these locations, while an anomaly is noted in the NEWA data. more
Application Atmosphere CM-SAF Climate Data Records

Validation of weather reanalysis datasets and geospatial and techno-economic viability and potential assessment of concentrated solar power plants

Author(s):
Ahmad, Momina; Zeeshan, Muhammad
Publication title: Energy Conversion and Management
2022
 | Volume: 256
2022
DOI: 10.1016/j.enconman.2022.115366
Abstract:
Accelerating the decarbonization of power sector requires strategic planning and multi-aspectual feasibility analysis of renewable energy systems incl… Accelerating the decarbonization of power sector requires strategic planning and multi-aspectual feasibility analysis of renewable energy systems including, but not limited to, meteorological, land-use, techno-economic and environmental parameters. In this study, at first, the suitability of reanalysis datasets of Direct Normal Irradiance, air temperature, wind speed, relative humidity and air pressure was investigated at different timescales and locations over Pakistan. High correlation (R > 0.9) and low bias is found for Surface Solar Radiation Data records – Heliosat East, after preprocessing, among radiation datasets in consideration. Likewise, Modern-Era Retrospective analysis for Research and Applications version 2 datasets of temperature and air pressure strongly correlate with ground measurements whereas wind speed and relative humidity show peculiarity. Afterwards, resource maps from long-term timeseries are developed for each of the aforementioned parameters. In the second part, spatial feasibility and Analytical Hierarchy Process based site suitability is assessed utilizing site-specific meteorological, socio-economic and environmental parameters. Moreover, multi-parametric evaluation of techno-economic potential is performed using bias-corrected datasets. For technical potential, System Advisor Model’s Physical Trough Collector model is used for exclusively selected points. Additionally, cost of water usage is introduced in estimation of Levelized Cost of Electricity besides other parameters. Cumulative power capacity potential of 10,035 GW is identified for country, with net cost estimated below 0.096 USD/kWh. Nine sites are found to have generation potential greater than 1200 TWh/year, the individual capacity to fulfil total predicted energy demand of the country for year 2030. Around 6.5% of viable regions are found to be highly suitable for plant deployment. Land cover and lack of access to transmission network act as limiting barriers in installation of concentrated solar power plants at many potential sites across the country. more
Atmosphere CM-SAF Climate Data Records Validation

Validation of Photovoltaic Spectral Effects Derived From Satellite-Based Solar Irradiance Products

Author(s):
Pelland, Sophie; Gueymard, Christian A.
2022
2022
DOI: 10.1109/PVSC48317.2022.9938602
Abstract:
The Satellite Application Facility on Climate Monitoring (CM-SAF) Spectral Resolved Irradiance (SRI) and National Renewable Energy Laboratory (NREL) N… The Satellite Application Facility on Climate Monitoring (CM-SAF) Spectral Resolved Irradiance (SRI) and National Renewable Energy Laboratory (NREL) National Solar Radiation Database Spectral on Demand (NSRDB-S) satellite-based spectral irradiance products are tested here against benchmark data and models at seven ground stations: one in Spain for CM-SAF SRI and six in North America for NSRDB-S. Benchmarks include WISER spectroradiometers, spectra modeled from SolarSIM-G measurements and the SMARTS radiative code with two alternate input sources: AErosol RObotic NETwork (AERONET) and the ModernEra Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. The satellite products are tested in terms of their ability to estimate photovoltaic (PV) spectral effects for six PV module technologies. The spectra are also compared directly under clear-sky conditions. Both CM-SAF SRI and NSRDB-S outperformed the simple benchmark of neglecting spectral effects in terms of predicting instantaneous spectral mismatch factors, but only CM-SAF SRI did better at predicting the long-term spectral derate factors. The clear-sky results revealed systematic differences between NSRDB-S and benchmark spectra, likely due to the NSRDB-S treatment of aerosols. Meanwhile, the mean SMARTS spectra with AERONET and MERRA-2 inputs were in good agreement, showing promise for the use of MERRA-2 as input to clear-sky models. more
Atmosphere CM-SAF Climate Data Records Validation

Validation of Photovoltaic Spectral Effects Derived From Satellite-Based Solar Irradiance Products

Author(s):
Pelland, S; Gueymard, CA
Publication title: IEEE JOURNAL OF PHOTOVOLTAICS
2022
 | Volume: 12 | Issue: 6
2022
DOI: 10.1109/JPHOTOV.2022.3216501
Abstract:
The Satellite Application Facility on Climate Monitoring (CM-SAF) Spectral Resolved Irradiance (SRI) and National Renewable Energy Laboratory National… The Satellite Application Facility on Climate Monitoring (CM-SAF) Spectral Resolved Irradiance (SRI) and National Renewable Energy Laboratory National Solar Radiation Database Spectral on Demand (NSRDB-S) satellite-based spectral irradiance products are tested here against benchmark data and models at seven ground stations: one in Spain for CM-SAF SRI and six in North America for NSRDB-S. Benchmarks include WISER spectroradiometers, spectra modeled from SolarSIM-G measurements, the First Solar model of spectral mismatch factor (SMM), and the SMARTS radiative code with two alternate input sources: AErosol RObotic NETwork (AERONET) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. The satellite products are tested in terms of their ability to estimate photovoltaic (PV) spectral effects for six PV module technologies. Spectra are also compared directly. CM-SAF SRI generally outperforms First Solar and "no spectral effects " benchmarks, except for cadmium telluride modules. For NSRDB-S, predictions of long-term spectral derate factors show less skill than for instantaneous SMMs. Spectra comparisons reveal systematic differences between NSRDB-S and benchmark spectra, likely due to the NSRDB-S treatment of aerosols. Meanwhile, the mean SMARTS spectra with AERONET and MERRA-2 inputs are in good agreement, showing promise for the use of MERRA-2 as input to clear-sky models. more
Atmosphere CM-SAF Climate Data Records Validation

Tropical surface temperature response to vegetation cover changes and the role of drylands

Author(s):
Feldman, Andrew F.; Short Gianotti, Daniel J.; Dong, Jianzhi; Trigo, Isabel F.; Salvucci, Guido D.; Entekhabi, Dara
Publication title: Global Change Biology
2022
2022
DOI: 10.1111/gcb.16455
Abstract:
Vegetation cover creates competing effects on land surface temperature: it typically cools through enhancing energy dissipation and warms via decreasi… Vegetation cover creates competing effects on land surface temperature: it typically cools through enhancing energy dissipation and warms via decreasing surface albedo. Global vegetation has been previously found to overall net cool land surfaces with cooling contributions from temperate and tropical vegetation and warming contributions from boreal vegetation. Recent studies suggest that dryland vegetation across the tropics strongly contributes to this global net cooling feedback. However, observation-based vegetation-temperature interaction studies have been limited in the tropics, especially in their widespread drylands. Theoretical considerations also call into question the ability of dryland vegetation to strongly cool the surface under low water availability. Here, we use satellite observations to investigate how tropical vegetation cover influences the surface energy balance. We find that while increased vegetation cover would impart net cooling feedbacks across the tropics, net vegetal cooling effects are subdued in drylands. Using observations, we determine that dryland plants have less ability to cool the surface due to their cooling pathways being reduced by aridity, overall less efficient dissipation of turbulent energy, and their tendency to strongly increase solar radiation absorption. As a result, while proportional greening across the tropics would create an overall biophysical cooling feedback, dryland tropical vegetation reduces the overall tropical surface cooling magnitude by at least 14%, instead of enhancing cooling as suggested by previous global studies. more
Application Climate Data Records LSA-SAF Land

Tropical Continents Rainier Than Expected From Geometrical Constraints

Author(s):
Hohenegger, C.; Stevens, B.
Publication title: AGU Advances
2022
 | Volume: 3 | Issue: 4
2022
DOI: 10.1029/2021AV000636
Abstract:
Abundant rainfall over tropical land masses sustains rich ecosystems, a crucial source of biodiversity and sink of carbon. Here, we use two characteri… Abundant rainfall over tropical land masses sustains rich ecosystems, a crucial source of biodiversity and sink of carbon. Here, we use two characteristics of the observed tropical precipitation distribution, its distinctive zonal arrangement and its partitioning between land and ocean, to understand whether land conditions the climate to receive more than its fair share of precipitation as set by the land-sea distribution. Our analysis demonstrates that it is not possible to explain the tropics-wide partitioning of precipitation unless one assumes that rain is favored over land. Land receives more than its fair share of precipitation by broadening and letting the tropical rainbelts move more, effectively underpinning a negative feedback between surface water storage and precipitation. In contrast, rain is disfavored over land in climate models. Our findings suggest that the abundance of rainfall that shapes the terrestrial tropical biosphere is more robust to perturbations than models have suggested. © 2022. The Authors. more
Application Atmosphere CM-SAF Climate Data Records

Trends and Interdependence of Solar Radiation and Air Temperature—A Case Study from Germany

Author(s):
Behr, Hein Dieter
Publication title: Meteorology
2022
 | Volume: 1 | Issue: 4
2022
DOI: 10.3390/meteorology1040022
Abstract:
This study characterizes the spatiotemporal solar radiation and air temperature patterns and their dependence on the general atmospheric circulation c… This study characterizes the spatiotemporal solar radiation and air temperature patterns and their dependence on the general atmospheric circulation characterized by the North Atlantic Oscillation (NAO) Index in Germany from 1991 to 2015. Germany was selected as the study area because it can be subdivided into three climatologically different regions: the North German lowlands are under the maritime influence of the North and Baltic Seas. Several low mountain ranges dominate Germany’s center. In the south, the highest low mountain ranges and the Alps govern solar radiation and air temperature differently. Solar radiation and air temperature patterns were studied in the context of the NAO index using daily values from satellite and ground measurements. The most significant long-term solar radiation increase was observed in spring, mainly due to seasonal changes in cloud cover. Air temperature shows a noticeable increase in spring and autumn. Solar radiation and air temperature were significantly correlated in spring and autumn, with correlation coefficient values up to 0.93. In addition, a significant dependence of solar radiation and air temperature on the NAO index was revealed, with correlation coefficient values greater than 0.66. The results obtained are important not only for studies on the climate of the study area but also for photovoltaic system operators to design their systems. They need to be massively expanded to support Germany’s climate neutrality ambitions until 2045. more
Application Atmosphere CM-SAF Climate Data Records

The Stratospheric Diurnal Cycle in COSMIC GPS Radio Occultation Data: Scientific Applications

Author(s):
Leroy, S. S.; Gleisner, H.
Publication title: Earth and Space Science
2022
 | Volume: 9 | Issue: 3
2022
DOI: 10.1029/2021EA002011
Abstract:
The diurnal cycle throughout the stratosphere is analyzed by applying Bayesian interpolation to Constellation Observing System for Meteorology, Ionosp… The diurnal cycle throughout the stratosphere is analyzed by applying Bayesian interpolation to Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) Global Positioning System radio occultation (RO) data and three scientific applications of the analysis are introduced. First, the migrating thermal tides are analyzed with unprecedented accuracy and precision, with an uncertainty in the analysis of the vertically propagating tides ranging from 0.1 in the lower stratosphere to 0.6 K in the upper stratosphere for an individual month of RO data and with an uncertainty in a 10-year climatological diurnal cycle a factor of 10 less. Moreover, the midlatitude trapped tide is found to be smaller than what is produced by an atmospheric model and lags the model in phase, a likely consequence of a faulty parameterization of eddy diffusivity in the upper stratosphere. Second, a clear signal of solar cycle influence on the diurnal cycle is evident in this analysis, but whether the cause is the systematic bias of ionospheric residual associated with RO retrieval or it is an actual atmospheric phenomenon is less clear. Third, RO satellites and missions that obtain inadequate coverage of the diurnal cycle will be biased by under-sampling it, whether or not subsampling weather forecasts is used to removal sampling error. The analysis of the diurnal cycle in COSMIC RO data can be used to diagnose the systematic sampling error incurred by incomplete coverage of the diurnal cycle, which is of the order of 0.2 K for a Metop-based RO climatology. more
Application Atmosphere Climate Data Records ROM-SAF

The Wet Bias of RegCM4 Over Tibet Plateau in Summer Reduced by Adopting the 3D Sub-Grid Terrain Solar Radiative Effect Parameterization Scheme

Author(s):
Gu, C.; Huang, A.; Zhang, Y.; Yang, B.; Cai, S.; Xu, X.; Luo, J.; Wu, Y.
Publication title: Journal of Geophysical Research: Atmospheres
2022
 | Volume: 127 | Issue: 21
2022
DOI: 10.1029/2022JD037434
Abstract:
The Regional Climate Model Version 4 (RegCM4) with the conventional plane-parallel radiative transfer scheme severely overestimates the summer precipi… The Regional Climate Model Version 4 (RegCM4) with the conventional plane-parallel radiative transfer scheme severely overestimates the summer precipitation over the Tibetan Plateau (TP) due to the excessive surface heat source, which results from the poor representation of the sub-grid terrain-related radiation processes. To realistically describe the surface sub-grid radiation process in the RegCM4, a 3-dimensional sub-grid terrain solar radiative effect (3DSTSRE) parameterization scheme is implemented into the RegCM4 to improve the original plane-parallel radiative transfer scheme. Results show that adopting the 3DSTSRE scheme in RegCM4 can significantly reduce the summer (June–August) wet bias over the TP produced by the model with the plane-parallel radiative transfer scheme. Mechanism analysis indicates that the 3DSTSRE scheme largely improves the description of the TP surface energy balance in the RegCM4 by reducing the positive bias of downward surface solar radiation (DSSR). The reduced DSSR leads to the weakened surface heat source and cooler near-surface air over the TP. Consequently, the local atmospheric circulation adapts to the temperature field as the low-level anti-cyclonic (high-level cyclonic) anomaly over the TP. The adjustment of the temperature and wind field attenuates the water vapor transport, enhances the low-level atmospheric stability, inhibits the updraft motion, and eventually reduces the rainfall over TP. Although the 3DSTSRE improves the DSSR simulation only during daytime, the precipitation simulation is also improved at nighttime, which is fundamentally attributed to the maintenance of the cooled atmosphere throughout the daytime and nighttime. © 2022. American Geophysical Union. All Rights Reserved. more
Atmosphere CM-SAF Climate Data Records Validation

The Sky-Status Climatology of Greece: Emphasis on Sunshine Duration and Atmospheric Scattering

Author(s):
Kambezidis, Harry D.
Publication title: Applied Sciences
2022
 | Volume: 12 | Issue: 16
2022
DOI: 10.3390/app12167969
Abstract:
The aim of this work is the study of the sky conditions climatology over Greece based on the diffuse-fraction (kd) limits, for clear, kd ∈ [0, 0.26]; … The aim of this work is the study of the sky conditions climatology over Greece based on the diffuse-fraction (kd) limits, for clear, kd ∈ [0, 0.26]; intermediate, kd ∈ (0.26, 0.78); and overcast, kd ∈ (0.78, 1) skies. kd is, therefore, used here to characterise the sky conditions over a site. Its values are estimated from diffuse and global horizontal solar irradiances the typical meteorological years of 43 selected Greek sites. The kd values in each specific range are equivalent to sunshine durations (SSDs) under the particular sky conditions. Annual, seasonal, and intra-annual variations in SSDs are estimated with regression equations to fit their means. Clear skies comprise 33%, intermediate 40%, and overcast 27% of the time in a year. kd, as an atmospheric scattering index (ASI), shows dependence on the sites’ geographical latitude: best-fit lines mean ASIs are derived showing no trend, while overcast skies show a slight negative trend. A comparison of the clear-sky SSDs for four Greek sites from the Global Climate Data and one site from the Academy of Sciences of Moldova with those derived from kd shows a remarkable difference. A new methodology is developed that results in much smaller differences. Finally, maps of the annual SSDs and ASIs are derived for Greece. more
Atmosphere CM-SAF Climate Data Records

The Performance of ECMWF Ensemble Prediction System for European Extreme Fires: Portugal/Monchique in 2018

Author(s):
Durão, Rita; Alonso, Catarina; Gouveia, Célia
Publication title: Atmosphere
2022
 | Volume: 13 | Issue: 8
2022
DOI: 10.3390/atmos13081239
Abstract:
At the beginning of August 2018, Portugal experienced a severe heat episode over a few days that consequently increased the probability of wildfire ev… At the beginning of August 2018, Portugal experienced a severe heat episode over a few days that consequently increased the probability of wildfire events. Due to the advection of an anomalous very hot and dry air mass, severe fire-prone meteorological conditions were forecasted mainly over southern Portugal, in the Monchique region. Together with the significant fuel amount accumulated since the last extreme wildfire in August 2003, all the unfavorable conditions were set to drive a severe fire over this region. The Monchique fire started on 3 August 2018, being very hard to suppress and lasting for seven days, with a burnt area of 27,000 ha. Regarding the need to have operational early warning tools, this work aims to evaluate the reliability of fire probabilistic products, up to 72 h ahead, together with the use of fire radiative power products, as support tools in fire monitoring and resource activities. To accomplish this goal, we used the fire probabilistic products of the Ensemble Prediction System, provided by the Copernicus Atmosphere Monitoring Service. Among available fire danger rating systems, the Fire Weather Index and the Fine Fuels Moisture Code of the Canadian Forest Fire Weather Index System were selected to assess the meteorological fire danger. The assessment of the fire intensity was based on the Fire Radiative Energy released, considering the Fire Radiative Power, delivered in near real-time, by EUMETSAT Land Surface Analysis Satellite Applications Facility. The exceptional fire danger over southern Portugal that favors the ignition of the Monchique fire and its severity was essential driven by two important factors: (i) the anomalous fire weather danger, before and during the event; (ii) the accumulated fuel amount, since the last severe event occurred in 2003, over the region. Results show that the selected fire probabilistic products described the meteorological fire danger observed well, and the LSA-SAF products revealed the huge amount of fire energy emitted, in line with the difficulties faced by authorities to suppress the Monchique fire. more
Application Climate Data Records LSA-SAF Land

The evolution and dynamics of the Hunga Tonga-Hunga Ha'apai sulfate aerosol plume in the stratosphere

Author(s):
Legras, Bernard; Duchamp, Clair; Sellitto, Pasquale; Podglajen, Aurelien; Carboni, Elisa; Siddans, Richard; Groob, Jens-Uwe; Khaykin, Sergey; Ploeger, Felix
Publication title: Atmospheric Chemistry and Physics
2022
 | Volume: 22 | Issue: 22
2022
DOI: 10.5194/acp-22-14957-2022
Abstract:
We use a combination of spaceborne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022. The aerosol… We use a combination of spaceborne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022. The aerosol plume was initially formed of two clouds at 30 and 28gkm, mostly composed of submicron-sized sulfate particles, without ash, which is washed out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulfate aerosols and induced a descent of the plume to 24-26gkm over the first 3 weeks by radiative cooling. Whereas SO2 returned to background levels by the end of January, volcanic sulfates and water still persisted after 6 months, mainly confined between 35ggS and 20ggN until June due to the zonal symmetry of the summer stratospheric circulation at 22-26gkm. Sulfate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer-Dobson circulation. Sulfate aerosol optical depths derived from the IASI (Infrared Atmospheric Sounding Interferometer) infrared sounder show that during the first 2 months, the aerosol plume was not simply diluted and dispersed passively but rather organized in concentrated patches. Space-borne lidar winds suggest that those structures, generated by shear-induced instabilities, are associated with vorticity anomalies that may have enhanced the duration and impact of the plume. © Copyright: more
Application Atmosphere NWP-SAF Software for CDR development

The Effect of Error Non-Orthogonality on Triple Collocation Analyses

Author(s):
Vogelzang, Jur; Stoffelen, Ad; Verhoef, Anton
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 17
2022
DOI: 10.3390/rs14174268
Abstract:
Triple collocation analysis is an established technique for calculating the relative linear intercalibration coefficients and observation error varian… Triple collocation analysis is an established technique for calculating the relative linear intercalibration coefficients and observation error variances for physical quantities measured simultaneously in space and time by three different observation systems. A simple parameterized error model is used. It relies on a few assumptions, one of which is that the observation errors are independent of the magnitude of the observed quantities. This is referred to as error orthogonality. Using an ocean surface vector winds data set of 44,948 collocations, this study shows that the violation of error orthogonality does affect the calibration coefficients but has only a small second-order effect on the observation error variances of the calibrated data. more
Atmosphere Climate Data Records Method OSI-SAF

State of the Climate in 2021

Author(s):
Blunden, J.; Boyer, T.
Publication title: Bulletin of the American Meteorological Society
2022
 | Volume: 103 | Issue: 8
2022
DOI: 10.1175/2022BAMSStateoftheClimate.1
Abstract:
Abstract Editors note: For easy download the posted pdf of the State of the Climate in 2021 is a low-resolution file. A hig… Abstract Editors note: For easy download the posted pdf of the State of the Climate in 2021 is a low-resolution file. A high-resolution copy of the report is available by clicking here . Please be patient as it may take a few minutes for the high-resolution file to download. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Springtime nitrogen oxides and tropospheric ozone in Svalbard: results from the measurement station network

Author(s):
Dekhtyareva, Alena; Hermanson, Mark; Nikulina, Anna; Hermansen, Ove; Svendby, Tove; Holmen, Kim; Graversen, Rune Grand
Publication title: ATMOSPHERIC CHEMISTRY AND PHYSICS
2022
 | Volume: 22 | Issue: 17
2022
DOI: 10.5194/acp-22-11631-2022
Abstract:
Svalbard is a remote and scarcely populated Arctic archipelago and is considered to be mostly influenced by long-range-transported air pollution. Howe… Svalbard is a remote and scarcely populated Arctic archipelago and is considered to be mostly influenced by long-range-transported air pollution. However, there are also local emission sources such as coal and diesel power plants, snowmobiles and ships, but their influence on the background concentrations of trace gases has not been thoroughly assessed. This study is based on data of tropospheric ozone (O-3) and nitrogen oxides (NOx) collected in three main Svalbard settlements in spring 2017. In addition to these ground-based observations and radiosonde and O-3 sonde soundings, ERAS reanalysis and BrO satellite data have been applied in order to distinguish the impact of local and synoptic-scale conditions on the NOx and O-3 chemistry. The measurement campaign was divided into several sub-periods based on the prevailing large-scale weather regimes. The local wind direction at the stations depended on the large-scale conditions but was modified due to complex topography. The NOx concentration showed weak correlation for the different stations and depended strongly on the wind direction and atmospheric stability. Conversely, the O-3 concentration was highly correlated among the different measurement sites and was controlled by the long-range atmospheric transport to Svalbard. Lagrangian backward trajectories have been used to examine the origin and path of the air masses during the campaign. more
AC-SAF Application Atmosphere Climate Data Records

Spatiotemporal Modeling of the Electricity Production from Variable Renewable Energies in Germany

Author(s):
Lehneis, Reinhold; Manske, David; Schinkel, Björn; Thrän, Daniela
Publication title: ISPRS International Journal of Geo-Information
2022
 | Volume: 11 | Issue: 2
2022
DOI: 10.3390/ijgi11020090
Abstract:
In recent years, electricity production from wind turbines and photovoltaic systems has grown significantly in Germany. To determine the multiple impa… In recent years, electricity production from wind turbines and photovoltaic systems has grown significantly in Germany. To determine the multiple impacts of rising variable renewable energies on an increasingly decentralized power supply, spatially and temporally resolved data on the power generation are necessary or, at least, very helpful. Because of extensive data protection regulations in Germany, especially for smaller operators of renewable power plants, such detailed data are not freely accessible. In order to fill this information gap, simulation models employing publicly available plant and weather data can be used. The numerical simulations are performed for the year 2016 and consider an ensemble of almost 1.64 million variable renewable power plants in Germany. The obtained time series achieve a high agreement with measured feed-in patterns over the investigated year. Such disaggregated power generation data are very advantageous to analyze the energy transition in Germany on a spatiotemporally resolved scale. In addition, this study also derives meaningful key figures for such an analysis and presents the generated results as detailed maps at county level. To the best of our knowledge, such highly resolved electricity data of variable renewables for the entire German region have never been shown before. more
Application Atmosphere CM-SAF Climate Data Records

Solar Energy Powered Decentralized Smart-Grid for Sustainable Energy Supply in Low-Income Countries: Analysis Considering Climate Change Influences in Togo

Author(s):
Amega, Kokou; Laré, Yendoubé; Bhandari, Ramchandra; Moumouni, Yacouba; Egbendewe, Aklesso Y. G.; Sawadogo, Windmanagda; Madougou, Saidou
Publication title: Energies
2022
 | Volume: 15 | Issue: 24
2022
DOI: 10.3390/en15249532
Abstract:
A smart and decentralized electrical system, powered by grid-connected renewable energy (RE) with a reliable storage system, has the potential to chan… A smart and decentralized electrical system, powered by grid-connected renewable energy (RE) with a reliable storage system, has the potential to change the future socio-economic dynamics. Climate change may, however, affect the potential of RE and its related technologies. This study investigated the impact of climate change on photovoltaic cells’ temperature response and energy potential under two CO2 emission scenarios, RCP2.6 and 8.5, for the near future (2024–2040) and mid-century (2041–2065) in Togo. An integrated Regional Climate Model version 4 (RegCM4) from the CORDEX-CORE initiative datasets has been used as input. The latter platform recorded various weather variables, such as solar irradiance, air temperature, wind speed and direction, and relative humidity. Results showed that PV cells’ temperature would likely rise over all five regions in the country and may trigger a decline in the PV potential under RCP2.6 and 8.5. However, the magnitude of the induced change, caused by the changing climate, depended on two major factors: (1) the PV technology and (2) geographical position. Results also revealed that these dissimilarities were more pronounced under RCP8.5 with the amorphous technology. It was further found that, nationally, the average cell temperature would have risen by 1 °C and 1.82 °C under RCP2.6 and 8.5, in that order, during the 2024–2065 period for a-Si technology. Finally, the PV potential would likely decrease, on average, by 0.23% for RCP2.6 and 0.4% for RCP8.5 for a-Si technology. more
Application Atmosphere CM-SAF Climate Data Records

Solar Energy Potential on Surfaces with Various Inclination Modes in Saudi Arabia: Performance of an Isotropic and an Anisotropic Model

Author(s):
Farahat, Ashraf; Kambezidis, Harry D.; Almazroui, Mansour; Ramadan, Emad
Publication title: Applied Sciences
2022
 | Volume: 12 | Issue: 11
2022
DOI: 10.3390/app12115356
Abstract:
The present work investigated the performance of an isotropic (Liu–Jordan, L–J) and an anisotropic (Hay) model in assessing the solar energy potential… The present work investigated the performance of an isotropic (Liu–Jordan, L–J) and an anisotropic (Hay) model in assessing the solar energy potential of Saudi Arabia. Three types of solar collectors were considered: with southward fixed-tilt (mode (i)), with fixed-tilt tracking the Sun (mode (ii)), and with varying-tilt tracking the Sun (mode (iii)). This was the first time such a study was conducted for Saudi Arabia. The average annual difference between anisotropic (Hay) and isotropic (L–J) estimates is least ≈38 kWhm−2 year−1 over Saudi Arabia for mode (i), and therefore, the L–J model can be used effectively. In modes (ii) and (iii), the difference is greater (≈197 and ≈226 kWhm−2 year−1, respectively). It is, then, up to the solar energy engineer to decide which model is to be used, but it is recommended that the Hay model be utilised for mode-(iii) solar collectors. These results fill a research gap about the suitability of models in practice. An interesting feature for the ratio of the annual mean solar energy yield of Hay over L–J as function of the latitude, φ, and the ground albedo, ρr, is the formation of a “well” for 29° ≤ φ ≤ 31° and 1.15 ≤ ρr ≤ 1. more
Application Atmosphere CM-SAF Climate Data Records

Satellite Observations of Fire Activity in Relation to Biophysical Forcing Effect of Land Surface Temperature in Mediterranean Climate

Author(s):
Stoyanova, Julia S.; Georgiev, Christo G.; Neytchev, Plamen N.
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 7
2022
DOI: 10.3390/rs14071747
Abstract:
The present work is aimed at gaining more knowledge on the nature of the relation between land surface temperature (LST) as a biophysical parameter, w… The present work is aimed at gaining more knowledge on the nature of the relation between land surface temperature (LST) as a biophysical parameter, which is related to the coupled effect of the energy and water cycles, and fire activity over Bulgaria, in the Eastern Mediterranean. In the ecosystems of this area, prolonged droughts and heat waves create preconditions in the land surface state that increase the frequency and intensity of landscape fires. The relationships between the spatial–temporal variability of LST and fire activity modulated by land cover types and Soil Moisture Availability (SMA) are quantified. Long-term (2007–2018) datasets derived from geostationary MSG satellite observations are used: LST retrieved by the LSASAF LST product; fire activity assessed by the LSASAF FRP-Pixel product. All fires in the period of July–September occur in days associated with positive LST anomalies. Exponential regression models fit the link between LST monthly means, LST positive anomalies, LST-T2 (as a first proxy of sensible heat exchange with atmosphere), and FRP fire characteristics (number of detections; released energy FRP, MW) at high correlations. The values of biophysical drivers, at which the maximum FRP (MW) might be expected at the corresponding probability level, are identified. Results suggest that the biophysical index LST is sensitive to the changes in the dynamics of vegetation fire occurrence and severity. Dependences are found for forest, shrubs, and cultivated LCs, which indicate that satellite IR retrievals of radiative temperature is a reliable source of information for vegetation dryness and fire activity. more
Climate Data Records LSA-SAF Land Validation

Satellite passive microwave sea-ice concentration data set intercomparison using Landsat data

Author(s):
Kern, Stefan; Lavergne, Thomas; Pedersen, Leif Toudal; Tonboe, Rasmus; Be, Louisa; Meyer, Maybritt; Zeigermann, Luise
Publication title: CRYOSPHERE
2022
 | Volume: 16 | Issue: 1
2022
DOI: 10.5194/tc-16-349-2022
Abstract:
We report on results of an intercomparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite pa… We report on results of an intercomparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite passive microwave (PMW) observations. For this we use SIC estimated from > 350 images acquired in the visible-near-infrared frequency range by the joint National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) Landsat sensor during the years 2003-2011 and 2013-2015. Conditions covered are late winter/early spring in the Northern Hemisphere and from late winter through fall freeze-up in the Southern Hemisphere. Among the products investigated are the four products of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) and European Space Agency (ESA) Climate Change Initiative (CCI) algorithms SICCI-2 and OSI450. We stress the importance to consider intercomparison results across the entire SIC range instead of focusing on overall mean differences and to take into account known biases in PMW SIC products, e.g., for thin ice. We find superior linear agreement between PMW SIC and Landsat SIC for the 25 and the 50 km SICCI-2 products in both hemispheres. We discuss quantitatively various uncertainty sources of the evaluation carried out. First, depending on the number of mixed ocean-ice Landsat pixels classified erroneously as ice only, our Landsat SIC is found to be biased high. This applies to some of our Southern Hemisphere data, promotes an overly large fraction of Landsat SIC underestimation by PMW SIC products, and renders PMW SIC products overestimating Landsat SIC particularly problematic. Secondly, our main results are based on SIC data truncated to the range 0 % to 100 %. We demonstrate using non-truncated SIC values, where possible, can considerably improve linear agreement between PMW and Landsat SIC. Thirdly, we investigate the impact of filters often used to clean up the final products from spurious SIC over open water due to weather effects and along coastlines due to land spillover. Benefiting from the possibility to switch on or off certain filters in the SICCI-2 and OSI-450 products, we quantify the impact land spillover filtering can have on evaluation results as shown in this paper. more
Climate Data Records Cryosphere OSI-SAF Validation

Rotational drift in Antarctic sea ice: pronounced cyclonic features and differences between data products

Author(s):
de Jager, Wayne; Vichi, Marcello
Publication title: CRYOSPHERE
2022
 | Volume: 16 | Issue: 3
2022
DOI: 10.5194/tc-16-925-2022
Abstract:
Sea ice extent variability, a measure based on satellite-derived sea ice concentration measurements, has traditionally been used as an indicator to ev… Sea ice extent variability, a measure based on satellite-derived sea ice concentration measurements, has traditionally been used as an indicator to evaluate the impact of climate change on polar regions. However, concentration-based measurements of ice variability do not allow the discrimination of the relative contributions made by thermodynamic and dynamic processes, prompting the need to use sea ice drift products and develop methods to quantify changes in sea ice dynamics that would indicate trends in the ice characteristics. Here, we present a new method to automate the detection of rotational drift features in Antarctic sea ice from space at spatial and temporal scales comparable to that of polar weather. This analysis focusses on drift features in the Atlantic sector of the Southern Ocean in the period 2013-2020 using currently available satellite ice motion products from EUMETSAT OSI SAF. We observe a large discrepancy between cyclonic and anticyclonic drift features, with cyclonic features typically exhibiting larger drift intensity and spatial variability according to all products. The mean intensity of the 95th percentile of cyclonic features is 1.52.0 times larger for cyclonic features than anticyclonic features. The spatial variability of cyclonic features increased with intensity, indicating that the most intense cyclonic features are also the least homogenous. There is good agreement between products in detecting anticyclonic features; however, larger disagreement is evident for cyclonic features, with the merged product showing the most intense 95th percentile threshold and largest spatial variability, likely due to the more extended coverage of valid vorticity points. A time series analysis of the 95th percentile shows an abrupt intensification of cyclonic features from 2014-2017, which coincides with the record decline in Antarctic sea ice extent since winter of 2015. Our results indicate the need for systematic assessments of sea ice drift products against dedicated observational experiments in the weather-dominated Atlantic sector. Such information will allow us to confirm whether the detected increase in cyclonic vorticity is linked to rapidly changing atmospheric changes driven by sea ice dynamics and establish the measure of rotational sea ice drift as a potential indicator of weather-driven variability in Antarctic sea ice. more
Climate Data Records Cryosphere OSI-SAF Validation

Resilience of Cultural Heritage in Extreme Weather Conditions: The Case of the UNESCO Villa Romana del Casale Archaeological Site’s Response to the Apollo Medicane in October 2021

Author(s):
Gervasi, Osvaldo; Murgante, Beniamino; Misra, Sanjay; Rocha, Ana Maria A. C.; Garau, Chiara; Prestileo, Fernanda; Mascitelli, Alessandra; Meli, Guido; Petracca, Marco; Giorgi, Claudio; Melfi, Davide; Puca, Silvia; Dietrich, Stefano
2022
 | Volume: 13380
2022
DOI:
Application Climate Data Records H-SAF Land

Remote sensing of solar surface radiation-a reflection of concepts, applications and input data based on experience with the effective cloud albedo

Author(s):
Müller, R.; Pfeifroth, U.
Publication title: Atmospheric Measurement Techniques
2022
 | Volume: 15 | Issue: 5
2022
DOI: 10.5194/amt-15-1537-2022
Abstract:
Accurate solar surface irradiance (SSI) data are a prerequisite for efficient planning and operation of solar energy systems. Respective data are also… Accurate solar surface irradiance (SSI) data are a prerequisite for efficient planning and operation of solar energy systems. Respective data are also essential for climate monitoring and analysis. Satellite-based SSI has grown in importance over the last few decades. However, a retrieval method is needed to relate the measured radiances at the satellite to the solar surface irradiance. In a widespread classical approach, these radiances are used directly to derive the effective cloud albedo (CAL) as basis for the estimation of the solar surface irradiance. This approach was already introduced and discussed in the early 1980s. Various approaches are briefly discussed and analysed, including an overview of open questions and opportunities for improvement. Special emphasis is placed on the reflection of fundamental physical laws and atmospheric measurement techniques. In addition, atmospheric input data and key applications are briefly discussed. It is concluded that the well-established observation-based CAL approach is still an excellent choice for the retrieval of the cloud transmission. The coupling with lookup-table-based clear-sky models enables the estimation of solar surface irradiance with high accuracy and homogeneity. This could explain why, despite its age, the direct CAL approach is still used by key players in energy meteorology and the climate community. For the clear-sky input data, it is recommended to use ECMWF forecast and reanalysis data. © 2022 Richard Müller. more
Atmosphere CM-SAF Climate Data Records Validation

Regional Features of the Arctic Sea Ice Area Changes in 2000–2019 versus 1979–1999 Periods

Author(s):
Matveeva, Tatiana A.; Semenov, Vladimir A.
Publication title: Atmosphere
2022
 | Volume: 13 | Issue: 9
2022
DOI: 10.3390/atmos13091434
Abstract:
One of the most striking manifestations of ongoing climate change is a rapid shrinking of the Arctic sea ice area (SIA). An important feature of the o… One of the most striking manifestations of ongoing climate change is a rapid shrinking of the Arctic sea ice area (SIA). An important feature of the observed SIA loss is a nonlinear rate of a decline with an accelerated decrease in the 2000–2019 period relative to a more gradual decline in 1979–1999. In this study, we perform a quantitative assessment and comparison of the spatial-temporal SIA changes during these two periods. It was found that winter Arctic SIA loss is primarily associated with changes in the Barents Sea, where the SIA decline in 2000–2019 has accelerated more than three-fold in comparison with 1979–1999. In summer and autumn, rates of SIA decline in 2000–2019 increased most strongly in the Kara, Beaufort Seas, the Northwestern Passage, and inner Arctic Ocean. The amplitude of the SIA seasonal cycle has also increased in 2000–2019 in comparison with the earlier period, with the largest changes in the inner Arctic Ocean, the Kara, Laptev, East Siberian and Beaufort Seas in summer and in the Barents Sea in winter. The results may reflect a transition to a new dynamic state in the recent two decades with the triggering of positive feedbacks in the Arctic climate system. more
Application Climate Data Records Cryosphere OSI-SAF

Reducing Weather Influences on an 89 GHz Sea Ice Concentration Algorithm in the Arctic Using Retrievals From an Optimal Estimation Method

Author(s):
Lu, Junshen; Scarlat, Raul; Heygster, Georg; Spreen, Gunnar
Publication title: JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
2022
 | Volume: 127 | Issue: 9
2022
DOI: 10.1029/2019JC015912
Abstract:
Sea ice concentration (SIC) derived from 89 GHz data has up to four times finer spatial resolution compared to that from the widely used 19 and 37 GHz… Sea ice concentration (SIC) derived from 89 GHz data has up to four times finer spatial resolution compared to that from the widely used 19 and 37 GHz data. But it has lower accuracy due to the enhanced weather influences from water vapor, cloud liquid water (CLW), wind, and surface temperature. Here we improve a high-resolution SIC algorithm, called the ASI algorithm, based on the difference between vertical and horizontal polarization 89 GHz data, by correcting the observed data for these weather influences through a radiative transfer model and geophysical data retrieved by an optimal estimation method. The improved algorithm denoted ASI3, is developed for the Arctic based on the weather-corrected brightness temperatures and newly identified open water (80 K) and sea ice (14 K) tie-points. The most important component of this correction is the inclusion of CLW, the largest weather influence contributor. ASI3 results are evaluated over pure surface sites of 0% and 100% SICs under various weather conditions, showing a much lower average standard deviation (1.1%) than ASI (16.2%). ASI3 reduces weather patterns over pack ice resulting in more homogeneous retrievals but biased toward lower values. Comparison to Landsat imagery under clear-sky conditions shows that ASI3 results in better agreement with the Landsat SIC than ASI. The number of cases where real sea ice is falsely identified as open water is reduced by ASI3 due to its relaxed open-water mask and wider water/ice dynamic range. more
Climate Data Records Cryosphere OSI-SAF Validation

Recent trends in the agrometeorological climate variables over Scandinavia

Author(s):
Devasthale, Abhay; Carlund, Thomas; Karlsson, Karl-Göran
Publication title: Agricultural and Forest Meteorology
2022
 | Volume: 316
2022
DOI: 10.1016/j.agrformet.2022.108849
Abstract:
The impacts of global climate change in response to increasing greenhouse gasses are spatio-temporally heterogeneous and are observed in a number of e… The impacts of global climate change in response to increasing greenhouse gasses are spatio-temporally heterogeneous and are observed in a number of essential climate variables (ECVs). Among the ECVs that are highly relevant for the agriculture and forestry applications are clouds, precipitation and the incoming surface solar radiation (SIS). The past trends in these three agrometeorological ECVs and, more importantly, the co-variability among them can impact future agriculture and forestry policies and practices, their resilience and conservation. Therefore, using 37-year long climate data records spanning from 1982 to 2018 from the satellite- and surface based observing systems, we investigate the co-variability of trends in cloudiness, precipitation and SIS over Scandinavia during the summer months (April through September). The results reveal a complex nature of such co-variability among the trends in these three climate variables over Scandinavia. We report that the total cloudiness has decreased over much of Scandinavia. The decrease is most pronounced and statistically significant over southern Scandinavia in April, over the western coast in July and over much of northern Scandinavia in August. These decreasing trends are mainly due to reductions in the low and middle level clouds. The trends in all-sky incoming surface radiation are opposite in nature and broadly follow the spatio-temporal patterns of the trends in total cloudiness. The precipitation trends are heterogeneous, both spatially and temporally. The analysis of co-variability of trends reveals three distinct area-regimes that are relevant for assessing the changes in the land use and land cover. © 2022 Swedish Meteorological and Hydrological Institute more
Application Atmosphere CM-SAF Climate Data Records

Projected Changes in Solar PV and Wind Energy Potential over West Africa: An Analysis of CORDEX-CORE Simulations

Author(s):
Ndiaye, A; Moussa, MS; Dione, C; Sawadogo, W; Bliefernicht, J; Dungall, L; Kunstmann, H
Publication title: ENERGIES
2022
 | Volume: 15 | Issue: 24
2022
DOI: 10.3390/en15249602
Abstract:
Renewable energy development is growing fast and is expected to expand in the next decades in West Africa as a contribution to addressing the power de… Renewable energy development is growing fast and is expected to expand in the next decades in West Africa as a contribution to addressing the power demand and climate change mitigation. However, the future impacts of climate change on solar PV and the wind energy potential in the region are still unclear. This study investigates the expected future impacts of climate change on solar PV and wind energy potential over West Africa using an ensemble of three regional climate models (RCMs). Each RCM is driven by three global climate models (GCMs) from the new coordinated high-resolution output for regional evaluations (CORDEX-CORE) under the RCP8.5 scenario. Two projection periods were used: the near future (2021-2050) and the far future (2071-2100). For the model evaluation, reanalysis data from ERA5 and satellite-based climate data (SARAH-2) were used. The models and their ensemble mean (hereafter Mean) show acceptable performance for the simulations of the solar PV potential, the wind power density, and related variables with some biases. The Mean predicts a general decrease in the solar PV potential over the region of about -2% in the near future and -4% in the far future. The wind power density (WPD) is expected to increase by about 20% in the near future and 40% in the far future. The changes for solar PV potential seem to be consistent, although the intensity differs according to the RCM used. For the WPD, there are some discrepancies among the RCMs in terms of intensity and direction. This study can guide governments and policymakers in decision making for future solar and wind energy projects in the region. more
Application Atmosphere CM-SAF Climate Data Records

Predicted sea-ice loss will terminate Iceland's driftwood supply by 2060 CE

Author(s):
Kolar, Tomas; Rybnicek, Michal; Eggertsson, Olafur; Kirdyanov, Alexander; Cejka, Tomas; Cermak, Petr; Zid, Tomas; Vavrcik, Hanus; Buentgen, Ulf
Publication title: GLOBAL AND PLANETARY CHANGE
2022
 | Volume: 213
2022
DOI: 10.1016/j.gloplacha.2022.103834
Abstract:
Driftwood supply was a pivotal factor for the Norse expansion in medieval times and still exhibits an essential resource for Arctic settlements. The p… Driftwood supply was a pivotal factor for the Norse expansion in medieval times and still exhibits an essential resource for Arctic settlements. The physical causes and societal consequences of long-term changes in the distribution of Arctic driftwood are, however, poorly understood. Here, we use dendrochronology to reconstruct the age and origin of 289 driftwood samples that were collected at remote shorelines in northeast Iceland. Based on 240 reference tree-ring width chronologies from the boreal forest zone, and an overall provenance success of 73%, we show that most of the driftwood is pine and larch from the Yenisei catchment in central Siberia. Our study reveals an abrupt decline in the amount of driftwood reaching Iceland since the 1980s, which is corroborated by the experience of local farmers and fishers. Despite the direct and indirect effects of changes in both, logging activity across Siberia as well as Arctic Ocean currents, the predicted amount of sea-ice loss under anthropogenic global warming is likely to terminate Iceland's driftwood supply by 2060 CE. more
Application Climate Data Records Cryosphere OSI-SAF

Polar stratospheric nitric acid depletion surveyed from a decadal dataset of IASI total columns

Author(s):
Wespes, Catherine; Ronsmans, Gaetane; Clarisse, Lieven; Solomon, Susan; Hurtmans, Daniel; Clerbaux, Cathy; Coheur, Pierre-François
Publication title: Atmospheric Chemistry and Physics
2022
 | Volume: 22 | Issue: 16
2022
DOI: 10.5194/acp-22-10993-2022
Abstract:
Abstract. In this paper, we exploit the first 10-year data record (2008–2017) of nitric acid (HNO3) total columns measured by the IASI-A/MetOp infrare… Abstract. In this paper, we exploit the first 10-year data record (2008–2017) of nitric acid (HNO3) total columns measured by the IASI-A/MetOp infrared sounder, characterized by an exceptional daily sampling and a good vertical sensitivity in the lower-to-mid stratosphere (around 50 hPa), to monitor the relationship between the temperature decrease and the observed HNO3 loss that occurs each year in the Antarctic stratosphere during the polar night. Since the HNO3 depletion results from the formation of polar stratospheric clouds (PSCs), which trigger the development of the ozone (O3) hole, its continuous monitoring is of high importance. We verify here, from the 10-year time evolution of HNO3 together with temperature (taken from reanalysis at 50 hPa), the recurrence of specific regimes in the annual cycle of IASI HNO3 and identify (for each year) the day and the 50 hPa temperature (“drop temperature”) corresponding to the onset of strong HNO3 depletion in the Antarctic winter. Although the measured HNO3 total column does not allow for the uptake of HNO3 by different types of PSC particles along the vertical profile to be differentiated, an average drop temperature of 194.2 ± 3.8 K, close to the nitric acid trihydrate (NAT) existence threshold (∼ 195 K at 50 hPa), is found in the region of potential vorticity lower than −10 × 10−5 Km2kg-1s-1 (similar to the 70–90∘ S equivalent latitude region during winter). The spatial distribution and interannual variability of the drop temperature are investigated and discussed. This paper highlights the capability of the IASI sounder to monitor the evolution of polar stratospheric HNO3, a key player in the processes involved in the depletion of stratospheric O3. more
AC-SAF Application Atmosphere

Observations and Implications of Diurnal Climatology and Trends in Direct and Diffuse Solar Radiation Over China

Author(s):
Wang, Y.; Zhang, J.; Trentmann, J.; Fiedler, S.; Yang, S.; Sanchez-Lorenzo, A.; Tanaka, K.; Yuan, W.; Wild, M.
Publication title: Journal of Geophysical Research: Atmospheres
2022
 | Volume: 127 | Issue: 15
2022
DOI: 10.1029/2022JD036769
Abstract:
Solar radiation received at the Earth's surface (Rs) is comprised of two components, the direct radiation (Rd) and the diffuse radiation (Rf). Rd, the… Solar radiation received at the Earth's surface (Rs) is comprised of two components, the direct radiation (Rd) and the diffuse radiation (Rf). Rd, the direct beam from the sun, is essential for concentrated solar power generation. Rf, scattered by atmospheric molecules, aerosols, or cloud droplets, has a fertilization effect on plant photosynthesis. But how Rd and Rf change diurnally is largely unknown owing to the lack of long-term measurements. Taking advantage of 22 years of homogeneous hourly surface observations over China, this study documents the climatological means and evolutions in the diurnal cycles of Rd and Rf since 1993, with an emphasis on their implications for solar power and agricultural production. Over the solar energy resource region, we observe a loss of Rd which is relatively large near sunrise and sunset at low solar elevation angles when the sunrays pass through the atmosphere on a longer pathway. However, the concentrated Rd energy covering an average 10-hr period around noon during a day is relatively unaffected. Over the agricultural crop resource region, the large amounts of clouds and aerosols scattering more of the incoming light result in Rf taking the main proportion of Rs during the whole day. Rf resources and their fertilization effect in the main crop region of China further enhances since 1993 over almost all hours of the day. © 2022. American Geophysical Union. All Rights Reserved. more
Application Atmosphere CM-SAF Climate Data Records

Observed Landscape Responsiveness to Climate Forcing

Author(s):
Feldman, Andrew F.; Short Gianotti, Daniel J.; Trigo, Isabel F.; Salvucci, Guido D.; Entekhabi, Dara
Publication title: Water Resources Research
2022
 | Volume: 58 | Issue: 1
2022
DOI: 10.1029/2021WR030316
Abstract:
Climate variability and change shift environmental conditions on global land surfaces, creating uncertainties in predicting hydrologic flows, crop yie… Climate variability and change shift environmental conditions on global land surfaces, creating uncertainties in predicting hydrologic flows, crop yields, and land carbon uptake. Land surfaces can present varying degrees of inertia to atmospheric forcing variability (e.g., precipitation). This study asks: are regions with the most variable environmental forcing necessarily the regions with the largest land surface variability? Specifically, it seeks to determine why land surfaces show varying responsiveness to environmental forcing. The degree to which and the mechanisms for how landscapes modulate the forcing are evaluated using a decade-long satellite observation record of Africa's diverse climates. Surface responsiveness is quantified using intra-seasonal energy flux variability, based on the observed diurnal temperature amplitude. We map the responsiveness and analyze the underlying mechanisms over intra-seasonal timescales (especially interstorms). We show that, at a location, land surface responsiveness is dependent on the soil moisture distribution and the nonlinear relationship between energy fluxes and soil moisture. Land surfaces with greater responsiveness to climate are those with soil moisture distributions that span the threshold between evaporation regimes and spend most of their time in the water-limited regime. Consequently, surface responsiveness mechanisms drive land surface variability beyond high climatic variability. Since we find these results to hold from intra-seasonal to interannual timescales, we expect that these responsive regions will be most vulnerable to long-term shifts in climate forcing. The quantification of these phenomena and determination of their geographic distributions based on observations can help assess land surface models used to evaluate hydrologic consequences of climate change. more
Application Climate Data Records LSA-SAF Land

Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment

Author(s):
Vandenbussche, Sophie; Langerock, Bavo; Vigouroux, Corinne; Buschmann, Matthias; Deutscher, Nicholas M.; Feist, Dietrich G.; García, Omaira; Hannigan, James W.; Hase, Frank; Kivi, Rigel; Kumps, Nicolas; Makarova, Maria; Millet, Dylan B.; Morino, Isamu; Nagahama, Tomoo; Notholt, Justus; Ohyama, Hirofumi; Ortega, Ivan; Petri, Christof; Rettinger, Markus; Schneider, Matthias; Servais, Christian P.; Sha, Mahesh Kumar; Shiomi, Kei; Smale, Dan; Strong, Kimberly; Sussmann, Ralf; Té, Yao; Velazco, Voltaire A.; Vrekoussis, Mihalis; Warneke, Thorsten; Wells, Kelley C.; Wunch, Debra; Zhou, Minqiang; De Mazière, Martine
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 8
2022
DOI: 10.3390/rs14081810
Abstract:
Nitrous oxide (N2 O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and… Nitrous oxide (N2 O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N2 O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N2 O ν3 band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N2 O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N2 O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. more
Application Atmosphere NWP-SAF Software for CDR development

Observational Constraint on the Contribution of Surface Albedo Feedback to the Amplified Tibetan Plateau Surface Warming

Author(s):
Chen, Y.; Ji, D.; Moore, J.C.; Hu, J.; He, Y.
Publication title: Journal of Geophysical Research: Atmospheres
2022
 | Volume: 127 | Issue: 13
2022
DOI: 10.1029/2021JD036085
Abstract:
Surface albedo feedback (SAF) is one of the main causes of amplified warming over the Tibetan Plateau (TP). Several recent studies have used the lates… Surface albedo feedback (SAF) is one of the main causes of amplified warming over the Tibetan Plateau (TP). Several recent studies have used the latest reanalysis datasets to evaluate the SAF induced warming, but without fully considering the fidelity of the surface albedo change and surface downward solar radiation in the reanalysis datasets, which directly affect the amplitude of SAF induced warming. This study finds that the state-of-the-art reanalysis datasets (ERA-Interim, ERA5, MERRA, MERRA-2, JRA-55 and CRA) and climate models that participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibit varying biases compared with observations in both surface albedo change and surface downward solar radiation over the TP. The state-of-the-art reanalysis datasets present no obvious advantages over the lower resolution but less constrained CMIP6 multi-model ensemble in representing SAF related processes over the TP. The surface albedo change drives most of the spread in SAF induced warming. The reanalysis datasets and CMIP6 climate models reveal a significant linear relationship between surface albedo change and its contribution to surface temperature change over the TP. Using the observation constrained linear relationship and satellite surface albedo products, the spread of warming contribution due to SAF in reanalysis datasets and climate models is greatly reduced, the estimated TP warming due to SAF is in the range of 0.26–0.50 K in winter and 0.27–0.77 K in spring over recent decades. © 2022. American Geophysical Union. All Rights Reserved. more
CM-SAF Climate Data Records Land Validation

Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations

Author(s):
Gregory, William; Stroeve, Julienne; Tsamados, Michel
Publication title: CRYOSPHERE
2022
 | Volume: 16 | Issue: 5
2022
DOI: 10.5194/tc-16-1653-2022
Abstract:
The indirect effect of winter Arctic Oscillation (AO) events on the following summer Arctic sea ice extent suggests an inherent winter-to-summer mecha… The indirect effect of winter Arctic Oscillation (AO) events on the following summer Arctic sea ice extent suggests an inherent winter-to-summer mechanism for sea ice predictability. On the other hand, operational regional summer sea ice forecasts in a large number of coupled climate models show a considerable drop in predictive skill for forecasts initialised prior to the date of melt onset in spring, suggesting that some drivers of sea ice variability on longer timescales may not be well represented in these models. To this end, we introduce an unsupervised learning approach based on cluster analysis and complex networks to establish how well the latest generation of coupled climate models participating in phase 6 of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP6) are able to reflect the spatio-temporal patterns of variability in Northern Hemisphere winter sea-level pressure and Arctic summer sea ice concentration over the period 1979-2020, relative to ERA5 atmospheric reanalysis and satellite-derived sea ice observations, respectively. Two specific global metrics are introduced as ways to compare patterns of variability between models and observations/reanalysis: the adjusted Rand index - a method for comparing spatial patterns of variability - and a network distance metric - a method for comparing the degree of connectivity between two geographic regions. We find that CMIP6 models generally reflect the spatial pattern of variability in the AO relatively well, although they overestimate the magnitude of sea-level pressure variability over the north-western Pacific Ocean and underestimate the variability over northern Africa and southern Europe. They also underestimate the importance of regions such as the Beaufort, East Siberian, and Laptev seas in explaining pan-Arctic summer sea ice area variability, which we hypothesise is due to regional biases in sea ice thickness. Finally, observations show that historically, winter AO events (negatively) covary strongly with summer sea ice concentration in the eastern Pacific sector of the Arctic, although now under a thinning ice regime, both the eastern and western Pacific sectors exhibit similar behaviour. CMIP6 models however do not show this transition on average, which may hinder their ability to make skilful seasonal to inter-annual predictions of summer sea ice. more
Climate Data Records Cryosphere OSI-SAF Validation

Multi-Sensor Sea Surface Temperature Products from the Australian Bureau of Meteorology

Author(s):
Govekar, Pallavi Devidas; Griffin, Christopher; Beggs, Helen
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 15
2022
DOI: 10.3390/rs14153785
Abstract:
Sea surface temperature (SST) products that can resolve fine scale features, such as sub-mesoscale eddies, ocean fronts and coastal upwelling, are inc… Sea surface temperature (SST) products that can resolve fine scale features, such as sub-mesoscale eddies, ocean fronts and coastal upwelling, are increasingly in demand. In response to user requirements for gap-free, highest spatial resolution, best quality and highest accuracy SST data, the Australian Bureau of Meteorology (BoM) produces operational, real-time Multi-sensor SST level 3 products by compositing SST from Advanced Very-High-Resolution Radiometer (AVHRR) sensors on Meteorological Operational satellite (MetOp)-B and National Oceanic and Atmospheric Administration (NOAA) 18, along with SST from Visible Infrared Imaging Radiometer Suite (VIIRS) sensors on the Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA 20 polar-orbiting satellites for the Australian Integrated Marine Observing System (IMOS) project. Here we discuss our method to combine data from different sensors and present validation of the satellite-derived SST against in situ SST data. The Multi-sensor Level 3 Super Collated (L3S) SSTs exhibit significantly greater spatial coverage and improved accuracy compared with the pre-existing IMOS AVHRR-only L3S SSTs. When compared to the Geo Polar Blended level 4 analysis SST data over the Great Barrier Reef, Multi-sensor L3S SST differs by less than 1 °C while exhibiting a wider range of SSTs over the region. It shows more variability and restores small-scale features better than the Geo Polar Blended level 4 analysis SST data. The operational Multi-sensor L3S SST products are used as input for applications such as IMOS OceanCurrent and the BoM ReefTemp Next-Generation Coral Bleaching Nowcasting service and provide useful insight into the study of marine heatwaves and ocean upwelling in near-coastal regions. more
Climate Data Records OSI-SAF Ocean Validation

Monitoring global climate change using GNSS radio occultation

Author(s):
Gleisner, Hans; Ringer, Mark A.; Healy, Sean B.
Publication title: npj Climate and Atmospheric Science
2022
 | Volume: 5 | Issue: 1
2022
DOI: 10.1038/s41612-022-00229-7
Abstract:
Abstract The emerging signal of climate change is now clearly evident in Global Navigation Satellite System (GNSS) radio occultation (RO) … Abstract The emerging signal of climate change is now clearly evident in Global Navigation Satellite System (GNSS) radio occultation (RO) data, matching predictions made by climate models 15 years ago. The observed RO trends represent well-understood responses to global warming, in particular the widespread cooling of the lower stratosphere and warming of the troposphere. This demonstrates the value of RO measurements for climate monitoring, consistent with their information content and their use in both weather forecasting and atmospheric reanalyses. more
Application Atmosphere Climate Data Records ROM-SAF

Maximum energy yield of PV surfaces in France and Italy from climate based equations for optimum tilt at different azimuth angles

Author(s):
Memme, Samuele; Fossa, Marco
Publication title: Renewable Energy
2022
 | Volume: 200
2022
DOI: 10.1016/j.renene.2022.10.019
Abstract:
In the present paper, the problem of the determination of yearly maximum energy producibility in terms of optimum tilt angle for solar surfaces is add… In the present paper, the problem of the determination of yearly maximum energy producibility in terms of optimum tilt angle for solar surfaces is addressed with reference to 216 locations in France and Italy. Original correlations are proposed to calculate the optimal surface slope as a correction parameter to be applied to the local latitude angle. The correction factor formulas are based on local climate conditions and have been inferred from local monthly insolation data (12-year global and diffuse irradiance, PV-GIS-SARAH platform). An optimization problem is solved aimed at maximizing the yearly collectable energy by a sloped surface, in a range of azimuth values (from South Facing to East Facing), for all the selected locations. Different equation forms have been investigated and compact and accurate formulas have been developed able to provide the optimal tilt as a function of latitude, surface azimuth and clearness parameters. The accuracy of the proposed formulas resulted in a correlation coefficient with respect to the “exact” tilt angles higher than 0.93 for azimuth angles till 60°. Proposed formulas allow up to a 4% increase in collectable solar energy, corresponding, as an example, to a virtual increase in PV module efficiency from 21% to 21.8%. more
Application Atmosphere CM-SAF Climate Data Records

Meteorological Analysis of the 2021 Extreme Wildfires in Greece: Lessons Learned and Implications for Early Warning of the Potential for Pyroconvection

Author(s):
Giannaros, Theodore M.; Papavasileiou, Georgios; Lagouvardos, Konstantinos; Kotroni, Vassiliki; Dafis, Stavros; Karagiannidis, Athanasios; Dragozi, Eleni
Publication title: Atmosphere
2022
 | Volume: 13 | Issue: 3
2022
DOI: 10.3390/atmos13030475
Abstract:
The 2021 fire season in Greece was the worst of the past 13 years, resulting in more than 130,000 ha of burnt area, with about 70% consumed by five wi… The 2021 fire season in Greece was the worst of the past 13 years, resulting in more than 130,000 ha of burnt area, with about 70% consumed by five wildfires that ignited and spread in early August. Common to these wildfires was the occurrence of violent pyroconvection. This work presents a meteorological analysis of this outbreak of extreme pyroconvective wildfires. Our analysis shows that dry and warm antecedent weather preconditioned fuels in the fire-affected areas, creating a fire environment that alone could effectively support intense wildfire activity. Analysis of surface conditions revealed that the ignition and the most active spread of all wildfires coincided with the most adverse fire weather since the beginning of the fire season. Further, the atmospheric environment was conducive to violent pyroconvection, as atmospheric instability gradually increased amid the breakdown of an upper-air ridge ahead of an approaching long-wave trough. In summary, we highlight that the severity and extent of the 2021 Greek wildfires were not surprising considering the fire weather potential for the period when they ignited. Continuous monitoring of the large- and local-scale conditions that promote extreme fire behavior is imperative for improving Greece’s capacity for managing extreme wildfires. more
Application Climate Data Records LSA-SAF Land

Marine aerosol properties over the Southern Ocean in relation to the wintertime meteorological conditions

Author(s):
Thomas, Manu Anna; Devasthale, Abhay; Kahnert, Michael
Publication title: ATMOSPHERIC CHEMISTRY AND PHYSICS
2022
 | Volume: 22 | Issue: 1
2022
DOI: 10.5194/acp-22-119-2022
Abstract:
Given the vast expanse of oceans on our planet, marine aerosols (and sea salt in particular) play an important role in the climate system via multitud… Given the vast expanse of oceans on our planet, marine aerosols (and sea salt in particular) play an important role in the climate system via multitude of direct and indirect effects. The efficacy of their net impact, however, depends strongly on the local meteorological conditions that influence their physical, optical and chemical properties. Understanding the coupling between aerosol properties and meteorological conditions is therefore important. It has been historically difficult to statistically quantify this coupling over larger oceanic areas due to the lack of suitable observations, leading to large uncertainties in the representation of aerosol processes in climate models. Perhaps no other region shows higher uncertainties in the representation of marine aerosols and their effects than the Southern Ocean. During winter the Southern Ocean boundary layer is dominated by sea salt emissions. Here, using 10 years of austral winter period (June, July and August, 2007-2016) space-based aerosol profiling by CALIOP-CALIPSO in combination with meteorological reanalysis data, we investigated the sensitivity of marine aerosol properties over the Southern Ocean (40-65 degrees S) to various meteorological parameters, such as vertical relative humidity (RH), surface wind speed and sea surface temperature (SST) in terms of joint histograms. The sensitivity study is done for the climatological conditions and for the enhanced cyclonic and anticyclonic conditions in order to understand the impact of large-scale atmospheric circulation on the aerosol properties. We find a clear demarcation in the 532 nm aerosol backscatter and extinction at RH around 60 %, irrespective of the state of the atmosphere. The backscatter and extinction increase at higher relative humidity as a function of surface wind speed. This is mainly because of the water uptake by the wind-driven sea salt aerosols at high RH near the ocean surface resulting in an increase in size, which is confirmed by the decreased depolarization for the wet aerosols. An increase in aerosol backscatter and extinction is observed during the anticyclonic conditions compared to cyclonic conditions for the higher wind speeds and relative humidity, mainly due to aerosols being confined to the boundary layer, and their proximity to the ocean surface facilitates the growth of the particles. We further find a very weak dependency of aerosol backscatter on SSTs at lower wind speeds. However, when the winds are stronger than about 12 m s(-1), the backscattering coefficient generally increases with SST. When aerosol properties are investigated in terms of aerosol verticality and in relation to meteorological parameters, it is seen that the aerosol backscatter values in the free troposphere (pressure 60 %, low depolarization values are noticeable in the lower troposphere, which is an indication of the dominance of water-coated and mostly spherical sea salt particles. For RH < 60 %, there are instances when the aerosol depolarization increases in the boundary layer; this is more prominent in the mean and anticyclonic cases, which can be associated with the presence of drier aerosol particles. Based on the joint histograms investigated here, we provide third-degree polynomials to obtain aerosol extinction and backscatter as a function of wind speed and relative humidity. Additionally, backscattering coefficient is also expressed jointly in terms of wind speed and sea surface temperature. Furthermore, depolarization is expressed as a function of relative humidity. These fitting functions would be useful to test and improve the parameterizations of sea salt aerosols in the climate models. We also note some limitations of our study. For example, interpreting the verticality of aerosol properties (especially depolarization) in relation to the meteorological conditions in the free and upper troposphere (pressure more
Application Atmosphere Climate Data Records Cryosphere OSI-SAF

Mapping long-term and high-resolution global gridded photosynthetically active radiation using the ISCCP H-series cloud product and reanalysis data

Author(s):
Tang, Wenjun; Qin, Jun; Yang, Kun; Jiang, Yaozhi; Pan, Weihao
Publication title: EARTH SYSTEM SCIENCE DATA
2022
 | Volume: 14 | Issue: 4
2022
DOI: 10.5194/essd-14-2007-2022
Abstract:
Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fiel… Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fields. In this study, we produced a 35-year (1984-2018) high-resolution (3 h, 10 km) global gridded PAR dataset using an effective physical-based model. The main inputs of the model were the latest International Satellite Cloud Climatology Project (ISCCP) H-series cloud products, MERRA-2 aerosol data, ERA5 surface routine variables, and MODIS and CLARRA-2 albedo products. Our gridded PAR product was evaluated against surface observations measured at 7 experimental stations of the SURFace RADiation budget network (SURFRAD), 42 experimental stations of the National Ecological Observatory Network (NEON), and 38 experimental stations of the Chinese Ecosystem Research Network (CERN). Instantaneous PAR was validated against SURFRAD and NEON data; mean bias errors (MBE) and root mean square errors (RMSE) were, on average 5.8 and 44.9 W m(-2), respectively, and the correlation coefficient (R) was 0.94 at the 10 km scale. When upscaled to 30 km, the errors were markedly reduced. Daily PAR was validated against SURFRAD, NEON, and CERN data, and the RMSEs were 13.2, 13.1, and 19.6 W m(-2,) respectively, at the 10 km scale. The RMSEs were slightly reduced when upscaled to 30 km. Compared with the well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES), our PAR product was found to be a more accurate dataset with higher resolution. This new dataset is now available at https://doi.org/10.11888/RemoteSen.tpdc.271909 (Tang, 2021). more
Application CM-SAF Climate Data Records Land

Introducing New Metrics for the Atmospheric Pressure Adjustment to Thermal Structures at the Ocean Surface

Author(s):
Meroni, Agostino N.; Desbiolles, Fabien; Pasquero, Claudia
Publication title: JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
2022
 | Volume: 127 | Issue: 16
2022
DOI: 10.1029/2021JD035968
Abstract:
Thermal structures at the sea surface are known to affect the overlying atmospheric dynamics over various spatio-temporal scales, from hourly and sub-… Thermal structures at the sea surface are known to affect the overlying atmospheric dynamics over various spatio-temporal scales, from hourly and sub-kilometric to annual and O(1,000 km). The relevant mechanisms at play are generally identified by means of correlation coefficients (in space or time) or by linear regression analysis using appropriate couples of variables. For fine spatial scales, where sea surface temperature (SST) gradients get stronger, the advection might disrupt these correlations and, thus, mask the action of such mechanisms, just because of the chosen metrics. For example, at the oceanic sub-mesoscale, around 1-10 km and hourly time scales, the standard metrics used to identify the pressure adjustment mechanism (that involves the Laplacian of sea surface temperature, SST, and the wind divergence) may suffer from this issue, even for weak wind conditions. By exploiting high-resolution realistic numerical simulations with ad hoc SST forcing fields, we introduce some new metrics to evaluate the action of the pressure adjustment atmospheric response to the surface oceanic thermal structures. It is found that the most skillful metrics is based on the wind divergence and the SST second spatial derivative evaluated in the across direction of a locally defined background wind field. more
Application Atmosphere Climate Data Records OSI-SAF Ocean

Integrating Reanalysis and Satellite Cloud Information to Estimate Surface Downward Long-Wave Radiation

Author(s):
Lopes, Francis M.; Dutra, Emanuel; Trigo, Isabel F.
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 7
2022
DOI: 10.3390/rs14071704
Abstract:
The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with impli… The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m−2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model. more
Climate Data Records LSA-SAF Land Validation

Impact of the revisit frequency on cloud climatology for CALIPSO, EarthCARE, Aeolus, and ICESat-2 satellite lidar missions

Author(s):
Kotarba, A.Z.
Publication title: Atmospheric Measurement Techniques
2022
 | Volume: 15 | Issue: 14
2022
DOI: 10.5194/amt-15-4307-2022
Abstract:
Space profiling lidars offer a unique insight into cloud properties in Earth's atmosphere and are considered the most reliable source of total (column… Space profiling lidars offer a unique insight into cloud properties in Earth's atmosphere and are considered the most reliable source of total (column-integrated) cloud amount (CA), and true (geometrical) cloud top height (CTH). However, lidar-based cloud climatologies suffer from infrequent sampling: every n days, and only along the ground track. This study therefore evaluated four lidar missions, namely CALIPSO (revisit every n = 16 d), EarthCARE (n = 25), Aeolus (n = 7), and ICESat-2 (n = 91), to test the hypothesis that each mission provides accurate data on CA and CTH. CA/CTH values for a hypothetical daily revisit mission were used as reference (data simulated with Meteosat 15 min cloud observations, assumed to be a proxy for ground truth). Our results demonstrated that this hypothesis is invalid, unless individual lidar transects are averaged over an area 10×10 in longitude and latitude (or larger). If this is not the case, the required accuracy of 1 % (for CA) or 150 m (for CTH) cannot be met, either for a single-year annual or monthly mean, or for a >10 year climatology. A CALIPSO-focused test demonstrated that the annual mean CA estimate is very sensitive to infrequent sampling, and that this factor alone can result in 14 % or 7 % average uncertainty with 1 or 2.5 resolution data, respectively. Consequently, applications that use gridded lidar data should consider calculating confidence intervals, or a similar measure of uncertainty. Our results suggest that CALIPSO, and its follow-on mission EarthCARE, are very likely to produce consistent cloud records despite the difference in sampling frequency. © 2022 The Author(s). more
Atmosphere CM-SAF Climate Data Records Validation

Ice water path retrievals from Meteosat-9 using quantile regression neural networks

Author(s):
Amell, A.; Eriksson, P.; Pfreundschuh, S.
Publication title: Atmospheric Measurement Techniques
2022
 | Volume: 15 | Issue: 19
2022
DOI: 10.5194/amt-15-5701-2022
Abstract:
The relationship between geostationary radiances and ice water path (IWP) is complex, and traditional retrieval approaches are not optimal. This work … The relationship between geostationary radiances and ice water path (IWP) is complex, and traditional retrieval approaches are not optimal. This work applies machine learning to improve the IWP retrieval from Meteosat-9 observations, with a focus on low latitudes, training the models against retrievals based on CloudSat. Advantages of machine learning include avoiding explicit physical assumptions on the data, an efficient use of information from all channels, and easily leveraging spatial information. Thermal infrared (IR) retrievals are used as input to achieve a performance independent of the solar angle. They are compared with retrievals including solar reflectances as well as a subset of IR channels for compatibility with historical sensors. The retrievals are accomplished with quantile regression neural networks. This network type provides case-specific uncertainty estimates, compatible with non-Gaussian errors, and is flexible enough to be applied to different network architectures. Spatial information is incorporated into the network through a convolutional neural network (CNN) architecture. This choice outperforms architectures that only work pixelwise. In fact, the CNN shows a good retrieval performance by using only IR channels. This makes it possible to compute diurnal cycles, a problem that CloudSat cannot resolve due to its limited temporal and spatial sampling. These retrievals compare favourably with IWP retrievals in CLAAS, a dataset based on a traditional approach. These results highlight the possibilities to overcome limitations from physics-based approaches using machine learning while providing efficient, probabilistic IWP retrieval methods. Moreover, they suggest this first work can be extended to higher latitudes as well as that geostationary data can be considered as a complement to the upcoming Ice Cloud Imager mission, for example, to bridge the gap in temporal sampling with respect to space-based radars. Copyright © 2022 Adrià Amell et al. more
Atmosphere CM-SAF Climate Data Records Validation

Historical and projected climatic trends in KwaZulu-Natal: 1950–2100

Author(s):
Jury, M.R.
Publication title: Water SA
2022
 | Volume: 48 | Issue: 4
2022
DOI: 10.17159/wsa/2022.v48.i4.3991
Abstract:
The climate of KwaZulu-Natal, South Africa, is evaluated for historical and projected trends in the period 1950–2100. This region lies next to the war… The climate of KwaZulu-Natal, South Africa, is evaluated for historical and projected trends in the period 1950–2100. This region lies next to the warm Indian Ocean and experiences an alternating airflow imposed by subtropical easterly and mid-latitude westerly wind belts. Multi-year wet spells have diminished since 2001 and potential evaporation deficits have spread from the Tugela Valley. Although coastal vegetation is greening and sea temperatures in the Agulhas Current are warming (&gt;0.02·yr−1), there are fewer rain days and less cloud cover. Tropical winds across southern Africa have turned toward Madagascar, re-directing moisture and convection away from KwaZulu-Natal in recent decades. Long-range coupled model projections of monthly rainfall display weak trends over the 21st century (−0.01 mm·day−1·yr −1) which are overshadowed by multi-year fluctuations (r2 = 0.04). In contrast, drying trends in potential evaporation are significant (r2 = 0.41). Forecasts of seasonal dry spells could mitigate climate change impacts in south-eastern Africa. © The Author(s) Published under a Creati. more
Application Atmosphere CM-SAF Climate Data Records

High-resolution satellite products improve hydrological modeling in northern Italy

Author(s):
Alfieri, Lorenzo; Avanzi, Francesco; Delogu, Fabio; Gabellani, Simone; Bruno, Giulia; Campo, Lorenzo; Libertino, Andrea; Massari, Christian; Tarpanelli, Angelica; Rains, Dominik; Miralles, Diego G.; Quast, Raphael; Vreugdenhil, Mariette; Wu, Huan; Brocca, Luca
Publication title: Hydrology and Earth System Sciences
2022
 | Volume: 26 | Issue: 14
2022
DOI: 10.5194/hess-26-3921-2022
Abstract:
Abstract. Satellite-based Earth observations (EO) are an accurate and reliable data source for atmospheric and environmental science. Their increasing… Abstract. Satellite-based Earth observations (EO) are an accurate and reliable data source for atmospheric and environmental science. Their increasing spatial and temporal resolutions, as well as the seamless availability over ungauged regions, make them appealing for hydrological modeling. This work shows recent advances in the use of high-resolution satellite-based EO data in hydrological modeling. In a set of six experiments, the distributed hydrological model Continuum is set up for the Po River basin (Italy) and forced, in turn, by satellite precipitation and evaporation, while satellite-derived soil moisture (SM) and snow depths are ingested into the model structure through a data-assimilation scheme. Further, satellite-based estimates of precipitation, evaporation, and river discharge are used for hydrological model calibration, and results are compared with those based on ground observations. Despite the high density of conventional ground measurements and the strong human influence in the focus region, all satellite products show strong potential for operational hydrological applications, with skillful estimates of river discharge throughout the model domain. Satellite-based evaporation and snow depths marginally improve (by 2 % and 4 %) the mean Kling–Gupta efficiency (KGE) at 27 river gauges, compared to a baseline simulation (KGEmean= 0.51) forced by high-quality conventional data. Precipitation has the largest impact on the model output, though the satellite data on average shows poorer skills compared to conventional data. Interestingly, a model calibration heavily relying on satellite data, as opposed to conventional data, provides a skillful reconstruction of river discharges, paving the way to fully satellite-driven hydrological applications. more
Atmosphere Climate Data Records H-SAF Land Validation

High-resolution electricity generation model demonstrates suitability of high-altitude floating solar power

Author(s):
Eyring, Nicholas; Kittner, Noah
Publication title: ISCIENCE
2022
 | Volume: 25 | Issue: 6
2022
DOI: 10.1016/j.isci.2022.104394
Abstract:
This paper develops a meteorological site selection algorithm to quantify the electricity generation potential of floating solar design configurations… This paper develops a meteorological site selection algorithm to quantify the electricity generation potential of floating solar design configurations on alpine water bodies in Switzerland. Using European power market demand patterns, we estimate the technical and economic potential of 82 prospective high-altitude floating solar sites co-located with existing Swiss hydropower. We demonstrate that the amount of solar energy radiating from high-altitude Swiss water bodies could meet total national electricity demand while significantly reducing carbon emissions and addressing seasonal supply/demand deficits. We construct a global map overlaying sites on each continent where high-altitude floating solar could provide low-carbon, land-sparing electricity. Our results present a compelling motivation to develop alpine floating solar installations. However, significant innovations are still needed to couple floating solar with existing hydropower operations or low-cost energy storage. As the industry matures, high-altitude floating solar technology could become a high-value, low-carbon electricity source. more
Application Atmosphere CM-SAF Climate Data Records

High-resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River basin as a case study

Author(s):
Filippucci, Paolo; Brocca, Luca; Quast, Raphael; Ciabatta, Luca; Saltalippi, Carla; Wagner, Wolfgang; Tarpanelli, Angelica
Publication title: Hydrology and Earth System Sciences
2022
 | Volume: 26 | Issue: 9
2022
DOI: 10.5194/hess-26-2481-2022
Abstract:
Abstract. The use of satellite sensors to infer rainfall measurements has become a widely used practice in recent years, but their spatial resolution … Abstract. The use of satellite sensors to infer rainfall measurements has become a widely used practice in recent years, but their spatial resolution usually exceeds 10 km, due to technological limitations. This poses an important constraint on its use for applications such as water resource management, index insurance evaluation or hydrological models, which require more and more detailed information. In this work, the algorithm SM2RAIN (Soil Moisture to Rain) for rainfall estimation is applied to two soil moisture products over the Po River basin: a high-resolution soil moisture product derived from Sentinel-1, named S1-RT1, characterized by 1 km spatial resolution (500 m spacing), and a 25 (12.5 km spacing) product derived from ASCAT, resampled to the same grid as S1-RT1. In order to overcome the need for calibration and to allow for its global application, a parameterized version of SM2RAIN algorithm was adopted along with the standard one. The capabilities in estimating rainfall of each obtained product were then compared, to assess both the parameterized SM2RAIN performances and the added value of Sentinel-1 high spatial resolution. The results show that good estimates of rainfall are obtainable from Sentinel-1 when considering aggregation time steps greater than 1 d, since the low temporal resolution of this sensor (from 1.5 to 4 d over Europe) prevents its application for infer daily rainfall. On average, the ASCAT-derived rainfall product performs better than S1-RT1, even if the performances are equally good when 30 d accumulated rainfall is considered (resulting in a mean Pearson correlation for the parameterized SM2RAIN product of 0.74 and 0.73, respectively). Notwithstanding this, the products obtained from Sentinel-1 outperform those from ASCAT in specific areas, like in valleys inside mountain regions and most of the plains, confirming the added value of the high-spatial-resolution information in obtaining spatially detailed rainfall. Finally, the performances of the parameterized products are similar to those obtained with the calibrated SM2RAIN algorithm, confirming the reliability of the parameterized algorithm for rainfall estimation in this area and fostering the possibility to apply SM2RAIN worldwide, even without the availability of a rainfall benchmark product. more
Atmosphere Climate Data Records H-SAF Method

Ground-based validation of the MetOp-A and MetOp-B GOME-2 OClO measurements

Author(s):
Pinardi, Gaia; Van Roozendael, Michel; Hendrick, François; Richter, Andreas; Valks, Pieter; Alwarda, Ramina; Bognar, Kristof; Frieß, Udo; Granville, José; Gu, Myojeong; Johnston, Paul; Prados-Roman, Cristina; Querel, Richard; Strong, Kimberly; Wagner, Thomas; Wittrock, Folkard; Yela Gonzalez, Margarita
Publication title: Atmospheric Measurement Techniques
2022
 | Volume: 15 | Issue: 11
2022
DOI: 10.5194/amt-15-3439-2022
Abstract:
Abstract. This paper reports on ground-based validation of the atmospheric OClO data record produced within the framework of EUMETSAT's Satellite Appl… Abstract. This paper reports on ground-based validation of the atmospheric OClO data record produced within the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC SAF) using the Global Ozone Monitoring Experiment (GOME)-2A and GOME-2B instrument measurements, covering the 2007–2016 and 2013–2016 periods, respectively. OClO slant column densities are compared to correlative measurements collected from nine Zenith-Scattered-Light Differential Optical Absorption Spectroscopy (ZSL-DOAS) instruments from the Network for the Detection of Atmospheric Composition Change (NDACC) distributed in both the Arctic and Antarctic. Sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings. On this basis, we infer systematic uncertainties of about 25 % (i.e., about 3.75×1013 molec. cm−2) between the different ground-based data analyses, reaching total uncertainties ranging from about 26 % to 33 % for the different stations (i.e., around 4 to 5×1013 molec. cm−2). Time series at the different sites show good agreement between satellite and ground-based data for both the inter-annual variability and the overall OClO seasonal behavior. GOME-2A results are found to be noisier than those of GOME-2B, especially after 2011, probably due to instrumental degradation effects. Daily linear regression analysis for OClO-activated periods yield correlation coefficients of 0.8 for GOME-2A and 0.87 for GOME-2B, with slopes with respect to the ground-based data ensemble of 0.64 and 0.72, respectively. Satellite minus ground-based offsets are within 8×1013 molec. cm−2, with some differences between GOME-2A and GOME-2B depending on the station. Overall, considering all the stations, a median offset of about -2.2×1013 molec. cm−2 is found for both GOME-2 instruments. more
AC-SAF Atmosphere Climate Data Records Validation

Global and Regional Evaluation of the CERES Edition-4A Surface Solar Radiation and Its Uncertainty Quantification

Author(s):
Zhang, Ke; Zhao, Long; Tang, Wenjun; Yang, Kun; Wang, Jing
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2022
 | Volume: 15
2022
DOI: 10.1109/JSTARS.2022.3164471
Abstract:
This article presents a comprehensive evaluation of the 2000–2018 Clouds and Earth's Radiant Energy System Synoptic 1° Ed4A (CERES SYN1deg Edition 4A)… This article presents a comprehensive evaluation of the 2000–2018 Clouds and Earth's Radiant Energy System Synoptic 1° Ed4A (CERES SYN1deg Edition 4A) surface solar radiation (SSR) product. In particular, the global assessment is conducted over different temporal scales (i.e., hourly, daily, and monthly-average) with special attention given to the impact of clouds, and a regional evaluation is further implemented over the Mainland of China (MC) using SSR measurements from a denser observational network provided by the China Meteorological Administration. Evaluation across all valid station-grid pairs yields mixed performance with |MBE|≤2.8 (6.2) W m−2, RMSE≤89.5 (31.6) W m−2, and R≥0.95 (0.93) over the globe (MC) for different temporal scales, and the monthly CERES SSR, with RMSE≤20 W m−2, is found to hold promise for global numerical weather prediction and climate monitoring. In addition, CERES is found to generally underestimate and overestimate SSR over land and ocean, respectively. Comparison between year-round and cloudy-season suggests that the presence of clouds may potentially impact the SSR retrievals, especially at the hourly temporal scales, with an increase in RMSE values larger than 10 W m−2 for most stations. Further investigation of subgrid heterogeneity suggests that most in situ SSR measurements can reasonably represent the 1° grid average except for some stations with specific geographic deployments, which may raise significant spatial representativeness issues and, therefore, need to be used with great caution. more
Application Atmosphere CM-SAF Climate Data Records Validation

Filling gaps of black-sky surface albedo of the Arctic sea ice using gradient boosting and brightness temperature data

Author(s):
Jaaskelainen, Emmihenna; Manninen, Terhikki; Hakkarainen, Janne; Tamminen, Johanna
Publication title: INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
2022
 | Volume: 107
2022
DOI: 10.1016/j.jag.2022.102701
Abstract:
Surface albedo is a necessary parameter for climate studies and modeling. There is a need for a full spatial coverage of albedo data, but clouds and h… Surface albedo is a necessary parameter for climate studies and modeling. There is a need for a full spatial coverage of albedo data, but clouds and high solar zenith angle cause missing values to the optical satellite products, especially around the polar areas. Therefore, our motivation is to develop gap filling models. For that purpose, we will apply monthly gradient boosting (GB) based models to the Arctic sea ice area of the 34 years long albedo time series of the Satellite Application Facility on Climate Monitoring (CM SAF) project. We demonstrate the ability of the GB models to accurately fill missing data using albedo monthly mean, brightness temperature, and sea ice concentration as model inputs. Monthly GB models produce the most unbiased, precise, and robust estimates when compared to alternative estimates presented, such as monthly mean albedo values or estimates from monthly linear regression (LR) models. The mean relative differences between GB based estimates and original pentad values vary from-20% to 20% with RMSE being 0.048, compared to relative differences varying from-20% to over 60% with RMSE varying from 0.054 to 0.074 between other estimates and original pentad values. Pixelwise mean differences and standard deviations (std) over the whole Arctic sea ice area show that GB based estimates are more accurate (mean differences from-0.02 to 0.02) and more precise (std from 0.02 to 0.08) than other estimates (mean differences varying between-0.05 to over 0.05, and std varying from around 0.03 to over 0.1). Also, albedo of the melting sea ice is predicted better by the GB model, with negligible mean differences, compared to the LR model. Based on these results, we show that GB method is a useful technique to fill missing data, and the brightness temperature and sea ice concentration are useful additional model input data sources. more
Application CM-SAF Climate Data Records Cryosphere Land OSI-SAF

Exploring Ecosystem Functioning in Spain with Gross and Net Primary Production Time Series

Author(s):
Martínez, Beatriz; Sánchez-Ruiz, Sergio; Campos-Taberner, Manuel; García-Haro, F. Javier; Gilabert, M. Amparo
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 6
2022
DOI: 10.3390/rs14061310
Abstract:
The main objective of this study is to analyze the spatial and temporal variability of gross and net primary production (GPP and NPP) in Peninsular Sp… The main objective of this study is to analyze the spatial and temporal variability of gross and net primary production (GPP and NPP) in Peninsular Spain across 15 years (2004–2018) and determine the relationship of those carbon fluxes with precipitation and air temperature. A time series study of daily GPP, NPP, mean air temperature, and monthly standardized precipitation index (SPI) at 1 km spatial resolution is conducted to analyze the ecosystem status and adaptation to changing environmental conditions. Spatial variability is analyzed for vegetation and specific forest types. Temporal dynamics are examined from a multiresolution analysis based on the wavelet transform (MRA-WT). The Mann–Kendall nonparametric test and the Theil–Sen slope are applied to quantify the magnitude and direction of trends (increasing or decreasing) within the time series. The use of MRA-WT to extract the annual component from daily series increased the number of statistically significant pixels. At pixel level, larger significant GPP and NPP negative changes (p-value < 0.1) are observed, especially in southeastern Spain, eastern Mediterranean coastland, and central Spain. At annual temporal scale, forests and irrigated crops are estimated to have twice the GPP of rainfed crops, shrublands, grasslands, and sparse vegetation. Within forest types, deciduous broadleaved trees exhibited the greatest annual NPP, followed by evergreen broadleaved and evergreen needle-leaved tree species. Carbon fluxes trends were correlated with precipitation. The temporal analysis based on daily TS demonstrated an increase of accuracy in the trend estimates since more significant pixels were obtained as compared to annual resolution studies (72% as to only 17%). more
Application Climate Data Records LSA-SAF Land

Evaluation of Sea Ice Radiative Forcing according to Surface Albedo and Skin Temperature over the Arctic from 1982–2015

Author(s):
Seong, Noh-Hun; Kim, Hyun-Cheol; Choi, Sungwon; Jin, Donghyun; Jung, Daeseong; Sim, Suyoung; Woo, Jongho; Kim, Nayeon; Seo, Minji; Lee, Kyeong-Sang; Han, Kyung-Soo
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 11
2022
DOI: 10.3390/rs14112512
Abstract:
Rapid warming of the Arctic has resulted in widespread sea ice loss. Sea ice radiative forcing (SIRF) is the instantaneous perturbation of Earth’s rad… Rapid warming of the Arctic has resulted in widespread sea ice loss. Sea ice radiative forcing (SIRF) is the instantaneous perturbation of Earth’s radiation at the top of the atmosphere (TOA) caused by sea ice. Previous studies focused only on the role of albedo on SIRF. Skin temperature is also closely related to sea ice changes and is one of the main factors in Arctic amplification. In this study, we estimated SIRF considering both surface albedo and skin temperature using radiative kernels. The annual average net-SIRF, which consists of the sum of albedo-SIRF and temperature-SIRF, was calculated as −54.57 ± 3.84 W/m2 for the period 1982–2015. In the net-SIRF calculation, albedo-SIRF and temperature-SIRF made similar contributions. However, the albedo-SIRF changed over the study period by 0.12 ± 0.07 W/m2 per year, while the temperature-SIRF changed by 0.22 ± 0.07 W/m2 per year. The SIRFs for each factor had different patterns depending on the season and region. In summer, rapid changes in the albedo-SIRF occurred in the Kara and Barents regions. In winter, only a temperature-SIRF was observed, and there was little difference between regions compared to the variations in albedo-SIRF. Based on the results of the study, it was concluded that the overall temperature-SIRF is changing more rapidly than the albedo-SIRF. This study indicates that skin temperatures may have a greater impact on the Arctic than albedo in terms of sea ice surface changes. more
Application CM-SAF Climate Data Records Cryosphere

Evaluating the impact of a time-evolving constellation on multi-platform satellite based daily precipitation estimates

Author(s):
Oliveira, Rômulo Augusto Jucá; Roca, Rémy; Finkensieper, Stephan; Cloché, Sophie; Schröder, Marc
Publication title: Atmospheric Research
2022
 | Volume: 279
2022
DOI: 10.1016/j.atmosres.2022.106414
Abstract:
Satellite based precipitation climate data records (CDRs) have recently emerged and provide new observational sources to characterize of the changing … Satellite based precipitation climate data records (CDRs) have recently emerged and provide new observational sources to characterize of the changing nature of global precipitation. These products rely on the use of passive microwave instruments. At the daily scale, these CDRs are prone to performance sensitivity resulting from the availability of microwave observations. As the configuration of the microwave sounders and imagers fleet evolves over time, adding new satellites and instruments or losing old platforms, the climate-oriented performances of the CDRs are likely impacted. In this study, this effect is quantified using a prototype constellation-based quasi-global precipitation product algorithm and data-denial experiments. The constellation change has a small impact of the long-term average climatology both in terms of mean and distribution recalling the resilience of the climatology of such a multi-platform product to the fluctuations of the amount of available input data. The interannual variability on the other hand is more impacted. More large rainfall amounts are relatively more perturbed than the lower rain daily accumulation with anomalies up to 30% for some configurations. The method to correct for the artefact is detailed and while some aspects of the computations are product-specific, the major outcome of this study should apply to various similar products as well. © 2022 The Authors more
Atmosphere CM-SAF Climate Data Records Method

Estimation of the effects of aerosol optical properties on peatland production in Rzecin, Poland

Author(s):
Harenda, Kamila M.; Markowicz, Krzysztof M.; Poczta, Patryk; Stachlewska, Iwona S.; Bojanowski, Jedrzej S.; Czernecki, Bartosz; McArthur, Alasdair; Schuetemeyer, Dirk; Chojnicki, Bogdan H.
Publication title: AGRICULTURAL AND FOREST METEOROLOGY
2022
 | Volume: 316
2022
DOI: 10.1016/j.agrformet.2022.108861
Abstract:
The productivity response of a peatland ecosystem in Rzecin, Poland, was determined based on varying aerosols abundant in the atmosphere. The study wa… The productivity response of a peatland ecosystem in Rzecin, Poland, was determined based on varying aerosols abundant in the atmosphere. The study was done with the use of a multifactorial model that combined atmo-spheric and ecosystem modules to describe plant photosynthetic ability from different perspectives. The Gross Ecosystem Production (GEP) was calculated for real conditions in the period from May through September 2018. This period was characterized by increased air temperatures (1.4 degrees C) and reduced precipitation (17%), when compared to the long-term averages (1981-2010) for the studied area. This also aligned with expected direction of climate change predictions. The multifactorial model was used to show that, depending on the aerosol situation, the peatland ecosystem may react with an average increase (8.2%) as well as a decrease (6%) of GEP during the growing season. The modification of atmospheric optical properties with a step-wise increase of aerosol optical depth (AOD) by 0.2 in relation to the observed value, resulted in the increase of diffuse index (DI) of circa 22%, the decrease of photosynthetic photon flux density (PPFD) of circa 5%, and the increase of GEP of circa 8% in each of analyzed months. The GEP reduction (6%) was caused by the absorbing aerosol presence characterized by low single scattering albedo (SSA) value. Consequently, the CO2 uptake process could not be maximized by the ecosystem due to reduced levels of available radiant energy. Conversely, the effect of non-absorbing aerosols presence on GEP was found negligible due to the continental clean aerosols prevailed in the air mass during the study period. Generally speaking, the estimation of the effects of aerosol optical properties on Rzecin peatland production shows that more absorbing aerosols occurrence cause GEP reduction while AOD rise results in GEP gain. more
Application Atmosphere CM-SAF Climate Data Records

Estimation of refractivity uncertainties and vertical error correlations in collocated radio occultations, radiosondes, and model forecasts

Author(s):
Nielsen, Johannes K.; Gleisner, Hans; Syndergaard, Stig; Lauritsen, Kent B.
Publication title: ATMOSPHERIC MEASUREMENT TECHNIQUES
2022
 | Volume: 15 | Issue: 20
2022
DOI: 10.5194/amt-15-6243-2022
Abstract:
Random uncertainties and vertical error correlations are estimated for three independent data sets. The three collocated data sets are (1) refractivit… Random uncertainties and vertical error correlations are estimated for three independent data sets. The three collocated data sets are (1) refractivity profiles of radio occultation measurements retrieved from the Metop-A and B and COSMIC-1 missions, (2) refractivity derived from GRUAN-processed RS92 sondes, and (3) refractivity profiles derived from ERAS forecast fields. The analysis is performed using a generalization of the so-called three-cornered hat method to include off-diagonal elements such that full error covariance matrices can be calculated. The impacts from various sources of representativeness error on the uncertainty estimates are analysed. The estimated refractivity uncertainties of radio occultations, radiosondes, and model data are stated with reference to the vertical representation of refractivity in these data sets. The existing theoretical estimates of radio occultation uncertainty are confirmed in the middle and upper troposphere and lower stratosphere, and only little dependence on latitude is found in that region. In the lower troposphere, refractivity uncertainty decreases with latitude. These findings have implications for both retrieval of tropospheric humidity from radio occultations and for assimilation of radio occultation data in numerical weather prediction models and reanalyses. more
Atmosphere Climate Data Records Method ROM-SAF

Discretization of Sea Ice Dynamics in the Tangent Plane to the Sphere by a CD-Grid-Type Finite Element

Author(s):
Mehlmann, Carolin; Gutjahr, Oliver
Publication title: Journal of Advances in Modeling Earth Systems
2022
 | Volume: 14 | Issue: 12
2022
DOI: 10.1029/2022MS003010
Abstract:
We present a new discretization of sea ice dynamics on the sphere. The approach describes sea ice motion in tangent planes to the sphere. On each tria… We present a new discretization of sea ice dynamics on the sphere. The approach describes sea ice motion in tangent planes to the sphere. On each triangle of the mesh, the ice dynamics are discretized in a local coordinate system using a CD-grid-like non-conforming finite element method. The development allows a straightforward coupling to the C-grid like ocean model in Icosahedral Non-hydrostatic-Ocean model, which uses the same infrastructure as the sea ice module. Using a series of test examples, we demonstrate that the non-conforming finite element discretization provides a stable realization of large-scale sea ice dynamics on the sphere. A comparison with observation shows that we can simulate typical drift patterns with the new numerical realization of the sea ice dynamics. © 2022 The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union. more
Climate Data Records Cryosphere OSI-SAF Validation

CRAAS: A European Cloud Regime dAtAset Based on the CLAAS-2.1 Climate Data Record

Author(s):
Tzallas, Vasileios; Hünerbein, Anja; Stengel, Martin; Meirink, Jan Fokke; Benas, Nikos; Trentmann, Jörg; Macke, Andreas
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 21
2022
DOI: 10.3390/rs14215548
Abstract:
Given the important role of clouds in our planet’s climate system, it is crucial to further improve our understanding of their governing processes as … Given the important role of clouds in our planet’s climate system, it is crucial to further improve our understanding of their governing processes as well as the resulting spatio-temporal variability of their properties. This co-variability of different cloud optical properties is adequately represented through the well-established concept of cloud regimes. The focus of the present study lies on the creation of a cloud regime dataset over Europe, named “Cloud Regime dAtAset based on the CLAAS-2.1 climate data record” (CRAAS), in order to analyze their variability and their changes at different spatio-temporal scales. In addition, co-occurrences between the cloud regimes and large-scale weather patterns are investigated. The CLoud property dAtAset using Spinning Enhanced Visible and Infrared (SEVIRI) edition 2.1 (CLAAS-2.1) data record, which is produced by the Satellite Application Facility on Climate Monitoring (CM SAF), was used as the basis for the derivation of the cloud regimes over Europe for a 14-year period (2004–2017). In particular, the cloud optical thickness (COT) and cloud top pressure (CTP) products of CLAAS-2.1 were used in order to compute 2D histograms. Then, the k-means clustering algorithm was applied to the generated 2D histograms in order to derive the cloud regimes. Eight cloud regimes were identified, which, along with the geographical distribution of their frequency of occurrence, assisted in providing a detailed description of the climate of the cloud properties over Europe. The annual and diurnal variabilities of the eight cloud regimes were studied, and trends in their frequency of occurrence were also examined. Larger changes in the frequency of occurrence of the produced cloud regimes were found for a regime associated to alto- and nimbo-type clouds and for a regime connected to shallow cumulus clouds and fog (−0.65% and +0.70% for the time period of the study, respectively). more
Application Atmosphere CM-SAF Climate Data Records

Contributions to the Improvement of Climate Data Availability and Quality for Sub-Saharan Africa

Author(s):
Kaspar, F.; Andersson, A.; Ziese, M.; Hollmann, R.
Publication title: Frontiers in Climate
2022
 | Volume: 3
2022
DOI: 10.3389/fclim.2021.815043
Abstract:
Reliable weather observations are the basis to assess climate change and variability. Compared to other regions of the world, long time series of weat… Reliable weather observations are the basis to assess climate change and variability. Compared to other regions of the world, long time series of weather observations are sparse in many countries of Sub-Saharan Africa. Various activities at national or international level are ongoing to improve the availability and quality of climate databases. Here, we present ongoing international contributions with a focus on representative examples hosted at Germany's national meteorological service DWD (Deutscher Wetterdienst). The international exchange of monthly climate reports (CLIMAT) is monitored within the Monitoring Centre of the GCOS Surface Network (Global Climate Observing System). In that context also quality control is performed and data are made publicly available. Recent climate observations can be complemented by digitization of historical hand-written weather observations which are available in distributed archives. International data centers, such as the Global Precipitation Climatology Centre (GPCC), collect international data. They perform quality-control of these observations and provide derived products in support of global and regional climate assessments. These activities can also contribute to the improvement of national climate databases, as e.g., demonstrated in a cooperation among selected countries with the SASSCAL initiative (Southern African Science Service Centre for Climate Change and Adaptive Land Management). Satellite-based observations are an additional source that can provide climatological information for selected parameters. In particular, the METEOSAT satellite series provides valuable data for the African continent. The Satellite Application Facility on Climate Monitoring (CM SAF) provides high resolution climate data covering the last decades derived from observations of such meteorological satellites. Based on these examples the paper illustrates the variety of ongoing international efforts in support of regional observation-based climate information, but also identifies the needs for further activities. Copyright © 2022 Kaspar, Andersson, Ziese and Hollmann. more
Application Atmosphere CM-SAF Climate Data Records

Comparison of Satellite-Based and Ångström–Prescott Estimated Global Horizontal Irradiance under Different Cloud Cover Conditions in South African Locations

Author(s):
Mabasa, Brighton; Lysko, Meena D.; Moloi, Sabata J.
Publication title: Solar
2022
 | Volume: 2 | Issue: 3
2022
DOI: 10.3390/solar2030021
Abstract:
The study compares the performance of satellite-based datasets and the Ångström–Prescott (AP) model in estimating the daily global horizontal irradian… The study compares the performance of satellite-based datasets and the Ångström–Prescott (AP) model in estimating the daily global horizontal irradiance (GHI) for stations in South Africa. The daily GHI from four satellites (namely SOLCAST, CAMS, NASA SSE, and CMSAF SARAH) and the Ångström–Prescott (AP) model are evaluated by validating them against ground observation data from eight radiometric stations located in all six macro-climatological regions of South Africa, for the period 2014-19. The evaluation is carried out under clear-sky, all-sky, and overcast-sky conditions. CLAAS-2 cloud fractional coverage data are used to determine clear and overcast sky days. The observed GHI data are first quality controlled using the Baseline Surface Radiation Network methodology and then quality control of the HelioClim model. The traditional statistical benchmarks, namely the relative mean bias error (rMBE), relative root mean square error (rRMSE), relative mean absolute error (rMAE), and the coefficient of determination (R2) provided information about the performance of the datasets. Under clear skies, the estimated datasets showed excellent performance with maximum rMBE, rMAE, and rRMSE less than 6.5% and a minimum R2 of 0.97. In contrast, under overcast-sky conditions there was noticeably poor performance with maximum rMBE (24%), rMAE (29%), rRMSE (39%), and minimum R2 (0.74). For all-sky conditions, good correlation was found for SOLCAST (0.948), CMSAF (0.948), CAMS (0.944), and AP model (0.91); all with R2 over 0.91. The maximum rRMSE for SOLCAST (10%), CAMS (12%), CMSAF (12%), and AP model (11%) was less than 13%. The maximum rMAE for SOLCAST (7%), CAMS (8%), CMSAF (8%), and AP model (9%) was less than 10%, showing good performance. While the R2 correlations for the NASA SSE satellite-based GHI were less than 0.9 (0.896), the maximum rRMSE was 18% and the maximum rMAE was 15%, showing rather poor performance. The performance of the SOLCAST, CAMS, CMSAF, and AP models was almost the same in the study area. CAMS, CMSAF, and AP models are viable, freely available datasets for estimating the daily GHI at South African locations with quantitative certainty. The relatively poor performance of the NASA SSE datasets in the study area could be attributed to their low spatial resolution of 0.5° × 0.5° (~55 km × 55 km). The feasibility of the datasets decreased significantly as the proportion of sky that was covered by clouds increased. The results of the study could provide a basis/data for further research to correct biases between in situ observations and the estimated GHI datasets using machine learning algorithms. more
Application Atmosphere CM-SAF Climate Data Records

Cloud-probability-based estimation of black-sky surface albedo from AVHRR data

Author(s):
Manninen, Terhikki; Jaaskelainen, Emmihenna; Siljamo, Niilo; Riihela, Aku; Karlsson, Karl-Goran
Publication title: ATMOSPHERIC MEASUREMENT TECHNIQUES
2022
 | Volume: 15 | Issue: 4
2022
DOI: 10.5194/amt-15-879-2022
Abstract:
This paper describes a new method for cloud-correcting observations of black-sky surface albedo derived using the Advanced Very High Resolution Radiom… This paper describes a new method for cloud-correcting observations of black-sky surface albedo derived using the Advanced Very High Resolution Radiometer (AVHRR). Cloud cover constitutes a major challenge for surface albedo estimation using AVHRR data for all possible conditions of cloud fraction and cloud type with any land cover type and solar zenith angle. This study shows how the new cloud probability (CP) data to be provided as part of edition A3 of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record from the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT can be used instead of traditional binary cloud masking to derive cloud-free monthly mean surface albedo estimates. Cloudy broadband albedo distributions were simulated first for theoretical cloud distributions and then using global cloud probability (CP) data for 1 month. A weighted mean approach based on the CP values was shown to produce very-high-accuracy black-sky surface albedo estimates for simulated data. The 90 % quantile for the error was 1.1 % (in absolute albedo percentage) and that for the relative error was 2.2 %. AVHRR-based and in situ albedo distributions were in line with each other and the monthly mean values were also consistent. Comparison with binary cloud masking indicated that the developed method improves cloud contamination removal. more
Application CM-SAF Climate Data Records Land

Climatological Drought Monitoring in Switzerland Using EUMETSAT SAF Satellite Data

Author(s):
Rassl, Annkatrin; Michel, Dominik; Hirschi, Martin; Duguay-Tetzlaff, Anke; Seneviratne, Sonia I.
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 23
2022
DOI: 10.3390/rs14235961
Abstract:
Climatological drought monitoring in Switzerland relies heavily on station-based precipitation and temperature data. Due to the high spatial variabili… Climatological drought monitoring in Switzerland relies heavily on station-based precipitation and temperature data. Due to the high spatial variability and complexity of droughts, it is important to complement station-based drought indices with gridded information and to couple multiple drought indicators within the monitoring system. Here, long-term satellite-based drought parameters from the EUMETSAT SAF network are analyzed in terms of dry anomalies within their climatology’s, namely ASCAT soil water index (SWI), CM SAF land surface temperature (LST), complemented with NOAA vegetation data, and LSA SAF Meteosat evapotranspiration data. The upcoming EUMETSAT SAF climate data records on land surface temperature and evapotranspiration will cover for the first time the WMO climatological 30-year reference period. This study is the first study investigating the potential of those long-term data records for climate monitoring of droughts in Europe. The satellite datasets are compared with the standardized precipitation index (SPI), soil moisture observations from the SwissSMEX measurement network, with a modelled soil moisture index (SMI) based on observations, and with evapotranspiration measurements, focusing on the temporal dynamics of the anomalies. For vegetation and surface temperature, the dry years of 2003, 2015, and 2018 are clearly visible in the satellite data. CM SAF LSTs show strong anomalies at the beginning of the drought period. The comparison of in situ and modelled soil moisture and evapotranspiration measurements with the satellite parameters shows strong agreement in terms of anomalies. The SWI indicates high anomaly correlations of 0.56 to 0.83 with measurements and 0.63 to 0.76 with the SMI at grassland sites. The Meteosat evapotranspiration data strongly agree with the measurements, with anomaly correlations of 0.63 and 0.67 for potential and actual evapotranspiration, respectively. Due to the prevailing humid climate conditions at the considered sites, evapotranspiration anomalies during the investigated dry periods were mostly positive and thus not water limited, but were also a driver for soil moisture drought. The results indicate that EUMETSAT SAF satellite data can well complement the station-based drought monitoring in Switzerland with spatial information. more
Application CM-SAF Climate Data Records H-SAF LSA-SAF Land

Climate services in support of climate change impact analyses for the German inland transportation system

Author(s):
Haensel, Stephanie; Brendel, Christoph; Haller, Michael; Kraehenmann, Stefan; Razafimaharo, Christene S.; Stanley, Kelly; Brienen, Susanne; Deutschlaender, Thomas; Rauthe, Monika; Walter, Andreas
Publication title: METEOROLOGISCHE ZEITSCHRIFT
2022
 | Volume: 31 | Issue: 3
2022
DOI: 10.1127/metz/2022/1117
Abstract:
Climate change and extreme weather events are an increasing challenge for society and the economy, including the transport sector. A sustainable and r… Climate change and extreme weather events are an increasing challenge for society and the economy, including the transport sector. A sustainable and resilient transportation system therefore requires information on the temporal and spatial pattern of risks induced by climate change and the assessment of resulting vulnerabilities. Such analyses in the past were usually made separately for each mode of transport based on different observational and climate model datasets and using different methodological approaches to analyse climatic changes and their impacts on the transport infrastructure. Within the research network “BMDV Network of Experts” an intermodal perspective is taken on transportation. Common observational and climate model datasets as well as a standardized analysis framework were coordinated and agreed upon to form the basis for comparable climate impact assessments for roads, railways and inland waterways. This manuscript introduces the climatological datasets and methodological approaches for the climate change and climate impact analysis used for the transportation sector and beyond. Selected results on the projected increases of extreme temperature and heavy precipitation are exemplarily presented in order to illustrate the need for developing climate change adaptation measures for the German inland transport system. more
Application Atmosphere CM-SAF Climate Data Records

Characterization of Tropical Cyclone Intensity Using the HY-2B Scatterometer Wind Data

Author(s):
Liu, Siqi; Lin, Wenming; Portabella, Marcos; Wang, Zhixiong
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 4
2022
DOI: 10.3390/rs14041035
Abstract:
The estimation of tropical cyclone (TC) intensity using Ku-band scatterometer data is challenging due to rain perturbation and signal saturation in th… The estimation of tropical cyclone (TC) intensity using Ku-band scatterometer data is challenging due to rain perturbation and signal saturation in the radar backscatter measurements. In this paper, an alternative approach to directly taking the maximum scatterometer-derived wind speed is proposed to assess the TC intensity. First, the TC center location is identified based on the unique characteristics of wind stress divergence/curl near the TC core. Then the radial extent of 17-m/s winds (i.e., R17) is calculated using the wind field data from the Haiyang-2B (HY-2B) scatterometer (HSCAT). The feasibility of HSCAT wind radii in determining TC intensity is evaluated using the maximum sustained wind speed (MSW) in the China Meteorological Administration best-track database. It shows that the HSCAT R17 value generally better correlates with the best-track MSW than the HSCAT maximum wind speed, therefore indicating the potential of using the HSCAT data to improve the TC nowcasting capabilities. more
Application Atmosphere NWP-SAF Software for CDR development

Characterization of Sunshine Duration in Western Equatorial Africa: In Situ Measurements versus SARAH-2 Satellite Estimates

Author(s):
Philippon, N.; Ouhechou, A.; Camberlin, P.; Trentmann, J.; Fink, A.H.; Maloba, J.D.; Morel, B.; Samba, G.
Publication title: Journal of Applied Meteorology and Climatology
2022
 | Volume: 61 | Issue: 2
2022
DOI: 10.1175/JAMC-D-21-0072.1
Abstract:
Western Equatorial Africa is one of the least sunny areas in the world. Yet, this has attracted little research so far. As in many other parts of Afri… Western Equatorial Africa is one of the least sunny areas in the world. Yet, this has attracted little research so far. As in many other parts of Africa, light availability is mainly estimated using in situ measurements of sunshine duration (SDU). Therefore, this study conducts the first characterization of SDU evolution during the annual cycle for the region. It also evaluates the skill of satellite-based estimates of SDU from the Surface Solar Radiation Data Set-Heliosat, edition 2.1 (SARAH-2.1). Mean annual SDU levels are low: Less than 5 h day21 at the regional scale, with the sunniest stations in the northeast (Cameroon and Central African Republic) and the least sunny in an ∼150-km-wide coastal strip in Gabon and Republic of the Congo (RoC). For most of the stations except the southeast ones in the Democratic Republic of Congo, the lowest SDU levels are recorded in July-September, during the main dry season, with persistent overcast conditions. They are as low as 2.5 h day21, especially on the windward slopes of the Massifs du Chaillu and du Mayombé, and of the Batéké Plateaus in Gabon and RoC. Although the mean annual and monthly spatial patterns are well reproduced in SARAH-2.1, SDU levels are systematically overestimated by 1-2 h day21. The largest positive biases are recorded during the December-February dry season, especially at the northernmost stations. Analyses at the daily time scale show that SARAH-2.-1 biases arise from a twofold problem: The number of dark days (SDU &lt;1 h day2-1) is 50%lower than observed whereas that of sunny days (SDU &gt; 9 h day21) is 50%higher than observed. © 2022 American Meteorological Society. more
Atmosphere CM-SAF Climate Data Records Validation

Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP

Author(s):
Modanesi, Sara; Massari, Christian; Bechtold, Michel; Lievens, Hans; Tarpanelli, Angelica; Brocca, Luca; Zappa, Luca; De Lannoy, Gabrielle J. M.
Publication title: HYDROLOGY AND EARTH SYSTEM SCIENCES
2022
 | Volume: 26 | Issue: 18
2022
DOI: 10.5194/hess-26-4685-2022
Abstract:
In recent years, the amount of water used for agricultural purposes has been rising due to an increase in food demand. However, anthropogenic water us… In recent years, the amount of water used for agricultural purposes has been rising due to an increase in food demand. However, anthropogenic water usage, such as for irrigation, is still not or poorly parameterized in regional- and larger-scale land surface models (LSMs). By contrast, satellite observations are directly affected by, and hence potentially able to detect, irrigation as they sense the entire integrated soil-vegetation system. By integrating satellite observations and fine-scale modelling it could thus be possible to improve estimation of irrigation amounts at the desired spatial-temporal scale. In this study we tested the potential information offered by Sentinel-1 backscatter observations to improve irrigation estimates, in the framework of a data assimilation (DA) system composed of the Noah-MP LSM, equipped with a sprinkler irrigation scheme, and a backscatter operator represented by a water cloud model (WCM), as part of the NASA Land Information System (LIS). The calibrated WCM was used as an observation operator in the DA system to map model surface soil moisture and leaf area index (LAI) into backscatter predictions and, conversely, map observation-minus-forecast backscatter residuals back to updates in soil moisture and LAI through an ensemble Kalman filter (EnKF). The benefits of Sentinel-1 backscatter observations in two different polarizations (VV and VH) were tested in two separate DA experiments, performed over two irrigated sites, the first one located in the Po Valley (Italy) and the second one located in northern Germany. The results confirm that VV backscatter has a stronger link with soil moisture than VH backscatter, whereas VH backscatter observations introduce larger updates in the vegetation state variables. The backscatter DA introduced both improvements and degradations in soil moisture, evapotranspiration and irrigation estimates. The spatial and temporal scale had a large impact on the analysis, with more contradicting results obtained for the evaluation at the fine agriculture scale (i.e. field scale). Above all, this study sheds light on the limitations resulting from a poorly parameterized sprinkler irrigation scheme, which prevents improvements in the irrigation simulation due to DA and points to future developments needed to improve the system. more
Application Climate Data Records H-SAF Land

Bayesian Cloud Detection over Land for Climate Data Records

Author(s):
Bulgin, Claire E.; Embury, Owen; Maidment, Ross I.; Merchant, Christopher J.
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 9
2022
DOI: 10.3390/rs14092231
Abstract:
Cloud detection is a necessary step in the generation of land surface temperature (LST) climate data records (CDRs) and affects data quality and uncer… Cloud detection is a necessary step in the generation of land surface temperature (LST) climate data records (CDRs) and affects data quality and uncertainty. We present here a sensor-independent Bayesian cloud detection algorithm and show that it is suitable for use in the production of LST CDRs. We evaluate the performance of the cloud detection with reference to two manually masked datasets for the Advanced Along-Track Scanning Radiometer (AATSR) and find a 7.9% increase in the hit rate and 4.9% decrease in the false alarm rate when compared to the operational cloud mask. We then apply the algorithm to four instruments aboard polar-orbiting satellites, which together can produce a global, 25-year LST CDR: the second Along-Track Scanning Radiometer (ATSR-2), AATSR, the Moderate Resolution Spectroradiometer (MODIS Terra) and the Sea and Land Surface Temperature Radiometer (SLSTR-A). The Bayesian cloud detection hit rate is assessed with respect to in situ ceilometer measurements for periods of overlap between sensors. The consistency of the hit rate is assessed between sensors, with mean differences in the cloud hit rate of 4.5% for ATSR-2 vs. AATSR, 4.9% for AATSR vs. MODIS, and 2.5% for MODIS vs. SLSTR-A. This is important because consistent cloud detection performance is needed for the observational stability of a CDR. The application of a sensor-independent cloud detection scheme in the production of CDRs is thus shown to be a viable approach to achieving LST observational stability over time. more
Application Atmosphere NWP-SAF Software for CDR development

Atmosphere and Terrain Coupling Simulation Framework for High-Resolution Visible-Thermal Spectral Imaging over Heterogeneous Land Surface

Author(s):
Qiu, Xianfei; Zhao, Huijie; Jia, Guorui; Li, Jiyuan
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 9
2022
DOI: 10.3390/rs14092043
Abstract:
Realistic modeling of high-resolution earth radiation signals in the visible-thermal spectral domain remains difficult, due to the complex radiation i… Realistic modeling of high-resolution earth radiation signals in the visible-thermal spectral domain remains difficult, due to the complex radiation interdependence induced by the heterogeneous and rugged features of land surface. To find the trade-off between accuracy and efficiency for image simulation, this paper established a unified simulation framework for the entire visible-thermal spectral domain, based on the energy balance between solar-reflected and thermal radiation components over rugged surfaces. Considering the joint contributions of atmospheric and topographic adjacency effects, three spatial–spectral convolution kernels were uniformly designed to quantify the topographic irradiance, the trapping effect, and the atmospheric adjacency effect. Radiation signal simulation was implemented in three forms: land surface temperature (LST), bottom of atmosphere (BOA) radiance, and top of atmosphere (TOA) radiance. The accuracy was validated with onboard data from China’s Gaofen-5 visual and infrared multispectral sensor (VIMS) over rugged desert. The simulation results demonstrate that the root mean square of relative deviations between the simulated and onboard TOA radiance are related to terrain, as 3–17% and 6–38% for the summer and winter scene, respectively. The evaluation of radiance components indicates the utility of the simulation framework to quantify the uncertainty associated with atmosphere and terrain coupling effects, in the sensor design and operation stages. more
Application Atmosphere NWP-SAF Software for CDR development

Assimilation of satellite data in numerical weather prediction. Part II: Recent years

Author(s):
Eyre, J.R.; Bell, W.; Cotton, J.; English, S.J.; Forsythe, M.; Healy, S.B.; Pavelin, E.G.
Publication title: Quarterly Journal of the Royal Meteorological Society
2022
 | Volume: 148 | Issue: 743
2022
DOI: 10.1002/qj.4228
Abstract:
Developments in the assimilation of satellite data in numerical weather prediction (NWP), from the first experiments in the late 1960s to the present … Developments in the assimilation of satellite data in numerical weather prediction (NWP), from the first experiments in the late 1960s to the present day, are presented in a two-part review article. This part, Part II, reviews the progress in recent years, from about 2000. It includes summaries of advances in the relevant satellite remote-sensing technologies and in methods to assimilate observations from these instruments into NWP systems. It also summarises impacts on forecast skill. Continued progress has been made on the assimilation of passive infrared (IR) sounding data and microwave (MW) sounding and imaging data. This has included data from hyperspectral IR sounders, which first became available during this period. Advances in the use of cloud-affected radiances, from both IR and MW instruments, have been made. In support of this progress, further developments have been made in fast radiative transfer models and in bias correction techniques, and work has continued to improve understanding and representation of observation uncertainties. Continued progress has also been made on the use of wind information from satellites, including atmospheric motion vectors and scatterometer data. A new source of temperature and humidity information, from radio occultation observations, has become available during the period and has been exploited by many NWP centres. The impact of satellite data on NWP accuracy is continually assessed using a range of methods and metrics. Some results from recent Observing System Experiments (OSEs) and Forecast Sensitivity to Observation Impact (FSOI) assessment are presented and other methods are discussed. The role of satellite data in NWP-based atmospheric reanalysis systems is also described. © 2021 Crown copyright. Quarterly Journal of the Royal Meteorological Society © 2021 Royal Meteorological Society. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. more
Application Atmosphere CM-SAF Climate Data Records EUM-Secr NWP-SAF Software for CDR development

Assessment of 24 soil moisture datasets using a new in situ network in the Shandian River Basin of China

Author(s):
Zheng, Jingyao; Zhao, Tianjie; Lü, Haishen; Shi, Jiancheng; Cosh, Michael H.; Ji, Dabin; Jiang, Lingmei; Cui, Qian; Lu, Hui; Yang, Kun; Wigneron, Jean-Pierre; Li, Xiaojun; Zhu, Yonghua; Hu, Lu; Peng, Zhiqing; Zeng, Yelong; Wang, Xiaoyi; Kang, Chuen Siang
Publication title: Remote Sensing of Environment
2022
 | Volume: 271
2022
DOI: 10.1016/j.rse.2022.112891
Climate Data Records H-SAF Land Validation

Assessing the potential for sea-based macroalgae cultivation and its application for nutrient removal in the Baltic Sea

Author(s):
Kotta, Jonne; Raudsepp, Urmas; Szava-Kovats, Robert; Aps, Robert; Armoskaite, Aurelija; Barda, Ieva; Bergstrom, Per; Futter, Martyn; Grondahl, Fredrik; Hargrave, Matthew; Jakubowska, Magdalena; Janes, Holger; Kaasik, Ants; Kraufvelin, Patrik; Kovaltchouk, Nikolai; Krost, Peter; Kulikowski, Tomasz; Koivupuu, Anneliis; Kotta, Ilmar; Lees, Liisi; Loite, Sander; Maljutenko, Ilja; Nylund, Goran; Paalme, Tiina; Pavia, Henrik; Purina, Ingrida; Rahikainen, Moona; Sandow, Verena; Visch, Wouter; Yang, Baoru; Barboza, Francisco R.
Publication title: SCIENCE OF THE TOTAL ENVIRONMENT
2022
 | Volume: 839
2022
DOI: 10.1016/j.scitotenv.2022.156230
Abstract:
Marine eutrophication is a pervasive and growing threat to global sustainability. Macroalgal cultivation is a promising circular economy solution to a… Marine eutrophication is a pervasive and growing threat to global sustainability. Macroalgal cultivation is a promising circular economy solution to achieve nutrient reduction and food security. However, the location of production hotspots is not well known. In this paper the production potential of macroalgae of high commercial value was predicted across the Baltic Sea region. In addition, the nutrient limitation within and adjacent to macroalgal farms was investigated to suggest optimal site-specific configuration of farms. The production potential of Saccharina latissima was largely driven by salinity and the highest production yields are expected in the westernmost Baltic Sea areas where salinity is > 23. The direct and interactive effects of light availability, temperature, salinity and nutrient concentrations regulated the predicted changes in the production of Ulva intestinalis and Fucus vesiculosus. The western and southern Baltic Sea exhibited the highest farming potential for these species, with promising areas also in the eastern Baltic Sea. Macroalgal farming did not induce significant nutrient limitation. The expected spatial propagation of nutrient limitation caused by macroalgal farming was less than 100-250 m. Higher propagation distances were found in areas of low nutrient and low water exchange (e.g. offshore areas in the Baltic Proper) and smaller distances in areas of high nutrient and high water exchange (e.g. western Baltic Sea and Gulf of Riga). The generated maps provide the most sought-after input to support blue growth initiatives that foster the sustainable development of macroalgal cultivation and reduction of in situ nutrient loads in the Baltic Sea. more
Application CM-SAF Climate Data Records Land

Assessing the consistency of satellite derived upper tropospheric humidity measurements

Author(s):
Shi, Lei; Schreck III, Carl J.; John, Viju O.; Chung, Eui-Seok; Lang, Theresa; Buehler, Stefan A.; Soden, Brian J.
2022
2022
DOI: 10.5194/amt-15-6949-2022
Abstract:
Abstract. Four upper tropospheric humidity (UTH) datasets derived from satellite sounders are evaluated to assess their consistency as part of the act… Abstract. Four upper tropospheric humidity (UTH) datasets derived from satellite sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The datasets include UTH computed from brightness temperature measurements of the 183.31 ± 1 GHz channel of the Special Sensor Microwave – Humidity (SSM/T-2), Advanced Microwave Sounding Unit-B (AMSU-B), and Microwave Humidity Sounder (MHS), and from channel 12 of the High-Resolution Infrared Radiation Sounder (HIRS). The four datasets are consistent in the interannual temporal and spatial variability of the tropics. Large positive anomalies peaked over the central equatorial Pacific region during El Niño events in the same phase with the increase of sea surface temperature. Conversely, large negative anomalies were obtained during El Niño events when the tropical domain average is taken. The weakened ascending branch of the Pacific Walker circulation in the western Pacific and the enhanced descending branches of the local Hadley circulation along the Pacific subtropics largely contributed to widespread drying areas and thus negative anomalies in the upper troposphere during El Niño events as shown in all four datasets. Due to differences in retrieval definitions, calibration methods, and sensor limitations, there are differences in spatial anomalies and temporal change rates, where more significant anomaly values are usually found in the microwave UTH data. more
Application Atmosphere CM-SAF Climate Data Records EUM-Secr Validation

Assessing Crop Water Requirement and Yield by Combining ERA5-Land Reanalysis Data with CM-SAF Satellite-Based Radiation Data and Sentinel-2 Satellite Imagery

Author(s):
Pelosi, Anna; Belfiore, Oscar Rosario; D’Urso, Guido; Chirico, Giovanni Battista
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 24
2022
DOI: 10.3390/rs14246233
Abstract:
The widespread development of Earth Observation (EO) systems and advances in numerical atmospheric modeling have made it possible to use the newest da… The widespread development of Earth Observation (EO) systems and advances in numerical atmospheric modeling have made it possible to use the newest data sources as input for crop–water balance models, thereby improving the crop water requirements (CWR) and yield estimates from the field to the regional scale. Satellite imagery and numerical weather prediction outputs offer high resolution (in time and space) gridded data that can compensate for the paucity of crop parameter field measurements and ground weather observations, as required for assessments of CWR and yield. In this study, the AquaCrop model was used to assess CWR and yield of tomato on a farm in Southern Italy by assimilating Sentinel-2 (S2) canopy cover imagery and using CM-SAF satellite-based radiation data and ERA5-Land reanalysis as forcing weather data. The prediction accuracy was evaluated with field data collected during the irrigation season (April–July) of 2021. Satellite estimates of canopy cover differed from ground observations, with a RMSE of about 11%. CWR and yield predictions were compared with actual data regarding irrigation volumes and harvested yield. The results showed that S2 estimates of crop parameters represent added value, since their assimilation into crop growth models improved CWR and yield estimates. Reliable CWR and yield estimates can be achieved by combining the ERA5-Land and CM-SAF weather databases with S2 imagery for assimilation into the AquaCrop model. more
Application Atmosphere CM-SAF Climate Data Records Land

Arctic Sea-Ice Surface Elevation Distribution from NASA’s Operation IceBridge ATM Data

Author(s):
Yi, Donghui; Egido, Alejandro; Smith, Walter H. F.; Connor, Laurence; Buchhaupt, Christopher; Zhang, Dexin
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 13
2022
DOI: 10.3390/rs14133011
Abstract:
In this paper, we characterize the sea-ice elevation distribution by using NASA’s Operation IceBridge (OIB) Airborne Topographic Mapper (ATM) L1B data… In this paper, we characterize the sea-ice elevation distribution by using NASA’s Operation IceBridge (OIB) Airborne Topographic Mapper (ATM) L1B data over the Arctic Ocean during 94 Spring campaigns between 2009 and 2019. The ultimate objective of this analysis is to better understand sea-ice topography to improve the estimation of the sea-ice freeboard for nadir-looking altimeters. We first introduce the use of an exponentially modified Gaussian (EMG) distribution to fit the surface elevation probability density function (PDF). The characteristic function of the EMG distribution can be integrated in the modeling of radar altimeter waveforms. Our results indicate that the Arctic sea-ice elevation PDF is dominantly positively skewed and the EMG distribution is better suited to fit the PDFs than the classical Gaussian or lognormal PDFs. We characterize the elevation correlation characteristics by computing the autocorrelation function (ACF) and correlation length (CL) of the ATM measurements. To support the radar altimeter waveform retracking over sea ice, we perform this study typically on 1.5 km ATM along-track segments that reflect the footprint diameter size of radar altimeters. During the studied period, the mean CL values range from 20 to 30 m, which is about 2% of the radar altimeter footprint diameter (1.5 km). more
Application Climate Data Records Cryosphere OSI-SAF

Analysis of the main source regions of moisture transport events with the new ESA CCI/CM-SAF total column water vapour climate data record (v2)

Author(s):
Eiras-Barca, Jorge; Algarra, Iago; Nieto, Raquel; Schroder, Marc; Hegglin, Michaela, I; Gimeno, Luis
Publication title: QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
2022
 | Volume: 148 | Issue: 748
2022
DOI: 10.1002/qj.4358
Abstract:
This study makes use of the new total column water vapour data record (CDR-2 (v2)), developed by the European Space Agency (ESA) in coordination with … This study makes use of the new total column water vapour data record (CDR-2 (v2)), developed by the European Space Agency (ESA) in coordination with the Satellite Application Facility on Climate Monitoring (CM SAF), to analyse the adequacy of the integrated vertical water vapour column (IWV) data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 and ERA-Interim reanalyses in regions of critical interest for moisture transport mechanisms. This information is critical for the initialization of moisture transport models-both Eulerian and Lagrangian-used to study the main mechanisms and predict the future evolution of moisture transport events. In particular, almost 40,000 atmospheric river (AR) and nocturnal low-level jet (NLLJ) events identified on a global scale between 2002 and 2017 have been used to study the variability between the cited reanalyses and CDR-2, in terms of both bias in the observed values of IWV during each particular event and daily temporal correlation fields. Although some notable discrepancies are reported in the main tropical rainforest regions, it is observed that, in regions of high interest for both ARs and NLLJs, the degree of agreement between the reanalyses and CDR-2 is high. The bias observed in the regions of interest is generally low, and the temporal correlation in the IWV fields is above 0.8 in most areas. ERA5 appears to show slightly better performance than ERA-Interim when resolving the moisture column, and both show greater similarity to CDR-2 in the midlatitudes compared with tropical regions. The probability density functions constructed on an event-to-event basis reinforce these ideas. We conclude that the evaluations presented here using CDR-2 serve to strengthen avaliable evidence that the ECMWF reanalyses can safely be used in the initializations of Lagrangian dispersion models and Eulerian moisture tracer simulations-commonly used for the analysis of main advection mechanisms-in the vast majority of regions critical to the study of ARs and LLJs. They can also safely be used for the detection of moisture source-sink regions in the study of the global hydrological cycle in these regions. more
Atmosphere CM-SAF Climate Data Records Validation

Analysis of Daytime Cloud Fraction Spatiotemporal Variation over the Arctic from 2000 to 2019 from Multiple Satellite Products

Author(s):
Liu, Xinyan; He, Tao; Sun, Lin; Xiao, Xiongxin; Liang, Shunlin; Li, Siwei
Publication title: Journal of Climate
2022
 | Volume: 35 | Issue: 23
2022
DOI: 10.1175/JCLI-D-22-0007.1
Abstract:
Abstract Insufficient understanding of complex Arctic cloud properties introduced large errors in estimating radiant energy balance parameters at the … Abstract Insufficient understanding of complex Arctic cloud properties introduced large errors in estimating radiant energy balance parameters at the regional and global scales. Comprehensive and reliable cloud information is necessary for improving the accuracy of flux inversion. This study evaluated daytime cloud fraction (CF) uncertainties from 16 available satellite products and estimated the spatiotemporal distributions of Arctic daytime CF during 2000–19. Our results show that the differences among multiple products had significant temporal and spatial heterogeneities. Temporally, the maximum and minimum interproduct discrepancies occurred in April and the summer months, respectively. Spatially, the largest uncertainties were seen over Greenland. Substantial inconsistency also occurred on the central and Pacific sides of the Arctic Ocean. The active satellite product tended to capture more clouds in these two regions. We found that the inconsistencies caused by sensor differences were smaller than those caused by algorithm differences; that is, for MODIS based CF products, the inconsistencies caused by different sensors and different algorithms are ±2% and ±5%, while for AVHRR-based products, these inconsistencies are ±6% and ±15%, respectively. The annual average daytime CF in sunlit months was 70.9% ± 2.93% and increased over the Arctic during study periods. These upward trends might cool the Arctic by approximately 0.05–0.5 W m−2 decade−1. In terms of the spatiotemporal distributions, the CF over the ocean is higher than that over the land, and the former increased significantly while the latter decreased; the CF trends of most products are positive in June and July but are opposite in other months. From this study, the findings based on multiple products would be more robust than that based on a single or few datasets. Significance Statement This study aimed to comprehensively understand and obtain more robust general characteristics of the temporal and spatial distributions of Arctic daytime cloud fraction by comparing and analyzing the consistencies and discrepancies of multisource satellite products. It is important because the cloud fraction is a nonnegligible modulator of Earth’s energy budget and climate change. Although the Arctic is the most climate-sensitive region, existing studies lack a comprehensive assessment of the cloud fraction over the entire Arctic. We analyzed 16 different cloud products and found that although the inconsistencies were inevitable, most products showed similar spatiotemporal distribution and trend distribution of daytime CF. This study provided a new idea for Arctic CF research under the existing conditions. more
Atmosphere CM-SAF Climate Data Records Validation

An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties

Author(s):
Bell, Alistair; Martinet, Pauline; Caumont, Olivier; Burnet, Frederic; Delanoe, Julien; Jorquera, Susana; Seity, Yann; Unger, Vinciane
Publication title: ATMOSPHERIC MEASUREMENT TECHNIQUES
2022
 | Volume: 15 | Issue: 18
2022
DOI: 10.5194/amt-15-5415-2022
Abstract:
A new generation of cloud radars, with the ability to make observations close to the surface, presents the possibility of observing fog properties wit… A new generation of cloud radars, with the ability to make observations close to the surface, presents the possibility of observing fog properties with better insight than was previously possible. The use of these instruments as part of an operational observation network could improve the prediction of fog events, something which is still a problem for even high-resolution numerical weather prediction models. However, the retrieval of liquid water content (LWC) profiles from radar reflectivity alone is an under-determined problem, something which ground-based microwave radiometer observations can help to constrain. In fact, microwave radiometers are not only sensitive to temperature and humidity profiles but are also known to be instruments of reference for the liquid water path. By providing the thermodynamic state of the atmosphere, to which the formation and evolution of fog events are highly sensitive, in addition to accurate liquid water path, which can be used to constrain the LWC retrieval from the cloud radar alone, combining microwave radiometers with cloud radars seems a natural next step to better understand and forecast fog events. To that end, a newly developed one-dimensional variational (1D-Var) algorithm designed for the retrieval of temperature, specific humidity and liquid water content profiles with both cloud radar and microwave radiometer (MWR) observations is presented in this study. The algorithm was developed to evaluate the capability of cloud radar and MWR to provide accurate LWC profiles in addition to temperature and humidity in view of assimilating the retrieved profiles into a 3D- and 4D-Var operational assimilation system. The algorithm is firstly tested on a synthetic dataset, which allows the evaluation of the developed algorithm in idealised conditions. This dataset was constructed by perturbing a high-resolution forecast dataset of fog and low-cloud cases by its expected errors. The algorithm is then tested with real data from the recent field campaign SOFOG-3D, carried out with the use of LWC measurements made from a tethered balloon platform. As expected, results from the synthetic dataset study were found to contain lower errors than those found from the retrievals on the dataset of real observations. It was found that LWC can be retrieved in idealised conditions with an uncertainty of less than 0.04 g m(-3). With real data, as expected, retrievals with a good correlation (0.7) to in situ measurements were found but with a higher uncertainty than the synthetic dataset of around 0.06 g m(-3) (41 %). This was reduced to 0.05 g m(-3) (35 %) when an accurate droplet number concentration could be prescribed to the algorithm. A sensitivity study was conducted to discuss the impact of different settings used in the 1D-Var algorithm and the forward operator. Additionally, retrievals of LWC from a real fog event observed during the SOFOG-3D field campaign were found to significantly improve the operational background profiles of the AROME (Application of Research to Operations at MEsoscale) model, showing encouraging results for future improvement of the AROME model initial state during fog conditions. more
Application Atmosphere NWP-SAF Software for CDR development

An Intercomparison of Satellite Derived Arctic Sea Ice Motion Products

Author(s):
Wang, Xue; Chen, Runtong; Li, Chao; Chen, Zhuoqi; Hui, Fengming; Cheng, Xiao
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 5
2022
DOI: 10.3390/rs14051261
Abstract:
Arctic sea ice motion information provides an important scientific basis for revealing the changing mechanism of Arctic sea ice and assessing the navi… Arctic sea ice motion information provides an important scientific basis for revealing the changing mechanism of Arctic sea ice and assessing the navigational safety of Arctic waterways. For now, many satellite derived Arctic sea ice motion products have been released but few studies have conducted comparisons of these products. In this study, eleven satellite sea ice motion products from the Ocean and Sea Ice Satellite Application Facility (OSI SAF), the National Snow and Ice Data Center (NSIDC), and the French Research Institute for the Exploitation of the Seas (Ifremer) were systematically evaluated and compared based on buoys from the International Arctic Buoy Program (IABP) and the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) over 2018–2020. The results show that the mean absolute errors (MAEs) of ice speed for these products are 1.15–2.26 km/d and the MAEs of ice motion angle are 14.93–23.19°. Among all products, Ifremer_AMSR2 achieves the best accuracy in terms of speed error, NSIDC_Pathfinder shows the lowest angle error and OSI-405-c_Merged performs best in sea-ice drift trajectory reconstruction. Moreover, season, region, data source, ice drift tracking algorithm, and time interval all influence the accuracy of these products: (1) The sea ice motion bias in the freezing season (1.04–1.96 km/d and 11.93–22.41°) is smaller than that in the melting season (1.13–3.90 km/d and 14.41–27.41°) for most of the products. (2) Most products perform worst in East Greenland, where ice movements are fast and complex. (3) The accuracies of the products derived from AMSR-2 remotely sensed data are better than those from other data sources. (4) The continuous maximum cross-correlation (CMCC) algorithm outperforms the maximum cross-correlation (MCC) algorithm in sea ice drift retrieval. (5) The MAEs of sea ice motion with longer time interval are relatively smaller. Overall, the results indicate that the eleven remote sensing Arctic sea ice drift products are of practical use for data assimilation and model validation if uncertainties are appropriately considered. Furthermore, this study provides some improvement directions for sea ice drift retrieval from satellite data. more
Climate Data Records Cryosphere OSI-SAF Validation

An indicator of sea ice variability for the Antarctic marginal ice zone

Author(s):
Vichi, Marcello
Publication title: CRYOSPHERE
2022
 | Volume: 16 | Issue: 10
2022
DOI: 10.5194/tc-16-4087-2022
Abstract:
Remote-sensing records over the last 40 years have revealed large year-to-year global and regional variability in Antarctic sea ice extent. Sea ice ar… Remote-sensing records over the last 40 years have revealed large year-to-year global and regional variability in Antarctic sea ice extent. Sea ice area and extent are useful climatic indicators of large-scale variability, but they do not allow the quantification of regions of distinct variability in sea ice concentration (SIC). This is particularly relevant in the marginal ice zone (MIZ), which is a transitional region between the open ocean and pack ice, where the exchanges between ocean, sea ice and atmosphere are more intense. The MIZ is circumpolar and broader in the Antarctic than in the Arctic. Its extent is inferred from satellite-derived SIC using the 15 %-80 % range, assumed to be indicative of open drift or partly closed sea ice conditions typical of the ice edge. This proxy has been proven effective in the Arctic, but it is deemed less reliable in the Southern Ocean, where sea ice type is unrelated to the concentration value, since wave penetration and free-drift conditions have been reported with 100 % cover. The aim of this paper is to propose an alternative indicator for detecting MIZ conditions in Antarctic sea ice, which can be used to quantify variability at the climatological scale on the ice-covered Southern Ocean over the seasons, as well as to derive maps of probability of encountering a certain degree of variability in the expected monthly SIC value. The proposed indicator is based on statistical properties of the SIC; it has been tested on the available climate data records to derive maps of the MIZ distribution over the year and compared with the threshold-based MIZ definition. The results present a revised view of the circumpolar MIZ variability and seasonal cycle, with a rapid increase in the extent and saturation in winter, as opposed to the steady increase from summer to spring reported in the literature. It also reconciles the discordant MIZ extent estimates using the SIC threshold from different algorithms. This indicator complements the use of the MIZ extent and fraction, allowing the derivation of the climatological probability of exceeding a certain threshold of SIC variability, which can be used for planning observational networks and navigation routes, as well as for detecting changes in the variability when using climatological baselines for different periods. more
Application Climate Data Records Cryosphere OSI-SAF

An Evaluation of the Performance of Sea Ice Thickness Forecasts to Support Arctic Marine Transport

Author(s):
Bilge, Tarkan Aslan; Fournier, Nicolas; Mignac, Davi; Hume-Wright, Laura; Bertino, Laurent; Williams, Timothy; Tietsche, Steffen
Publication title: Journal of Marine Science and Engineering
2022
 | Volume: 10 | Issue: 2
2022
DOI: 10.3390/jmse10020265
Abstract:
In response to declining sea ice cover, human activity in the Arctic is increasing, with access to the Arctic Ocean becoming more important for socio-… In response to declining sea ice cover, human activity in the Arctic is increasing, with access to the Arctic Ocean becoming more important for socio-economic reasons. Accurate knowledge of sea ice conditions is therefore becoming increasingly important for reducing the risk and operational cost of human activities in the Arctic. Satellite-based sea ice charting is routinely used for tactical ice management, but the marine sector does not yet make optimal use of sea ice thickness (SIT) or sea ice concentration (SIC) forecasts on weekly timescales. This is because forecasts have not achieved sufficient accuracy, verification and resolution to be used in situations where maritime safety is paramount, and assessing the suitability of forecasts can be difficult because they are often not available in the appropriate format. In this paper, existing SIT forecasts currently available on the Copernicus Marine Service (CMS) or elsewhere in the public domain are evaluated for the first time. These include the seven-day forecasts from the UK Met Office, MET Norway, the Nansen Environmental and Remote Sensing Center (NERSC) and the European Centre for Medium-Range Weather Forecasts (ECMWF). Their forecast skills were assessed against unique in situ data from five moorings deployed between 2016 and 2019 by the Barents Sea Metocean and Ice Network (BASMIN) and Barents Sea Exploration Collaboration (BaSEC) Joint Industry Projects. Assessing these models highlights the importance of data assimilation in short-term forecasting of SIT and suggests that improved assimilation of sea ice data could increase the utility of forecasts for navigational purposes. This study also demonstrates that forecasts can achieve similar or improved correlation with observations when compared to a persistence model at a lead time of seven days, providing evidence that, when used in conjunction with sea ice charts, SIT forecasts could provide valuable information on future sea ice conditions. more
Application Climate Data Records Cryosphere OSI-SAF

A Review on the Current Status of Numerical Weather Prediction in Portugal 2021: Surface–Atmosphere Interactions

Author(s):
Monteiro, Maria José; Couto, Flavio T.; Bernardino, Mariana; Cardoso, Rita M.; Carvalho, David; Martins, João P. A.; Santos, João A.; Argain, José Luís; Salgado, Rui
Publication title: Atmosphere
2022
 | Volume: 13 | Issue: 9
2022
DOI: 10.3390/atmos13091356
Abstract:
Earth system modelling is currently playing an increasing role in weather forecasting and understanding climate change, however, the operation, deploy… Earth system modelling is currently playing an increasing role in weather forecasting and understanding climate change, however, the operation, deployment and development of numerical Earth system models are extremely demanding in terms of computational resources and human effort. Merging synergies has become a natural process by which national meteorological services assess and contribute to the development of such systems. With the advent of joining synergies at the national level, the second edition of the workshop on Numerical Weather Prediction in Portugal was promoted by the Portuguese Institute for the Sea and Atmosphere, I.P. (IPMA), in cooperation with several Portuguese Universities. The event was hosted by the University of Évora, during the period of 11–12 of November 2021. It was dedicated to surface–atmosphere interactions and allowed the exchange of experiences between experts, students and newcomers. The workshop provided a refreshed overview of ongoing research and development topics in Portugal on surface–atmosphere interaction modelling and its applications and an opportunity to revisit some of the concepts associated with this area of atmospheric sciences. This article reports on the main aspects discussed and offers guidance on the many technical and scientific modelling platforms currently under study. more
Application Climate Data Records LSA-SAF Land

A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS

Author(s):
Preußer, Andreas; Heinemann, Günther; Schefczyk, Lukas; Willmes, Sascha
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 9
2022
DOI: 10.3390/rs14092036
Abstract:
Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which driv… Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combination with atmospheric reanalysis data have proven to be a strong tool to monitor large and regularly forming polynyas and to resolve narrow thin-ice areas (i.e., leads) along the shelf-breaks and across the entire Arctic Ocean. However, the selection of the atmospheric data sets has a large influence on derived polynya characteristics due to their impact on the calculation of the heat loss to the atmosphere, which is determined by the local thin-ice thickness. In order to overcome this methodical ambiguity, we present a MODIS-assisted temperature adjustment (MATA) algorithm that yields corrections of the 2 m air temperature and hence decreases differences between the atmospheric input data sets. The adjustment algorithm is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies on the developed algorithm and present time series of polynya characteristics in the winter season 2019/2020. It shows that the application of the empirically derived correction decreases the difference between different utilized atmospheric products significantly from 49% to 23%. Additional filter strategies are applied that aim at increasing the capability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites. More generally, the winter of 2019/2020 features high polynya activity in the eastern Arctic and less activity in the Canadian Arctic Archipelago, presumably as a result of the particularly strong polar vortex in early 2020. more
Application Climate Data Records Cryosphere OSI-SAF

A Method for Clear-Sky Identification and Long-Term Trends Assessment Using Daily Surface Solar Radiation Records

Author(s):
Correa, L.F.; Folini, D.; Chtirkova, B.; Wild, M.
Publication title: Earth and Space Science
2022
 | Volume: 9 | Issue: 8
2022
DOI: 10.1029/2021EA002197
Abstract:
Time series of clear-sky irradiance are fundamental for the understanding of changes in the Earth Radiation budget, since they allow to examine radiat… Time series of clear-sky irradiance are fundamental for the understanding of changes in the Earth Radiation budget, since they allow to examine radiative processes in the cloud-free atmosphere. Clear-sky data is usually derived from all-sky irradiances using one of several clear-sky methods proposed in the literature. However, most of the available clear-sky methods require additional in situ measurements and/or high temporal resolution (sub-daily), which restricts the derivation of clear-sky time series to a few well equipped stations. Here we propose a new clear-sky identification method that aims to overcome this problem, with the ultimate goal of deriving multidecadal clear-sky trends for many sites globally. The method uses site specific monthly transmittance thresholds to derive long term clear-sky time series for any station worldwide that has daily mean irradiance data. We exemplify the method for 24 stations. Transmittance thresholds are derived by combining 29 years (1990–2018) of satellite cloud cover data with in situ irradiance measurements. The thresholds are then applied to the whole time series (independent of satellite data availability) to screen out cloudy days. Comparison of our results with reference data derived using Long and Ackerman's (2000, https://doi.org/10.1029/2000jd900077) method shows good agreement after bias correction, especially for decadal trends. While limitations of the method, such as anomalies representation, are highlighted and discussed, validation results encourage its use to derive long term clear-sky time series and associated decadal-scale trends around the globe. © 2022 The Authors. more
Application Atmosphere CM-SAF Climate Data Records

A Machine Learning Snowfall Retrieval Algorithm for ATMS

Author(s):
Sanò, Paolo; Casella, Daniele; Camplani, Andrea; D’Adderio, Leo Pio; Panegrossi, Giulia
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 6
2022
DOI: 10.3390/rs14061467
Abstract:
This article describes the development of a machine learning (ML)-based algorithm for snowfall retrieval (Snow retrievaL ALgorithm fOr gpM–Cross Track… This article describes the development of a machine learning (ML)-based algorithm for snowfall retrieval (Snow retrievaL ALgorithm fOr gpM–Cross Track, SLALOM-CT), exploiting ATMS radiometer measurements and using the CloudSat CPR snowfall products as references. During a preliminary analysis, different ML techniques (tree-based algorithms, shallow and convolutional neural networks—NNs) were intercompared. A large dataset (three years) of coincident observations from CPR and ATMS was used for training and testing the different techniques. The SLALOM-CT algorithm is based on four independent modules for the detection of snowfall and supercooled droplets, and for the estimation of snow water path and snowfall rate. Each module was designed by choosing the best-performing ML approach through model selection and optimization. While a convolutional NN was the most accurate for the snowfall detection module, a shallow NN was selected for all other modules. SLALOM-CT showed a high degree of consistency with CPR. Moreover, the results were almost independent of the background surface categorization and the observation angle. The reliability of the SLALOM-CT estimates was also highlighted by the good results obtained from a direct comparison with a reference algorithm (GPROF). more
Atmosphere Climate Data Records H-SAF Method Validation

A Comprehensive Clear-Sky Database for the Development of Land Surface Temperature Algorithms

Author(s):
Ermida, Sofia L.; Trigo, Isabel F.
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 10
2022
DOI: 10.3390/rs14102329
Abstract:
Land surface temperature is linked to a wide range of surface processes. Given the increased development of earth observation systems, a large effort … Land surface temperature is linked to a wide range of surface processes. Given the increased development of earth observation systems, a large effort has been put into advancing land surface temperature retrieval algorithms from remote sensors. Due to the very limited number of reliable in situ observations matching the spatial scales of satellite observations, algorithm development relies on synthetic databases, which then constitute a crucial part of algorithm development. Here we provide a database of atmospheric profiles and respective surface conditions that can be used to train and verify algorithms for land surface temperature retrieval, including machine learning techniques. The database was built from ERA5 data resampled through a dissimilarity criterion applied to the temperature and specific humidity profiles. This criterion aims to obtain regular distributions of these variables, ensuring a good representation of all atmospheric conditions. The corresponding vertical profiles of ozone and relevant surface and vertically integrated variables are also included in the dataset. Information on the surface conditions (i.e., temperature and emissivity) was complemented with data from a wide array of satellite products, enabling a more realistic surface representation. The dataset is freely available online at Zenodo. more
Application Climate Data Records LSA-SAF Land

A CO₂-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications

Author(s):
Whitburn, S.; Clarisse, L.; Crapeau, M.; August, T.; Hultberg, T.; Coheur, P. F.; Clerbaux, C.
Publication title: Atmospheric Measurement Techniques
2022
 | Volume: 15 | Issue: 22
2022
DOI: 10.5194/amt-15-6653-2022
Abstract:
With more than 15 years of continuous and consistent measurements, the Infrared Atmospheric Sounding Interferometer (IASI) radiance dataset is becomin… With more than 15 years of continuous and consistent measurements, the Infrared Atmospheric Sounding Interferometer (IASI) radiance dataset is becoming a reference climate data record. To be exploited to its full potential, it requires a cloud filter that is accurate, unbiased over the full IASI life span and strict enough to be used in satellite data retrieval schemes. Here, we present a new cloud detection algorithm which combines (1) a high sensitivity, (2) a good consistency over the whole IASI time series and between the different copies of the instrument flying on board the suite of Metop satellites, and (3) simplicity in its parametrization. The method is based on a supervised neural network (NN) and relies, as input parameters, on the IASI radiance measurements only. The robustness of the cloud mask over time is ensured in particular by avoiding the IASI channels that are influenced by CO2, N2O, CH4, CFC-11 and CFC-12 absorption lines and those corresponding to the ν2 H2O absorption band. As a reference dataset for the training, version 6.5 of the operational IASI Level 2 (L2) cloud product is used. We provide different illustrations of the NN cloud product, including comparisons with other existing products. We find very good agreement overall with version 6.5 of the operational IASI L2 with an identical mean annual cloud amount and a pixel-by-pixel correspondence of about 87 %. The comparison with the other cloud products shows a good correspondence in the main cloud regimes but with sometimes large differences in the mean cloud amount (up to 10 %) due to the specificities of each of the different products. We also show the good capability of the NN product to differentiate clouds from dust plumes. more
Atmosphere CM-SAF Climate Data Records EUM-Secr Validation

A comparison of clustering methods for the spatial reduction of renewable electricity optimisation models of Europe

Author(s):
Frysztacki, M.M.; Recht, G.; Brown, T.
Publication title: Energy Informatics
2022
 | Volume: 5 | Issue: 1
2022
DOI: 10.1186/s42162-022-00187-7
Abstract:
Modeling the optimal design of the future European energy system involves large data volumes and many mathematical constraints, typically resulting in… Modeling the optimal design of the future European energy system involves large data volumes and many mathematical constraints, typically resulting in a significant computational burden. As a result, modelers often apply reductions to their model that can have a significant effect on the accuracy of their results. This study investigates methods for spatially clustering electricity system models at transmission level to overcome the computational constraints. Spatial reduction has a strong effect both on flows in the electricity transmission network and on the way wind and solar generators are aggregated. Clustering methods applied in the literature are typically oriented either towards preserving network flows or towards preserving the properties of renewables, but both are important for future energy systems. In this work we adapt clustering algorithms to accurately represent both networks and renewables. To this end we focus on hierarchical clustering, since it preserves the topology of the transmission system. We test improvements to the similarity metrics used in the clustering by evaluating the resulting regions with measures on renewable feed-in and electrical distance between nodes. Then, the models are optimised under a brownfield capacity expansion for the European electricity system for varying spatial resolutions and renewable penetration. Results are compared to each other and to existing clustering approaches in the literature and evaluated on the preciseness of siting renewable capacity and the estimation of power flows. We find that any of the considered methods perform better than the commonly used approach of clustering by country boundaries and that any of the hierarchical methods yield better estimates than the established method of clustering with k-means on the coordinates of the network with respect to the studied parameters. © 2022, The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

A 35-year daily global solar radiation dataset reconstruction at the Great Wall Station, Antarctica: First results and comparison with ERA5, CRA40 reanalysis, and ICDR (AVHRR) satellite products

Author(s):
Zeng, Zhaoliang; Wang, Xin; Wang, Zemin; Zhang, Wenqian; Zhang, Dongqi; Zhu, Kongju; Mai, Xiaoping; Cheng, Wei; Ding, Minghu
Publication title: Frontiers in Earth Science
2022
 | Volume: 10
2022
DOI:
Abstract:
Solar radiation drives many geophysical and biological processes in Antarctica, such as sea ice melting, ice sheet mass balance, and photosynthetic pr… Solar radiation drives many geophysical and biological processes in Antarctica, such as sea ice melting, ice sheet mass balance, and photosynthetic processes of phytoplankton in the polar marine environment. Although reanalysis and satellite products can provide important insight into the global scale of solar radiation in a seamless way, the ground-based radiation in the polar region remains poorly understood due to the harsh Antarctic environment. The present study attempted to evaluate the estimation performance of empirical models and machine learning models, and use the optimal model to establish a 35-year daily global solar radiation (DGSR) dataset at the Great Wall Station, Antarctica using meteorological observation data during 1986–2020. In addition, it then compared against the DGSR derived from ERA5, CRA40 reanalysis, and ICDR (AVHRR) satellite products. For the DGSR historical estimation performance, the machine learning method outperforms the empirical formula method overall. Among them, the Mutli2 model (hindcast test R2, RMSE, and MAE are 0.911, 1.917 MJ/m2, and 1.237 MJ/m2, respectively) for the empirical formula model and XGBoost model (hindcast test R2, RMSE, and MAE are 0.938, 1.617 MJ/m2, and 1.030 MJ/m2, respectively) for the machine learning model were found with the highest accuracy. For the austral summer half-year, the estimated DGSR agrees very well with the observed DGSR, with a mean bias of only −0.47 MJ/m2. However, other monthly DGSR products differ significantly from observations, with mean bias of 1.05 MJ/m2, 3.27 MJ/m2, and 6.90 MJ/m2 for ICDR (AVHRR) satellite, ERA5, and CRA40 reanalysis products, respectively. In addition, the DGSR of the Great Wall Station, Antarctica followed a statistically significant increasing trend at a rate of 0.14 MJ/m2/decade over the past 35 years. To our best knowledge, this study presents the first reconstruction of the Antarctica Great Wall Station DGSR spanning 1986–2020, which will contribute to the research of surface radiation balance in Antarctic Peninsula. more
Atmosphere CM-SAF Climate Data Records Cryosphere Validation

UV-Indien network: ground-based measurements dedicated to the monitoring of UV radiation over the western Indian Ocean

Author(s):
Lamy, Kevin; Portafaix, Thierry; Brogniez, Colette; Lakkala, Kaisa; Pitkänen, Mikko R. A.; Arola, Antti; Forestier, Jean-Baptiste; Amelie, Vincent; Toihir, Mohamed Abdoulwahab; Rakotoniaina, Solofoarisoa
Publication title: Earth System Science Data
2021
 | Volume: 13 | Issue: 9
2021
DOI: 10.5194/essd-13-4275-2021
Abstract:
Abstract. Within the framework of the UV-Indien network, nine ground stations have been equipped with ultraviolet broadband radiometers, five of them … Abstract. Within the framework of the UV-Indien network, nine ground stations have been equipped with ultraviolet broadband radiometers, five of them have also been equipped with an all-sky camera, and the main station in Saint-Denis de la Réunion is also equipped with a spectroradiometer. These stations are spatially distributed to cover a wide range of latitudes, longitudes, altitudes, and environmental conditions in five countries of the western Indian Ocean region (Comoros, France, Madagascar, Mauritius, and Seychelles), a part of the world where almost no measurements have been made so far. The distribution of the stations is based on the scientific interest of studying ultraviolet radiation not only in relation to atmospheric processes but also in order to provide data relevant to fields such as biology, health (prevention of skin cancer), and agriculture. The main scientific objectives of this network are to study the annual and inter-annual variability in the ultraviolet (UV) radiation in this area, to validate the output of numerical models and satellite estimates of ground-based UV measurements, and to monitor UV radiation in the context of climate change and projected ozone depletion in this region. A calibration procedure including three types of calibrations responding to the various constraints of sustaining the network has been put in place, and a data processing chain has been set up to control the quality and the format of the files sent to the various data centres. A method of clear-sky filtering of the data is also applied. Here, we present an intercomparison with other datasets, as well as several daily or monthly representations of the UV index (UVI) and cloud fraction data, to discuss the quality of the data and their range of values for the older stations (Antananarivo, Anse Quitor, Mahé, and Saint-Denis). Ground-based measurements of the UVI are used to validate satellite estimates – Ozone Monitoring Instrument (OMI), the TROPOspheric Monitoring Instrument (TROPOMI), and the Global Ozone Monitoring Experiment (GOME) – and model forecasts of UVI – Tropospheric Emission Monitoring Internet Service (TEMIS) and Copernicus Atmospheric Monitoring Service (CAMS). The median relative differences between satellite or model estimates and ground-based measurements of clear-sky UVI range between −34.5 % and 15.8 %. Under clear skies, the smallest UVI median difference between the satellite or model estimates and the measurements made by ground-based instruments is found to be 0.02 (TROPOMI), 0.04 (OMI), −0.1 (CAMS), and −0.4 (CAMS) at Saint-Denis, Antananarivo, Anse Quitor, and Mahé, respectively. The diurnal variability in UVI and cloud fraction, as well as the monthly variability in UVI, is evaluated to ensure the quality of the dataset. The data used in this study are available at https://doi.org/10.5281/zenodo.4811488 (Lamy and Portafaix, 2021a). more
AC-SAF Atmosphere Climate Data Records Validation

Upscaling Net Ecosystem Exchange Over Heterogeneous Landscapes With Machine Learning

Author(s):
Reitz, O.; Graf, A.; Schmidt, M.; Ketzler, G.; Leuchner, M.
Publication title: Journal of Geophysical Research: Biogeosciences
2021
 | Volume: 126 | Issue: 2
2021
DOI: 10.1029/2020JG005814
Abstract:
This paper discusses different feature selection methods and CO2 flux data sets with a varying quality-quantity balance for the application of a Rando… This paper discusses different feature selection methods and CO2 flux data sets with a varying quality-quantity balance for the application of a Random Forest model to predict daily CO2 fluxes at 250 m spatial resolution for the Rur catchment area in western Germany between 2010 and 2018. Measurements from eddy covariance stations of different ecosystem types, remotely sensed vegetation data from MODIS, and COSMO-REA6 reanalysis data were used to train the model and predictions were validated by a spatial and temporal validation scheme. Results show the capabilities of a backwards feature elimination to remove irrelevant variables and an importance of high-quality-low-quantity flux data set to improve predictions. However, results also show that spatial prediction is more difficult than temporal prediction by reflecting the mean value accurately though underestimating the variance of CO2 fluxes. Vegetated parts of the catchment acted as a CO2 sink during the investigation period, net capturing about 237 g C m−2 y−1. Croplands, coniferous forests, deciduous forests and grasslands were all sinks on average. The highest uptake was predicted to occur in late spring and early summer, while the catchment was a CO2 source in fall and winter. In conclusion, the Random Forest model predicted a narrower distribution of CO2 fluxes, though our methodological improvements look promising in order to achieve high-resolution net ecosystem exchange data sets at the regional scale. © 2020. The Authors. more
Atmosphere CM-SAF Climate Data Records Validation

Towards Including Dynamic Vegetation Parameters in the EUMETSAT H SAF ASCAT Soil Moisture Products

Author(s):
Steele-Dunne, Susan C.; Hahn, Sebastian; Wagner, Wolfgang; Vreugdenhil, Mariette
Publication title: Remote Sensing
2021
 | Volume: 13 | Issue: 8
2021
DOI: 10.3390/rs13081463
Abstract:
The TU Wien Soil Moisture Retrieval (TUW SMR) approach is used to produce several operational soil moisture products from the Advanced Scatterometer (… The TU Wien Soil Moisture Retrieval (TUW SMR) approach is used to produce several operational soil moisture products from the Advanced Scatterometer (ASCAT) on the Metop series of satellites as part of the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF). The incidence angle dependence of backscatter is described by a second-order Taylor polynomial, the coefficients of which are used to normalize ASCAT observations to the reference incidence angle of 40∘ and for correcting vegetation effects. Recently, a kernel smoother was developed to estimate the coefficients dynamically, in order to account for interannual variability. In this study, we used the kernel smoother for estimating these coefficients, where we distinguished for the first time between their two uses, meaning that we used a short and fixed window width for the backscatter normalisation while we tested different window widths for optimizing the vegetation correction. In particular, we investigated the impact of using the dynamic vegetation parameters on soil moisture retrieval. We compared soil moisture retrievals based on the dynamic vegetation parameters to those estimated using the current operational approach by examining their agreement, in terms of the Pearson correlation coefficient, unbiased RMSE and bias with respect to in situ soil moisture. Data from the United States Climate Research Network were used to study the influence of climate class and land cover type on performance. The sensitivity to the kernel smoother half-width was also investigated. Results show that estimating the vegetation parameters with the kernel smoother can yield an improvement when there is interannual variability in vegetation due to a trend or a change in the amplitude or timing of the seasonal cycle. However, using the kernel smoother introduces high-frequency variability in the dynamic vegetation parameters, particularly for shorter kernel half-widths. more
Climate Data Records H-SAF Land Validation

Time-dependent 3D simulations of tropospheric ozone depletion events in the Arctic spring using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem)

Author(s):
Herrmann, Maximilian; Sihler, Holger; Friess, Udo; Wagner, Thomas; Platt, Ulrich; Gutheil, Eva
Publication title: ATMOSPHERIC CHEMISTRY AND PHYSICS
2021
 | Volume: 21 | Issue: 10
2021
DOI: 10.5194/acp-21-7611-2021
Abstract:
Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using a regional model based on… Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using a regional model based on the open-source software package Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). For this purpose, the MOZART (Model for Ozone and Related chemical Tracers)-MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) chemical reaction mechanism is extended by bromine and chlorine reactions as well as an emission mechanism for reactive bromine via heterogeneous reactions on snow surfaces. The simulation domain covers an area of 5040km x 4960km, centered north of Utqiagvik (formerly Barrow), Alaska, and the time interval from February through May 2009. Several simulations for different strengths of the bromine emission are conducted and evaluated by comparison with in situ and ozone sonde measurements of ozone mixing ratios as well as by comparison with tropospheric BrO vertical column densities (VCDs) from the Global Ozone Monitoring Experiment-2 (GOME-2) satellite instrument. The base bromine emission scheme includes the direct emission of bromine due to bromide oxidation by ozone. Results of simulations with the base emission rate agree well with the observations; however, a simulation with 50% faster emissions performs somewhat better. The bromine emission due to bromide oxidation by ozone is found to be important to provide an initial seed for the bromine explosion. Bromine release due to N2O5 was found to be important from February to mid March but irrelevant thereafter. A comparison of modeled BrO with in situ and multi-axis differential optical absorption spectroscopy (MAX-DOAS) data hints at missing bromine release and recycling mechanisms on land or near coasts. A consideration of halogen chemistry substantially improves the prediction of the ozone mixing ratio with respect to the observations. Meteorological nudging is essential for a good prediction of ODEs over the 3-month period. more
AC-SAF Atmosphere Climate Data Records Validation

Thermodynamics of climate change between cloud cover, atmospheric temperature and humidity

Author(s):
Mendoza, V.; Pazos, M.; Garduño, R.; Mendoza, B.
Publication title: Scientific Reports
2021
 | Volume: 11 | Issue: 1
2021
DOI: 10.1038/s41598-021-00555-5
Abstract:
On a global and annual average, we find a parameterization in which the cloud cover increase is proportional to the mid tropospheric temperature incre… On a global and annual average, we find a parameterization in which the cloud cover increase is proportional to the mid tropospheric temperature increase, with a negative proportionality factor. If the relative humidity is conserved throughout the troposphere, a 1 °C heating (cooling) of the mid troposphere, decreases (increases) the cloud cover by 1.5 percentage points (pp). But if the relative humidity is not conserved, then the cloud cover decreases (increases) by 7.6 pp. If the shortwave reflection effect of the cloud cover is dominant on a global scale, this parameterization leads to a predominant positive feedback: if the temperature increases like in the current climate change, the cloud cover decreases and more solar radiation reaches the surface increasing the temperature even more. The contribution of the present work consists in finding that the negative sign of the proportionality factor is due to the Clausius–Clapeyron equation; that is, to the magnitude of the derivative of the saturation vapor pressure at the typical standard surface temperature of 288 K. The negative sign of the factor is independent on the conservation or non-conservation of relative humidity in the troposphere under climate change. © 2021, The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

The potential of increasing man-made air pollution to reduce rainfall over southern West Africa

Author(s):
Pante, G.; Knippertz, P.; Fink, A.H.; Kniffka, A.
Publication title: Atmospheric Chemistry and Physics
2021
 | Volume: 21 | Issue: 1
2021
DOI: 10.5194/acp-21-35-2021
Abstract:
Southern West Africa has one of the fastest-growing populations worldwide. This has led to a higher water demand and lower air quality. Over the last … Southern West Africa has one of the fastest-growing populations worldwide. This has led to a higher water demand and lower air quality. Over the last 3 decades, most of the region has experienced decreasing rainfall during the little dry season (LDS; mid-July to end of August) and more recently also during the second rainy season (SRS; September-October), while trends during the first rainy season (FRS; mid-May to mid-July) are insignificant. Here we analyse spatio-Temporal variations in precipitation, aerosol, radiation, cloud, and visibility observations from surface stations and from space to find indications for a potential contribution of anthropogenic air pollution to these rainfall trends. The proposed mechanism is that the dimming of incoming solar radiation by aerosol extinction contributes to reducing vertical instability and thus convective precipitation. To separate a potential aerosol influence from large-scale climatic drivers, a multilinear-regression model based on sea-surface temperature (SST) indices is used. During both LDS and SRS, weakly statistically significant but accelerating negative rainfall trends unrelated to known climatic factors are found. These are accompanied by a strong increase in pollution over the upstream tropical Atlantic caused by fire aerosol from Central Africa, particularly during the LDS. Over southern West Africa, no long-Term aerosol records are available, inhibiting a direct quantification of the local man-made effect. However, significant decreases in horizontal visibility and incoming surface solar radiation are strong indicators for an increasing aerosol burden, in line with the hypothesized pollution impact on rainfall. The radiation trend is further enhanced by an increase in low-level cloudiness. The large spatial extent of potentially aerosol-related trends during the LDS is consistent with the stronger monsoon flow and less wet deposition during this season. Negligible aerosol impacts during the FRS are likely due to the high degree of convective organization, which makes rainfall less sensitive to surface radiation. The overall coherent picture and the accelerating trends-some of which are concealed by SST effects-should alarm policymakers in West Africa to prevent a further increase in air pollution as this could endanger water supply and food and energy production for a large and growing population. © 2021 Copernicus GmbH. All rights reserved. more
Application Atmosphere CM-SAF Climate Data Records

The development and persistence of soil moisture stress during drought across southwestern Germany

Author(s):
Tijdeman, E.; Menzel, L.
Publication title: Hydrology and Earth System Sciences
2021
 | Volume: 25 | Issue: 4
2021
DOI: 10.5194/hess-25-2009-2021
Abstract:
The drought of 2018 in central and northern Europe showed once more the large impact that this natural hazard can have on the environment and society.… The drought of 2018 in central and northern Europe showed once more the large impact that this natural hazard can have on the environment and society. Such droughts are often seen as slowly developing phenomena. However, root zone soil moisture deficits can rapidly develop during periods lacking precipitation and meteorological conditions that favor high evapotranspiration rates. These periods of soil moisture stress can persist for as long as the meteorological drought conditions last, thereby negatively affecting vegetation and crop health. In this study, we aim to characterize past soil moisture stress events over the croplands of southwestern Germany and, furthermore, to relate the characteristics of these past events to different soil and climate properties.We first simulated daily soil moisture over the period 1989 2018 on a 1 km resolution grid, using the physically based hydrological model TRAIN. We then derived various soil moisture stress characteristics, including probability, development time, and persistence, from the simulated time series of all agricultural grid cells (n 15000). Logistic regression and correlation were then applied to relate the derived characteristics to the plant-Available storage capacity of the root zone and to the climatological setting. Finally, sensitivity analyses were carried out to investigate how results changed when using a different parameterization of the root zone, i.e., soil based or fixed, or when assessing soil moisture drought (anomaly) instead of stress. Results reveal that the majority of agricultural grid cells across the study region reached soil moisture stress during prominent drought years. The development time of these soil moisture stress events varied substantially, from as little as 10 d to over 4 months. The persistence of soil moisture stress varied as well and was especially high for the drought of 2018. A strong control on the probability and development time of soil moisture stress was found to be the storage capacity of the root zone, whereas the persistence was not strongly linearly related to any of the considered controls. On the other hand, the sensitivity analyses revealed the increased control of climate on soil moisture stress characteristics when using a fixed instead of a soil-based root zone storage. Thus, the strength of different controls depends on the assumptions made during modeling. Nonetheless, the storage capacity of the root zone, whether it is a characteristic of the soil or a difference between a shallow or deep rooting crop, remains an important control on soil moisture stress characteristics. This is different for SM drought characteristics, which have little or contrasting relation with the storage capacity of the root zone. Overall, the results give insight to the large spatial and temporal variability in soil moisture stress characteristics and suggest the importance of considering differences in root zone soil storage for agricultural drought assessments. © 2021 Copernicus GmbH. All rights reserved. more
Application Atmosphere CM-SAF Climate Data Records

The assimilation of microwave humidity sounder observations in all-sky conditions

Author(s):
Candy, B.; Migliorini, S.
Publication title: Quarterly Journal of the Royal Meteorological Society
2021
 | Volume: 147 | Issue: 739
2021
DOI: 10.1002/qj.4115
Abstract:
Numerical weather prediction (NWP) schemes use a wide variety of satellite observations to help constrain atmospheric analyses. Passive microwave humi… Numerical weather prediction (NWP) schemes use a wide variety of satellite observations to help constrain atmospheric analyses. Passive microwave humidity data from channels operating in the water vapour band at 183 GHz, such as those on the Microwave Humidity Sounder (MHS), are an important component of the satellite observing network. At this frequency the observations are very sensitive to scattering from ice crystals and, until recently, quality-control tests were used at the Met Office to exclude assimilation of these data in regions of strong scattering such as thick cirrus clouds. In the work described here we report on improvements to the pre-processing and assimilation of MHS data within the global NWP scheme at the Met Office, with the goal of utilising the data in scenes where liquid and ice cloud strongly affect the radiances. These improvements include the introduction of an observation operator that models the effects of ice scattering, and a scene-dependent observation error model. The error model is based on the estimated cloud ice and cloud liquid in the field of view. The new scheme has increased observation usage of MHS data over ocean by up to 40%. Trials have shown benefits to forecasts in both boreal summer and winter seasons. In the boreal summer period, for example, low-level wind forecast errors have improved in the Northern Hemisphere extratropics by up to 0.6%. Also, our experiments show evidence of significant improvements to the fit between observations and short-range forecasts for humidity-sensitive channels operating in both the microwave and infrared regions of the electromagnetic spectrum. © 2021 Crown copyright. Quarterly Journal of the Royal Meteorological Society © 2021 Royal Meteorological Society. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. more
Atmosphere Method NWP-SAF Software for CDR development

Ten Years of Satellite Infrared Radiance Monitoring With the Met Office NWP Model

Author(s):
Saunders, Roger W.; Blackmore, Thomas A.; Candy, Brett; Francis, Peter N.; Hewison, Tim J.
Publication title: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2021
 | Volume: 59 | Issue: 6
2021
DOI: 10.1109/TGRS.2020.3015257
Abstract:
Satellite sounder infrared radiances are among the most important contributions to the global observing system and have been assimilated into global n… Satellite sounder infrared radiances are among the most important contributions to the global observing system and have been assimilated into global numerical weather prediction (NWP) analyses for many years. They are also used as fundamental climate data records for climate monitoring. Prior to assimilation or producing climate records, the radiances should have all residual instrument biases removed. One way of estimating the mean biases is to continuously monitor the measured radiances against the NWP model equivalent radiances. This article is an extension of one published in 2012 which documented these biases for three years but now the time span of the monitoring has extended to beyond ten years, allowing the long-term stability of the instruments to be assessed. Data from high-resolution infrared sounder (HIRS), Advanced Along Track Scanning Radiometer (AATSR), and Spinning Enhanced Visible and Infrared Imager (SEVIRI), radiometers; atmospheric infrared sounder (AIRS), a spectrometer; and infrared atmospheric sounding interferometer (IASI), an interferometer, were included. Changes in mean biases and standard deviations were used to investigate the temporal stability of the bias and radiometric noise of the instruments over ten years. A double difference technique was employed to remove the effect of changes or deficiencies in the NWP system and radiative transfer (RT) model, which can contribute to the biases. The IASI and AIRS radiances were stable but with a different bias between the two instruments due to different versions of the RT model used. The SEVIRI radiometers were stable in most channels with the exception of the 13.4 mu m channel. The HIRS instruments were subject to sudden changes in bias and increases in standard deviation compared with NWP simulations during the past decade. more
Application Atmosphere NWP-SAF Software for CDR development

Techno-Economic Feasibility of Grid-Connected Solar PV System at Near East University Hospital, Northern Cyprus

Author(s):
Kassem, Youssef; Gokcekus, Hueseyin; Guvensoy, Ali
Publication title: ENERGIES
2021
 | Volume: 14 | Issue: 22
2021
DOI: 10.3390/en14227627
Abstract:
The growth of populations and economy in Northern Cyprus has led to continuing utilization of fossil fuels as the primary source of electricity, which… The growth of populations and economy in Northern Cyprus has led to continuing utilization of fossil fuels as the primary source of electricity, which will raise environmental pollution. Thus, utilizing renewable energy, particularly solar energy, might be a solution to minimize this issue. This paper presents the potential of grid-connected solar PV power generation at Near East University Hospital (NEU Hospital), one of the largest and leading medical facilities in Northern Cyprus, to meet the energy demand during the daytime to reduce energy bills. For this purpose, the first objective of the study is to evaluate the solar energy potential as a power source for the NEU Hospital based on four datasets (actual measurement, Satellite Application Facility on Climate Monitoring (CMSAF), Surface Radiation Data Set-Heliosat (SARAH), and ERA-5, produced by the European Centre for Medium-range Weather Forecast). The results showed that the solar resource of the selected location is categorized as excellent (class 5), that is, the global solar radiation is within the range of 1843.8-2035.9 kWH/m(2). The second objective is to investigate the impact of orientation angles on PV output, capacity factor, economic feasibility indicators, and CO2 emissions by using different PV modules. The results are compared with optimum orientation angles found by Photovoltaic Geographical Information System (PVGIS) simulation software. This objective was achieved by using RETScreen Expert software. The results demonstrated that the highest performance of the proposed system was achieved for orientation angles of 180 & DEG; (azimuth angle) and -35 & DEG; (tilt angle). Consequently, it is recommended that orientation angles, PV modules, and market prices are considered to maximize energy production and reduce electricity production costs. more
Atmosphere CM-SAF Climate Data Records Validation

State of the Climate in 2020

Author(s):
Blunden, J.; Boyer, T.
Publication title: Bulletin of the American Meteorological Society
2021
 | Volume: 102 | Issue: 8
2021
DOI: 10.1175/2021BAMSStateoftheClimate.1
Abstract:
In 2020, the dominant greenhouse gases stored in Earth’s atmosphere continued to increase. The annual global average carbon dioxide (CO2) concentratio… In 2020, the dominant greenhouse gases stored in Earth’s atmosphere continued to increase. The annual global average carbon dioxide (CO2) concentration at Earth’s surface was 412.5 ± 0.1 ppm, an increase of 2.5 ± 0.1 ppm over 2019, and the high-est in the modern instrumental record and in ice core records dating back 800,000 years. While anthropogenic CO2 emissions were estimated to decrease around 6%–7% globally during the year due to reduced human activities during the COVID-19 pan-demic, the reduction did not materially affect atmospheric CO2accumulation as it is a relatively small change, less even than interannual variability driven by the terrestrial biosphere. The net global uptake of ~3.0 petagrams of anthropogenic carbon by oceans in 2020 was the highest in the 39-year record and almost 30% higher than the 1999–2019 average. Weak El Niño-like conditions in the eastern equatorial Pacific Ocean in early 2020 cooled and transitioned to a moderate La Niña later in the year. Even so, the annual global surface tem-perature across land and oceans was among the three highest in records dating to the mid- to late 1800s. In Europe, 17 countries reported record high annual mean temperatures, contributing to the warmest year on record for the European continent. Elsewhere, Japan, Mexico, and Seychelles also experienced re-cord high annual mean temperatures. In the Caribbean, Aruba, Martinique, and St. Lucia reported their all-time monthly maximum temperatures. In the United States, Furnace Creek in Death Valley, California, reached 54.4°C on 16 August—the hottest temperature measured on Earth since 1931, pending confirma-tion. North of 60°N, the annual mean temperature over Arctic land areas was 2.1°C above the 1981–2010 average, the highest in the 121-year record. On 20 June, a temperature of 38°C was observed at Verkhoyansk, Russia (67.6°N), provisionally the highest temperature ever measured within the Arctic Circle. Near the opposite pole, an atmospheric river—a long, nar-row region in the atmosphere that transports heat and moisture from sub-tropical and midlatitudes—brought extreme warmth from sub-tropical and midlatitudes to parts of Antarctica during austral summer. On 6 February, Esperanza Station recorded a temperature of 18.3°C, the highest temperature recorded on the continent, surpassing the previous record set in 2015 by 1.1°C. The warmth also led to the largest late-summer surface melt event in the 43-year record, affecting more than 50% of the Antarctic Peninsula. In August, daily sea ice extent in the waters surrounding Antarctica shifted from below to above average, marking the end of persistent below-average sea ice extent since austral spring 2016.In the Arctic, when sea ice reached its annual maximum extent in March, thin, first-year ice comprised ~70% of the ice; the thickest ice, which is usually more than four years old, had declined by more than 86% since 1985 to make up just 2% of total ice in 2020. When the minimum sea ice extent was reached in September, it was the second smallest except for 2012 in the 42-year satellite record. The Northern Sea Route along the Siberian coast was open for about 2.5 months, from late July through mid-October, compared to less than a month typically.Glaciers across the global cryosphere lost mass for the 33rd consecutive year, and permafrost temperatures continued to reach record highs at many high latitude and mountain locations. In the Northern Hemisphere, lakes froze three days later and thawed 5.5 days earlier on average. In Finland, the average duration of lake ice was 42 days shorter. Record high spring temperatures in central Siberia drove rapid snow melt that contributed to the lowest June snow cover extent across Eurasia in the 54-year record. As is typical, some areas around the world were notably dry in 2020 and some were notably wet. The Middle East experienced an extreme drought during autumn, with most places reporting no precipitation in October. In South America, the Bolivian lowlands suffered one of its most severe droughts on record during autumn. Drought also spanned the Chaco and Pantanal in Bolivia, Paraguay, and southern Brazil. The Paraguay River shrank to its lowest levels in half a century. A decadal “mega drought” in south-central Chile continued through its 11th year, with extreme conditions in the most populated areas. Argentina reported its driest year since 1995. In North America, drought continued to prevail in the West. The lack of moisture in drought-stricken regions often pro-vide ideal conditions for fire. Total fire emissions in the western United States in 2020 were almost three times higher than the 2003–10 mean. The Arctic experienced its highest fire year in terms of carbon emitted into the atmosphere, surpassing the record set in 2019 by 34%, with most of the fires occurring in Arctic Asia. In the tropics, the Amazon saw its highest fire activity since 2012, while fire activity in tropical Asia—including Indonesia—was one of the lowest on record, related to wet conditions as La Niña evolved during the fire season. The 2020 Southwest Asian Monsoon season (June–September) was the wettest since 1981, also coincident with the emergence of La Niña. The Meiyu rainy season, which usually occurs between July and August over the Yangtze and Huaihe River Valleys of China, was extended by two months in 2020. The May–October total rainfall averaged over the area was the most since the start of the record in 1961. Associated severe flooding affected about 45.5 million people. A widespread desert locust infestation during 2019–20 impacted equatorial and northern East Africa, as heavy rains and prevailing winds were favorable for breeding and movement of swarms across Kenya, Ethiopia, northeastern Somalia, Uganda, South Sudan, and northern Tanzania. The massive infestation destroyed thousands of square kilometers of cropland and pasture lands, resulting in one million people in need of food aid in Ethiopia alone. Extremely heavy rains in April also trig-gered widespread flooding and landslides in Ethiopia, Somalia, Rwanda, and Burundi. The Lake Victoria region was the wettest in its 40-year record. Across the global oceans, the average ocean heat content reached a record high in 2020 and the sea surface temperature was the third highest on record, surpassed only by 2016 and 2019. Approximately 84% of the ocean surface experienced at least one marine heatwave (MHW) in 2020. For the second time in the past decade, a major MHW developed in the northeast Pacific, covering an area roughly six times the size of Alaska in September. Global mean sea level was record high for the ninth consecutive year, reaching 91.3 mm above the 1993 average when satellite measurements began, an increase of 3.5 mm over 2019. Melting of the Greenland Ice Sheet accounted for about 0.8 mm of the sea level rise, with an overall loss of 293 ± 66 gigatons of ice.A total of 102 named tropical storms were observed during the Northern and Southern Hemisphere storm seasons, well above the 1981–2010 average of 85. In the North Atlantic, a record 30 tropical cyclones formed, surpassing the previous record of 28 in 2005. Major Hurricanes Eta and Iota made landfall along the eastern coast of Nicaragua in nearly the same location within a two-week period, impacting over seven million people across Central America. In the western North Pacific, Super Typhoon Goni was the strongest tropical cyclone to make landfall in the historical record and led to the evacuation of almost 1 million people in the Philippines. Very Severe Cyclonic Storm Gati was the strongest recorded cyclone to make landfall over Somalia. Bosaso, in northeast Somalia, received 128 mm of rainfall in a 24-hour period, exceeding the city’s average annual total of 100 mm.Above Earth’s surface, the annual lower troposphere temperature equaled 2016 as the highest on record, while stratospheric temperatures continued to decline. In 2020, the stratospheric winter polar vortices in both hemispheres were unusually strong and stable. Between December 2019 and March 2020, the Arctic polar vortex was the strongest since the beginning of the satellite era, contributing to record low stratospheric ozone levels in the region that lasted into spring. The anomalously strong and persistent Antarctic polar vortex was linked to the longest-lived, and 12th-largest, ozone hole over the region, which lasted to the end of December. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Spatial heterogeneity in dead sea surface temperature associated with inhomogeneity in evaporation

Author(s):
Kishcha, P.; Starobinets, B.
Publication title: Remote Sensing
2021
 | Volume: 13 | Issue: 1
2021
DOI: 10.3390/rs13010093
Abstract:
Spatial heterogeneity in Dead Sea surface temperature (SST) was pronounced throughout the daytime, based on METEOSAT geostationary satellite data (200… Spatial heterogeneity in Dead Sea surface temperature (SST) was pronounced throughout the daytime, based on METEOSAT geostationary satellite data (2005–2015). In summer, SST peaked at 13 LT (local time), when SST reached 38.1◦ C, 34.1◦ C, and 35.4◦ C being averaged over the east, middle, and west parts of the lake, respectively. In winter, daytime SST heterogeneity was less pronounced than that in summer. As the characteristic feature of the diurnal cycle, the SST daily temperature range (the difference between daily maxima and minima) was equal to 7.2◦ C, 2.5◦ C, and 3.8◦ C over the east, middle, and west parts of the Dead Sea, respectively, in summer, compared to 5.3◦ C, 1.2◦ C, and 2.3◦ C in winter. In the presence of vertical water mixing, the maximum of SST should be observed several hours later than that of land surface temperature (LST) over surrounding land areas due to thermal inertia of bulk water. However, METEOSAT showed that, in summer, maxima of SST and LST were observed at the same time, 13 LT. This fact is evidence that there was no noticeable vertical water mixing. Our findings allowed us to consider that, in the absence of water mixing and under uniform solar radiation in the summer months, spatial heterogeneity in SST was associated with inhomogeneity in evaporation. Maximal evaporation (causing maximal surface water cooling) took place at the middle part of the Dead Sea, while minimum evaporation took place at the east side of the lake. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. more
Application Atmosphere CM-SAF Climate Data Records

Spatial Correlation Length Scales of Sea-Ice Concentration Errors for High-Concentration Pack Ice

Author(s):
Kern, Stefan
Publication title: REMOTE SENSING
2021
 | Volume: 13 | Issue: 21
2021
DOI: 10.3390/rs13214421
Abstract:
The European Organisation for the Exploitation of Meteorological Satellites-Ocean and Sea Ice Satellite Application Facility-European Space Agency-Cli… The European Organisation for the Exploitation of Meteorological Satellites-Ocean and Sea Ice Satellite Application Facility-European Space Agency-Climate Change Initiative (EUMETSAT-OSISAF-ESA-CCI) Level-4 sea-ice concentration (SIC) climate data records (CDRs), named SICCI-25km, SICCI-50km and OSI-450, provide gridded SIC error estimates in addition to SIC. These error estimates, called total error henceforth, comprise a random, uncorrelated error contribution from retrieval and sensor noise, aka the algorithm standard error, and a locally-to-regionally correlated contribution from gridding and averaging Level-2 SIC into the Level-4 SIC CDRs, aka the representativity error. However, these CDRs do not yet provide an error covariance matrix. Therefore, correlation scales of these error contributions and the total error in particular are unknown. In addition, larger-scale SIC errors due to, e.g., unaccounted weather influence or mismatch between the actual ice type and the algorithm setup are neither well represented by the total error, nor are their correlation scales known for these CDRs. In this study, I attempt to contribute to filling this knowledge gap by deriving spatial correlation length scales for the total error and the large-scale SIC error for high-concentration pack ice. For every grid cell with > 90% SIC, I derive circular one-point correlation maps of 1000 km radius by computing the cross-correlation between the central 31-day time series of the errors and all other 31-day error time series within that circular area (disc) with 1000 km radius. I approximate the observed decrease in the correlation away from the disc's center with an exponential function that best fits this decrease and thereby obtain the correlation length scale L sought. With this approach, I derive L separately for the total error and the large-scale SIC error for every high-concentration grid cell, and map, present and discuss these for the Arctic and the Southern Ocean for the year 2010 for the above-mentioned products. I find correlation length scales are substantially smaller for the total error, mostly below ∼200 km, than the SIC error, ∼200 km to ∼700 km, in both hemispheres. I observe considerable spatiotemporal variability of the SIC error correlation length scales in both hemispheres and provide first directions to explain these. For SICCI-50km, I present the first evidence of the method's robustness for other years and time series of L for 2003-2010. more
Climate Data Records Cryosphere OSI-SAF Validation

Sixteen Years of Measurements of Ozone over Athens, Greece with a Brewer Spectrophotometer

Author(s):
Eleftheratos, Kostas; Kouklaki, Dimitra; Zerefos, Christos
Publication title: Oxygen
2021
 | Volume: 1 | Issue: 1
2021
DOI: 10.3390/oxygen1010005
Abstract:
Sixteen years (July 2003–July 2019) of ground-based measurements of total ozone in the urban environment of Athens, Greece, are analyzed in this work.… Sixteen years (July 2003–July 2019) of ground-based measurements of total ozone in the urban environment of Athens, Greece, are analyzed in this work. Measurements were acquired with a single Brewer monochromator operating on the roof of the Biomedical Research Foundation of the Academy of Athens since July 2003. We estimate a 16-year climatological mean of total ozone in Athens of about 322 DU, with no significant change since 2003. Ozone data from the Brewer spectrophotometer were compared with TOMS, OMI, and GOME-2A satellite retrievals. The results reveal excellent correlations between the ground-based and satellite ozone measurements greater than 0.9. The variability of total ozone over Athens related to the seasonal cycle, the quasi biennial oscillation (QBO), the El Nino Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the 11-year solar cycle, and tropopause pressure variability is presented. more
AC-SAF Application Atmosphere Climate Data Records

Seasonal Arctic sea ice forecasting with probabilistic deep learning

Author(s):
Andersson, T.R.; Hosking, J.S.; Pérez-Ortiz, M.; Paige, B.; Elliott, A.; Russell, C.; Law, S.; Jones, D.C.; Wilkinson, J.; Phillips, T.; Byrne, J.; Tietsche, S.; Sarojini, B.B.; Blanchard-Wrigglesworth, E.; Aksenov, Y.; Downie, R.; Shuckburgh, E.
Publication title: Nature Communications
2021
 | Volume: 12 | Issue: 1
2021
DOI: 10.1038/s41467-021-25257-4
Abstract:
Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and… Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss. © 2021, The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF

Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model

Author(s):
Im, U.; Tsigaridis, K.; Faluvegi, G.; Langen, P.L.; French, J.P.; Mahmood, R.; Thomas, M.A.; Von Salzen, K.; Thomas, D.C.; Whaley, C.H.; Klimont, Z.; Skov, H.; Brandt, Jø.
Publication title: Atmospheric Chemistry and Physics
2021
 | Volume: 21 | Issue: 13
2021
DOI: 10.5194/acp-21-10413-2021
Abstract:
The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In… The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In order to study the effects of atmospheric aerosols in this warming, recent past (1990-2014) and future (2015-2050) simulations have been carried out using the GISS-E2.1 Earth system model to study the aerosol burdens and their radiative and climate impacts over the Arctic (>60 N), using anthropogenic emissions from the Eclipse V6b and the Coupled Model Intercomparison Project Phase 6 (CMIP6) databases, while global annual mean greenhouse gas concentrations were prescribed and kept fixed in all simulations. Results showed that the simulations have underestimated observed surface aerosol levels, in particular black carbon (BC) and sulfate (SO42-), by more than 50%, with the smallest biases calculated for the atmosphere-only simulations, where winds are nudged to reanalysis data. CMIP6 simulations performed slightly better in reproducing the observed surface aerosol concentrations and climate parameters, compared to the Eclipse simulations. In addition, simulations where atmosphere and ocean are fully coupled had slightly smaller biases in aerosol levels compared to atmosphere-only simulations without nudging. Arctic BC, organic aerosol (OA), and SO42- burdens decrease significantly in all simulations by 10%-60% following the reductions of 7%-78% in emission projections, with the Eclipse ensemble showing larger reductions in Arctic aerosol burdens compared to the CMIP6 ensemble. For the 2030-2050 period, the Eclipse ensemble simulated a radiative forcing due to aerosol-radiation interactions (RFARI) of -0.39±0.01Wm-2, which is -0.08Wm-2 larger than the 1990-2010 mean forcing (-0.32Wm-2), of which -0.24±0.01Wm-2 was attributed to the anthropogenic aerosols. The CMIP6 ensemble simulated a RFARI of -0.35 to -0.40Wm-2 for the same period, which is -0.01 to -0.06Wm-2 larger than the 1990-2010 mean forcing of -0.35Wm-2. The scenarios with little to no mitigation (worst-case scenarios) led to very small changes in the RFARI, while scenarios with medium to large emission mitigations led to increases in the negative RFARI, mainly due to the decrease in the positive BC forcing and the decrease in the negative SO42- forcing. The anthropogenic aerosols accounted for -0.24 to -0.26Wm-2 of the net RFARI in 2030-2050 period, in Eclipse and CMIP6 ensembles, respectively. Finally, all simulations showed an increase in the Arctic surface air temperatures throughout the simulation period. By 2050, surface air temperatures are projected to increase by 2.4 to 2.6C in the Eclipse ensemble and 1.9 to 2.6C in the CMIP6 ensemble, compared to the 1990-2010 mean. Overall, results show that even the scenarios with largest emission reductions leads to similar impact on the future Arctic surface air temperatures and sea-ice extent compared to scenarios with smaller emission reductions, implying reductions of greenhouse emissions are still necessary to mitigate climate change. © Copyright: more
Atmosphere CM-SAF Climate Data Records Validation

Precipitation efficiency of cloud and its influencing factors over the Tibetan plateau

Author(s):
Zhao, P.; Xiao, H.; Liu, J.; Zhou, Y.
Publication title: International Journal of Climatology
2021
2021
DOI: 10.1002/joc.7251
Abstract:
The basic characteristics of cloud water, precipitation, and the dependence of precipitation efficiency (PE) on the influencing factors over the Tibet… The basic characteristics of cloud water, precipitation, and the dependence of precipitation efficiency (PE) on the influencing factors over the Tibetan Plateau (TP) are investigated. Results found that the liquid water path shows a significant downward trend in winter over the TP, and the ice water path shows a significant upward trend in the pre-monsoon and winter seasons and a significant downward trend in the monsoon season in the western TP from 1998 to 2015. In the eastern TP, the precipitation in the monsoon season also shows a significant downward trend, which may be related to the weakening of the South Asian monsoon. Results have determined that precipitation depends more on the ice water cloud than on the liquid water cloud over the TP. Moreover, the convective available potential energy (CAPE) and the low-tropospheric relative humidity (RH) are two environmental factors that have a prominent influence on the PE. During the monsoon season, higher CAPE and RH were conducive to a larger PE over the TP. The results suggest that the CAPE has a positive effect on the PE, which means that the PE is directly dependent on the convective precipitation, mainly due to the frequent convective activity and dominant convective precipitation over the TP. © 2021 Royal Meteorological Society more
Application Atmosphere CM-SAF Climate Data Records

Nitrogen dioxide decline and rebound observed by GOME-2 and TROPOMI during COVID-19 pandemic

Author(s):
Liu, Song; Valks, Pieter; Beirle, Steffen; Loyola, Diego G.
Publication title: Air Quality, Atmosphere & Health
2021
2021
DOI: 10.1007/s11869-021-01046-2
Abstract:
Since its first confirmed case in December 2019, coronavirus disease 2019 (COVID-19) has become a worldwide pandemic with more than 90 million confirm… Since its first confirmed case in December 2019, coronavirus disease 2019 (COVID-19) has become a worldwide pandemic with more than 90 million confirmed cases by January 2021. Countries around the world have enforced lockdown measures to prevent the spread of the virus, introducing a temporal change of air pollutants such as nitrogen dioxide (NO2) that are strongly related to transportation, industry, and energy. In this study, NO2 variations over regions with strong responses to COVID-19 are analysed using datasets from the Global Ozone Monitoring Experiment-2 (GOME-2) sensor aboard the EUMETSAT Metop satellites and TROPOspheric Monitoring Instrument (TROPOMI) aboard the EU/ESA Sentinel-5 Precursor satellite. The global GOME-2 and TROPOMI NO2 datasets are generated at the German Aerospace Center (DLR) using harmonized retrieval algorithms; potential influences of the long-term trend and seasonal cycle, as well as the shortterm meteorological variation, are taken into account statistically. We present the application of the GOME-2 data to analyze the lockdown-related NO2 variations for morning conditions. Consistent NO2 variations are observed for the GOME-2 measurements and the early afternoon TROPOMI data: regions with strong social responses to COVID-19 in Asia, Europe, North America, and South America show strong NO2 reductions of ∼30–50% on average due to restriction of social and economic activities, followed by a gradual rebound with lifted restriction measures. more
AC-SAF Application Atmosphere Climate Data Records

MICRU: an effective cloud fraction algorithm designed for UV-vis satellite instruments with large viewing angles

Author(s):
Sihler, Holger; Beirle, Steffen; Doerner, Steffen; de Vries, Marloes Gutenstein-Penning; Hoermann, Christoph; Borger, Christian; Warnach, Simon; Wagner, Thomas
Publication title: ATMOSPHERIC MEASUREMENT TECHNIQUES
2021
 | Volume: 14 | Issue: 6
2021
DOI: 10.5194/amt-14-3989-2021
Abstract:
Clouds impact the radiative transfer of the Earth's atmosphere and strongly influence satellite measurements in the ultraviolet-visible (UV-vis) and i… Clouds impact the radiative transfer of the Earth's atmosphere and strongly influence satellite measurements in the ultraviolet-visible (UV-vis) and infrared (IR) spectral ranges. For satellite measurements of trace gases absorbing in the UV-vis spectral range, particularly clouds ultimately determine the vertical sensitivity profile, mainly by reducing the sensitivity for trace-gas columns below the cloud. The Mainz iterative cloud retrieval utilities (MICRU) algorithm is specifically designed to reduce the error budget of trace-gas retrievals, such as those for nitrogen dioxide (NO2), which strongly depends on the accuracy of small cloud fractions (CFs) in particular. The accuracy of MICRU is governed by an empirical parameterisation of the viewing-geometry-dependent background surface reflectivity taking instrumental and physical effects into account. Instrumental effects are mainly degradation and polarisation effects; physical effects are due to the anisotropy of the surface reflectivity, e.g. shadowing of plants and sun glitter. MICRU is applied to main science channel (MSC) and polarisation measurement device (PMD) data collected between April 2007 and June 2013 by the Global Ozone Monitoring Experiment 2A (GOME-2A) instrument aboard the MetOp-A satellite. CFs are retrieved at different spectral bands between 374 and 758 nm. The MICRU results for MSC and PMD at different wavelengths are intercompared to study CF precision and accuracy, which depend on wave-length and spatial correlation. Furthermore, MICRU results are compared to FRESCO (fast retrieval scheme for clouds from the oxygen A band) and OCRA (optical cloud recognition algorithm) operational cloud products. We show that MICRU retrieves small CFs with an accuracy of 0.04 or better for the entire 1920 km wide swath with a potential bias between -0.01 and -0.03. CFs retrieved at shorter wavelengths are less affected by adverse surface heterogeneities. The comparison to the operational CF algorithms shows that MICRU significantly reduces the dependence on viewing angle, time, and sun glitter. Systematic effects along coasts are particularly small for MICRU due to its dedicated treatment of land and ocean surfaces. The MICRU algorithm is designed for spectroscopic instruments ranging from the GOME to Sentinel-5P/Tropospheric Monitoring Instrument (TROPOMI) but is also applicable to UV-vis imagers like the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and Sentinel-2. more
AC-SAF Application Atmosphere Climate Data Records

Merging high-resolution satellite surface radiation data with meteorological sunshine duration observations over China from 1983 to 2017

Author(s):
Feng, F.; Wang, K.
Publication title: Remote Sensing
2021
 | Volume: 13 | Issue: 4
2021
DOI: 10.3390/rs13040602
Abstract:
Surface solar radiation (Rs ) is essential to climate studies. Thanks to long-term records from the Advanced Very High-Resolution Radiometers (AVHRR),… Surface solar radiation (Rs ) is essential to climate studies. Thanks to long-term records from the Advanced Very High-Resolution Radiometers (AVHRR), the recent release of International Satellite Cloud Climatology Project (ISCCP) HXG cloud products provide a promising opportunity for building long-term Rs data with high resolutions (3 h and 10 km). In this study, we compare three satellite Rs products based on AVHRR cloud products over China from 1983 to 2017 with direct observations of Rs and sunshine duration (SunDu)-derived Rs . The results show that SunDu-derived Rs have higher accuracy than the direct observed Rs at time scales of a month or longer by comparing with the satellite Rs products. SunDu-derived Rs is available from the 1960s at more than 2000 stations over China, which provides reliable decadal estimations of Rs . However, the three AVHRR-based satellite Rs products have significant biases in quantifying the trend of Rs from 1983 to 2016 (−4.28 W/m2/decade to 2.56 W/m2/decade) due to inhomogeneity in satellite cloud products and the lack of information on atmospheric aerosol optical depth. To adjust the inhomogeneity of the satellite Rs products, we propose a geographically weighted regression fusion method (HGWR) to merge ISCCP-HXG Rs with SunDu-derived Rs . The merged Rs product over China from 1983 to 2017 with a spatial resolution of 10 km produces nearly the same trend as that of the SunDu-derived Rs . This study makes a first attempt to adjust the inhomogeneity of satellite Rs products and provides the merged high-resolution Rs product from 1983 to 2017 over China, which can be downloaded freely. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. more
Atmosphere CM-SAF Climate Data Records Validation

Life Cycle of Shallow Marine Cumulus Clouds From Geostationary Satellite Observations

Author(s):
Seelig, Torsten; Deneke, Hartwig; Quaas, Johannes; Tesche, Matthias
Publication title: JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
2021
 | Volume: 126 | Issue: 22
2021
DOI: 10.1029/2021JD035577
Abstract:
An analysis of the life cycle of shallow marine cumulus clouds is presented based on geostationary observations by the Spinning Enhanced Visible and I… An analysis of the life cycle of shallow marine cumulus clouds is presented based on geostationary observations by the Spinning Enhanced Visible and InfraRed Imager aboard Meteosat Second Generation (MSG-SEVIRI). Trajectories of about 250,000 individual shallow marine cumulus clouds have been derived by applying Particle Image Velocimetry to the Satellite Application Facility on Climate Monitoring CLoud property dAtAset using SEVIRI for a region in the trade wind zone centered around the Canary Islands in August 2015. The temporal evolution of the physical properties of these clouds allows to characterize cloud development and to infer the distribution of cloud life time and cloud extent. In the derived data set, the life time distribution follows a double power law with most clouds existing on a time scale of tens of minutes. The cloud physical properties, available during daytime, are analyzed along the cloud tracks. Relative time series of cloud extent, cloud water path, cloud droplet effective radius at cloud top, cloud optical thickness, and cloud droplet number concentration for clouds in two temporal ranges reveal conditions that can be attributed to long-lasting clouds. Clouds of a certain horizontal extent and cloud top height as well as cloud droplet radius show longer life times if they are optically more dense, i.e., have a higher droplet number concentration. Furthermore, the investigation of the content of liquid cloud water regarding cloud life time and cloud extent shows that small short-living clouds significantly contribute to cloud radiative effects. more
Application Atmosphere CM-SAF Climate Data Records

Intraseasonal and synoptic climate variability of surface solar radiation over South-West Indian Ocean: Regional climate modelling

Author(s):
Li, Peng; Li, Qi
Publication title: INTERNATIONAL JOURNAL OF CLIMATOLOGY
2021
2021
DOI: 10.1002/joc.7476
Abstract:
The abundant surface solar radiation (SSR) over South-West Indian Ocean (SWIO) presents significant temporal variability. To characterize this tempora… The abundant surface solar radiation (SSR) over South-West Indian Ocean (SWIO) presents significant temporal variability. To characterize this temporal variability is important for the application of solar energy, such as photovoltaic industry. This article studied the intraseasonal and synoptic climate variability of SSR by regional climate modelling over SWIO region. The regional climate model, RegCM4's skill is first evaluated through analysing the seasonal mean SSR with the precipitation, near surface temperature and total cloud cover in austral summer and winter. The basic validation of those simulated parameters with the reference data showed model's performance on SSR. The austral summer (November-February) 1999-2008 was chosen to search the Madden-Julian Oscillation patterns and tropical temperate troughs which are the major expression of intraseasonal and synoptic climate variability. The circulation, moisture fluxes, and radiation fluxes have been checked at the beginning for RegCM4's input dataset (ERA-Interim) to find the signals. Then, the output simulation results were taking into account to see if the model can reproduce the intraseasonal and synoptic climate variability or not. SSR from SARAH-E (CM SAF@5 km) as the reference dataset in the end has been used to validate the simulated patterns, which showed that the eastward SSR anomalies propagation and negative SSR anomalies bands can be observed in RegCM4 and the according satellite dataset. These results identified and explained SSR's intraseasonal and synoptic climate variability over SWIO region, which provide a way through RegCM to perform SSR's evaluation and prediction. more
Application Atmosphere CM-SAF Climate Data Records

Introducing hydrometeor orientation into all-sky microwave and submillimeter assimilation

Author(s):
Barlakas, V.; Geer, A.J.; Eriksson, P.
Publication title: Atmospheric Measurement Techniques
2021
 | Volume: 14 | Issue: 5
2021
DOI: 10.5194/amt-14-3427-2021
Abstract:
Numerical weather prediction systems still employ many simplifications when assimilating microwave radiances under all-sky conditions (clear sky, clou… Numerical weather prediction systems still employ many simplifications when assimilating microwave radiances under all-sky conditions (clear sky, cloudy, and precipitation). For example, the orientation of ice hydrometeors is ignored, along with the polarization that this causes. We present a simple approach for approximating hydrometeor orientation, requiring minor adaption of software and no additional calculation burden. The approach is introduced in the RTTOV (Radiative Transfer for TOVS) forward operator and tested in the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). For the first time within a data assimilation (DA) context, this represents the ice-induced brightness temperature differences between vertical (V) and horizontal (H) polarization-the polarization difference (PD). The discrepancies in PD between observations and simulations decrease by an order of magnitude at 166.5 GHz, with maximum reductions of 10-15 K. The error distributions, which were previously highly skewed and therefore problematic for DA, are now roughly symmetrical. The approach is based on rescaling the extinction in V and H channels, which is quantified by the polarization ratio. Using dual-polarization observations from the Global Precipitation Mission microwave imager (GMI), suitable values for were found to be 1.5 and 1.4 at 89.0 and 166.5 GHz, respectively. The scheme was used for all the conical scanners assimilated at ECMWF, with a broadly neutral impact on the forecast but with an increased physical consistency between instruments that employ different polarizations. This opens the way towards representing hydrometeor orientation for cross-track sounders and at frequencies above 183.0 GHz where the polarization can be even stronger. © 2021 Author(s). more
Atmosphere Method NWP-SAF Software for CDR development

Inter-model Variability in Convection-Resolving Simulations of Subtropical Marine Low Clouds

Author(s):
Heim, Christoph; Hentgen, Laureline; Ban, Nikolina; Schar, Christoph
Publication title: JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN
2021
 | Volume: 99 | Issue: 5
2021
DOI: 10.2151/jmsj.2021-062
Abstract:
We analyze a multi-model ensemble at a convection-resolving resolution based on the DYAMOND models and a resolution ensemble based on the limited-area… We analyze a multi-model ensemble at a convection-resolving resolution based on the DYAMOND models and a resolution ensemble based on the limited-area model COSMO over 40 days to study how tropical and subtropical marine low clouds are represented at a kilometer-scale resolution. The analyzed simulations produce low cloud fields that look in general realistic in comparison with satellite images. The evaluation of the radiative balance, however, reveals substantial inter-model differences and an under estimated low cloud cover in most models. Models that simulate increased low cloud cover are found to have a deeper marine boundary layer (MBL), stronger entrainment, and an enhanced latent heat flux. These findings demonstrate that some of the fundamental relations of the MBL are systematically represented by the model ensemble, which implies that the relevant dynamical processes start to become resolved on the model grid at a kilometer-scale resolution. A sensitivity experiment with the COSMO model suggests that differences in the strength of turbulent vertical mixing may contribute to the inter-model spread in cloud cover. more
Atmosphere CM-SAF Climate Data Records Validation

Influence of air pressure patterns over Europe on solar radiation variability over Poland (1986–2015)

Author(s):
Kulesza, Kinga
Publication title: International Journal of Climatology
2021
 | Volume: 41 | Issue: S1
2021
DOI: 10.1002/joc.6689
Abstract:
The key factor that affects the inflow of radiant energy to the Earth's surface is the circulation of the atmosphere (caused by uneven distribution of… The key factor that affects the inflow of radiant energy to the Earth's surface is the circulation of the atmosphere (caused by uneven distribution of air pressure on the globe) and the related changes in the amount of aerosols and cloudiness. This paper identified the areas in the Euro-Atlantic region where the air pressure change had a significant impact on global solar radiation (GSR) changes over Poland, during the period 1986–2015. In general, growing GSR sums over Poland are to some extent related to the positive phase of the NAO (simultaneous pressure growth in the area of the Azores High and the pressure decrease in the area of the Icelandic Low). Correlation coefficient between the NAO index and GSR over Poland equals 0.18 (statistically significant at α = 0.05). In turn, in summer and autumn the pressure growth in southern Scandinavia results in a significant increase in the amount of GSR over Poland. Days with extremely large GSR sums (above the 95th percentile) are also prompted by the Azores High ridge which covers Central and Southern Europe, and by air mass inflow from the Atlantic. more
Application Atmosphere CM-SAF Climate Data Records

Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: Implementation and examples

Author(s):
Deneke, H.; Barrientos-Velasco, C.; Bley, S.; Hunerbein, A.; Lenk, S.; Macke, A.; Meirink, J.F.; Schroedter-Homscheidt, M.; Senf, F.; Wang, P.; Werner, F.; Witthuhn, J.
Publication title: Atmospheric Measurement Techniques
2021
 | Volume: 14 | Issue: 7
2021
DOI: 10.5194/amt-14-5107-2021
Abstract:
The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the… The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1ĝ€¯km2 compared to the standard 3×3ĝ€¯km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6ĝ€¯μm, 0.8ĝ€¯μm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6ĝ€¯μm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6ĝ€¯μm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains. © Copyright: more
Atmosphere CM-SAF Climate Data Records Method

How accurate are satellite-derived surface solar radiation products over tropical oceans?

Author(s):
Tang, W.; Yang, K.; Qin, J.; Li, J.; Ye, J.
Publication title: Journal of Atmospheric and Oceanic Technology
2021
 | Volume: 38 | Issue: 2
2021
DOI: 10.1175/JTECH-D-20-0099.1
Abstract:
Surface solar radiation (SSR) over the ocean is essential for studies of ocean–atmosphere interactions and marine ecology, and satellite remote sensin… Surface solar radiation (SSR) over the ocean is essential for studies of ocean–atmosphere interactions and marine ecology, and satellite remote sensing is a major way to obtain the SSR over ocean. A new high-resolution (10 km; 3 h) SSR product has recently been developed, mainly based on the newly released cloud product of the International Satellite Cloud Climatology Project H series (ISCCP-HXG), and is available for the period from July 1983 to December 2018. In this study, we compared this SSR product with in situ observations from 70 buoy sites in the Global Tropical Moored Buoy Array (GTMBA) and also compared it with another well-known satellite-derived SSR product from the Clouds and the Earth’s Radiant Energy System (CERES; edition 4.1), which has a spatial resolution of approximately 100 km. The results show that the ISCCP-HXG SSR product is generally more accurate than the CERES SSR product for both ocean and land surfaces. We also found that the accuracy of both satellite-derived SSR products (ISCCP-HXG and CRERS) was higher over ocean than over land and that the accuracy of ISCCP-HXG SSR improves greatly when the spatial resolution of the product is coarsened to ≥ 30 km. © 2021 American Meteorological Society. more
Application Atmosphere CM-SAF Climate Data Records

Homogenization of incoming solar radiation measurements over Poland with satellite and climate reanalysis data

Author(s):
Kulesza, K.; Bojanowski, J.S.
Publication title: Solar Energy
2021
 | Volume: 225
2021
DOI: 10.1016/j.solener.2021.07.031
Abstract:
Well-maintained and regularly calibrated measuring instruments provide the most accurate solar radiation data. This extremely valuable research materi… Well-maintained and regularly calibrated measuring instruments provide the most accurate solar radiation data. This extremely valuable research material makes it possible, among others, to analyse variability in solar radiation over the long term and its dependence on other atmospheric state elements such as cloud cover and atmospheric aerosol concentration. Unfortunately, ground-based measurements of solar radiation are often subject to various errors which are very difficult to detect. This is why quality control procedures and homogenisation of data are essential and should be performed prior to further analyses. This paper presents a method for quality control and homogenization of solar radiation data, which builds on the bias-based quality control (BQC) method (Urraca et al., 2017), and is tailored specially for detecting single erroneous daily values, and very long periods of small errors. The method was tested for 16 ground-based stations located in Poland for the period 1991–2015. In comparison with the number of errors detected by the BQC method, the number of detected errors increased significantly: 130 to 2890 more erroneous days were detected at each station. Consequently, the number of inhomogeneous data sets was reduced from 8 to 3 stations. The values on the days considered as erroneous were replaced with debiased values originating from the Surface Solar Radiation Data Set – Heliosat, Edition 2 (SARAH-2). The presented methodology can be also of use in any other places, especially those with many single erroneous days and no metadata publicly available. © 2021 International Solar Energy Society more
Application Atmosphere CM-SAF Climate Data Records

Glyoxal tropospheric column retrievals from TROPOMI - multi-satellite intercomparison and ground-based validation

Author(s):
Lerot, Christophe; Hendrick, Francois; Van Roozendael, Michel; Alvarado, Leonardo M. A.; Richter, Andreas; De Smedt, Isabelle; Theys, Nicolas; Vlietinck, Jonas; Yu, Huan; Van Gent, Jeroen; Stavrakou, Trissevgeni; Muller, Jean-Francois; Valks, Pieter; Loyola, Diego; Irie, Hitoshi; Kumar, Vinod; Wagner, Thomas; Schreier, Stefan F.; Sinha, Vinayak; Wang, Ting; Wang, Pucai; Retscher, Christian
Publication title: ATMOSPHERIC MEASUREMENT TECHNIQUES
2021
 | Volume: 14 | Issue: 12
2021
DOI: 10.5194/amt-14-7775-2021
Abstract:
We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPO-spheric Monitoring Instrument (TROPOMI) on board the S… We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPO-spheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite. Atmospheric glyoxal results from the oxidation of other non-methane volatile organic compounds (NMVOCs) and from direct emissions caused by combustion processes. Therefore, this product is a useful indicator of VOC emissions. It is generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the differential optical absorption spectroscopy (DOAS) approach. Among the algorithmic updates, the DOAS fit now includes corrections to mitigate the impact of spectral misfits caused by scene brightness inhomogeneity and strong NO2 absorption. The product comes along with a full error characterization, which allows for providing random and systematic error estimates for every observation. Systematic errors are typically in the range of 1 x 10(14)-3 x 10(14) molec.cm(-2) (similar to 30 %-70 % in emission regimes) and originate mostly from a priori data uncertainties and spectral interferences with other absorbing species. The latter may be at the origin, at least partly, of an enhanced glyoxal signal over equatorial oceans, and further investigation is needed to mitigate them. Random errors are large (> 6 x 10(14) molec. cm(-2)) but can be reduced by averaging observations in space and/or time. Benefiting from a high signal-to-noise ratio and a large number of small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of detail. Using the same retrieval algorithmic baseline, glyoxal column data sets are also generated from the Ozone Monitoring Instrument (OMI) on Aura and from the Global Ozone Monitoring Experiment-2 (GOME-2) on board Metop-A and Metop-B. Those four data sets are intercompared over large-scale regions worldwide and show a high level of consistency. The satellite glyoxal columns are also compared to glyoxal columns retrieved from ground-based Multi-AXis DOAS (MAX-DOAS) instruments at nine stations in Asia and Europe. In general, the satellite and MAX-DOAS instruments provide consistent glyoxal columns both in terms of absolute values and variability. Correlation coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where satellite data appear to be biased low during wintertime. The mean absolute glyoxal columns from satellite and MAX-DOAS generally agree well for low/moderate columns with differences of less than 1 x 10(14) molec.cm(-2). A larger bias is identified at two sites where the MAX-DOAS columns are very large. Despite this systematic bias, the consistency of the satellite and MAX-DOAS glyoxal seasonal variability is high. more
AC-SAF Atmosphere Climate Data Records Validation

Global, regional and national trends of atmospheric ammonia derived from a decadal (2008–2018) satellite record

Author(s):
Van Damme, Martin; Clarisse, Lieven; Franco, Bruno; Sutton, Mark A; Erisman, Jan Willem; Wichink Kruit, Roy; van Zanten, Margreet; Whitburn, Simon; Hadji-Lazaro, Juliette; Hurtmans, Daniel; Clerbaux, Cathy; Coheur, Pierre-François
Publication title: Environmental Research Letters
2021
 | Volume: 16 | Issue: 5
2021
DOI: 10.1088/1748-9326/abd5e0
Abstract:
Abstract Excess atmospheric ammonia (NH 3 ) leads to deleterious effects on biodiversity, ecosy… Abstract Excess atmospheric ammonia (NH 3 ) leads to deleterious effects on biodiversity, ecosystems, air quality and health, and it is therefore essential to monitor its budget and temporal evolution. Hyperspectral infrared satellite sounders provide daily NH 3 observations at global scale for over a decade. Here we use the version 3 of the Infrared Atmospheric Sounding Interferometer (IASI) NH 3 dataset to derive global, regional and national trends from 2008 to 2018. We find a worldwide increase of 12.8 ± 1.3 % over this 11-year period, driven by large increases in east Asia (5.80 ± 0.61% increase per year), western and central Africa (2.58 ± 0.23 % yr −1 ), North America (2.40 ± 0.45 % yr −1 ) and western and southern Europe (1.90 ± 0.43 % yr −1 ). These are also seen in the Indo-Gangetic Plain, while the southwestern part of India exhibits decreasing trends. Reported national trends are analyzed in the light of changing anthropogenic and pyrogenic NH 3 emissions, meteorological conditions and the impact of sulfur and nitrogen oxides emissions, which alter the atmospheric lifetime of NH 3 . We end with a short case study dedicated to the Netherlands and the ‘Dutch Nitrogen crisis’ of 2019. more
AC-SAF Application Atmosphere Climate Data Records

First validation of GOME-2/MetOp absorbing aerosol height using EARLINET lidar observations

Author(s):
Michailidis, Konstantinos; Koukouli, Maria-Elissavet; Siomos, Nikolaos; Balis, Dimitris; Tuinder, Olaf; Tilstra, L. Gijsbert; Mona, Lucia; Pappalardo, Gelsomina; Bortoli, Daniele
Publication title: Atmospheric Chemistry and Physics
2021
 | Volume: 21 | Issue: 4
2021
DOI: 10.5194/acp-21-3193-2021
Abstract:
The aim of this study is to investigate the potential of the Global Ozone Monitoring Experiment-2 (GOME-2) instruments, aboard the Meteorological Oper… The aim of this study is to investigate the potential of the Global Ozone Monitoring Experiment-2 (GOME-2) instruments, aboard the Meteorological Operational (MetOp)-A, MetOp-B and MetOp-C satellite programme platforms, to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based lidar data from stations available from the European Aerosol Research Lidar Network (EARLINET) database. The data are post-processed using the wavelet covariance transform (WCT) method in order to extract geometrical features such as the planetary boundary layer (PBL) height and the cloud boundaries. To obtain a significant number of collocated and coincident GOME-2 – EARLINET cases for the period between January 2007 and September 2019, 13 lidar stations, distributed over different European latitudes, contributed to this validation. For the 172 carefully screened collocations, the mean bias was found to be −0.18 ± 1.68 km, with a near-Gaussian distribution. On a station basis, and with a couple of exceptions where very few collocations were found, their mean biases fall in the ± 1 km range with an associated standard deviation between 0.5 and 1.5 km. Considering the differences, mainly due to the temporal collocation and the difference, between the satellite pixel size and the point view of the ground-based observations, these results can be quite promising and demonstrate that stable and extended aerosol layers as captured by the satellite sensors are verified by the ground-based data. We further present an in-depth analysis of a strong and long-lasting Saharan dust intrusion over the Iberian Peninsula. We show that, for this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exact temporally collocated lidar observation for the entire range of 0 to 150 km radii. This finding further testifies for the capabilities of the MetOp-borne instruments to sense the atmospheric aerosol layer heights. more
AC-SAF Atmosphere Climate Data Records Validation

Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors

Author(s):
Bruno, O.; Hoose, C.; Storelvmo, T.; Coopman, Q.; Stengel, M.
Publication title: Geophysical Research Letters
2021
 | Volume: 48 | Issue: 2
2021
DOI: 10.1029/2020GL089863
Abstract:
One of the largest uncertainties in numerical weather prediction and climate models is the representation of mixed-phase clouds. With the aim of under… One of the largest uncertainties in numerical weather prediction and climate models is the representation of mixed-phase clouds. With the aim of understanding how the supercooled liquid fraction (SLF) in clouds with temperature from −40°C to 0°C is related to temperature, geographical location, and cloud type, our analysis contains a comparison of four satellite-based datasets (one derived from active and three from passive satellite sensors), and focuses on SLF distribution near-globally, but also stratified by latitude and continental/maritime regions. Despite the warm bias in cloud top temperature of the passive sensor compared to the active sensor and the phase mismatch in collocated data, all datasets indicate, at the same height-level, an increase of SLF with cloud optical thickness, and generally larger SLF in the Southern Hemisphere than in the Northern Hemisphere (up to about 20% difference), with the exception of continental low-level clouds, for which the opposite is true. © 2020. The Authors. more
Application Atmosphere CM-SAF Climate Data Records Validation

Evidence for Clear-Sky Dimming and Brightening in Central Europe

Author(s):
Wild, M.; Wacker, S.; Yang, S.; Sanchez-Lorenzo, A.
Publication title: Geophysical Research Letters
2021
 | Volume: 48 | Issue: 6
2021
DOI: https://doi.org/10.1029/2020GL092216
Abstract:
For the explanation of the observed decadal variations in surface solar radiation (known as dimming and brightening), the relative importance of cloud… For the explanation of the observed decadal variations in surface solar radiation (known as dimming and brightening), the relative importance of clouds and the cloud-free atmosphere (particularly aerosols) is currently disputed. Here, we investigate this issue using daily data from the prominent long-term observational radiation record at Potsdam, Germany, over the 71-year period 1947–2017. We identify cloud-free days based on synop cloud observations as well as on days with maximum atmospheric transmission. Irrespective of the cloud-screening method, strong dimming and brightening tendencies in the atmospheric transmission are evident not only under all-sky but also of similar magnitude under clear-sky conditions, causing multidecadal variations in surface solar radiation on the order of 10 Wm−2. This points to the cloud-free atmosphere as a main responsible for dimming and brightening in central Europe and suggests that these variations are anthropogenically forced rather than of natural origin, with aerosol pollutants as likely major drivers. more
Application Atmosphere CM-SAF Climate Data Records

Evapotranspiration in the Amazon: Spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models

Author(s):
Baker, J.C.A.; Garcia-Carreras, L.; Gloor, M.; Marsham, J.H.; Buermann, W.; Da Rocha, H.R.; Nobre, A.D.; De Carioca Araujo, A.; Spracklen, D.V.
Publication title: Hydrology and Earth System Sciences
2021
 | Volume: 25 | Issue: 4
2021
DOI: 10.5194/hess-25-2279-2021
Abstract:
Water recycled through transpiring forests influences the spatial distribution of precipitation in the Amazon and has been shown to play a role in the… Water recycled through transpiring forests influences the spatial distribution of precipitation in the Amazon and has been shown to play a role in the initiation of the wet season. However, due to the challenges and costs associated with measuring evapotranspiration (ET) directly and high uncertainty in remote-sensing ET retrievals, the spatial and temporal patterns in Amazon ET remain poorly understood. In this study, we estimated ET over the Amazon and 10 sub-basins using a catchment-balance approach, whereby ET is calculated directly as the balance between precipitation, runoff, and change in groundwater storage. We compared our results with ET from remote-sensing datasets, reanalysis, models from Phase 5 and Phase 6 of the Coupled Model Intercomparison Projects (CMIP5 and CMIP6 respectively), and in situ flux tower measurements to provide a comprehensive overview of current understanding. Catchment-balance analysis revealed a gradient in ET from east to west/southwest across the Amazon Basin, a strong seasonal cycle in basin-mean ET primarily controlled by net incoming radiation, and no trend in ET over the past 2 decades. This approach has a degree of uncertainty, due to errors in each of the terms of the water budget; therefore, we conducted an error analysis to identify the range of likely values. Satellite datasets, reanalysis, and climate models all tended to overestimate the magnitude of ET relative to catchment-balance estimates, underestimate seasonal and interannual variability, and show conflicting positive and negative trends. Only two out of six satellite and model datasets analysed reproduced spatial and seasonal variation in Amazon ET, and captured the same controls on ET as indicated by catchment-balance analysis. CMIP5 and CMIP6 ET was inconsistent with catchment-balance estimates over all scales analysed. Overall, the discrepancies between data products and models revealed by our analysis demonstrate a need for more ground-based ET measurements in the Amazon as well as a need to substantially improve model representation of this fundamental component of the Amazon hydrological cycle./p. © 2021 American Medical Association. All rights reserved. more
Application Atmosphere CM-SAF Climate Data Records

Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors

Author(s):
Beck, Hylke E.; Pan, Ming; Miralles, Diego G.; Reichle, Rolf H.; Dorigo, Wouter A.; Hahn, Sebastian; Sheffield, Justin; Karthikeyan, Lanka; Balsamo, Gianpaolo; Parinussa, Robert M.; van Dijk, Albert I. J. M.; Du, Jinyang; Kimball, John S.; Vergopolan, Noemi; Wood, Eric F.
Publication title: Hydrology and Earth System Sciences
2021
 | Volume: 25 | Issue: 1
2021
DOI: 10.5194/hess-25-17-2021
Abstract:
Abstract. Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes… Abstract. Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo (Merged soil Moisture) and six estimates from the HBV (Hydrologiska Byråns Vattenbalansavdelning) model with three precipitation inputs (ERA5, IMERG, and MSWEP) with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5 cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. We found that application of the Soil Wetness Index (SWI) smoothing filter resulted in improved performance for all satellite products. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3ESWI, SMOSSWI, AMSR2SWI, and ASCATSWI, with the L-band-based SMAPL3ESWI (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCISWI), MeMo performed better on average (median R of 0.72 versus 0.67), probably due to the inclusion of SMAPL3ESWI. The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale. more
Climate Data Records H-SAF Land Validation

Effects of aerosols and clouds on the levels of surface solar radiation and solar energy in cyprus

Author(s):
Fountoulakis, I.; Kosmopoulos, P.; Papachristopoulou, K.; Raptis, I.-P.; Mamouri, R.-E.; Nisantzi, A.; Gkikas, A.; Witthuhn, J.; Bley, S.; Moustaka, A.; Buehl, J.; Seifert, P.; Hadjimitsis, D.G.; Kontoes, C.; Kazadzis, S.
Publication title: Remote Sensing
2021
 | Volume: 13 | Issue: 12
2021
DOI: https://doi.org/10.3390/rs13122319
Abstract:
Cyprus plans to drastically increase the share of renewable energy sources from 13.9% in 2020 to 22.9% in 2030. Solar energy can play a key role in th… Cyprus plans to drastically increase the share of renewable energy sources from 13.9% in 2020 to 22.9% in 2030. Solar energy can play a key role in the effort to fulfil this goal. The potential for production of solar energy over the island is much higher than most of European territory because of the low latitude of the island and the nearly cloudless summers. In this study, high quality and fine resolution satellite retrievals of aerosols and dust, from the newly developed MIDAS climatology, and information for clouds from CM SAF are used in order to quantify the effects of aerosols, dust, and clouds on the levels of surface solar radiation for 2004–2017 and the corresponding financial loss for different types of installations for the production of solar energy. Surface solar radiation climatology has also been developed based on the above information. Ground-based measurements were also incorporated to study the contribution of different species to the aerosol mixture and the effects of day-to-day variability of aerosols on SSR. Aerosols attenuate 5–10% of the annual global horizontal irradiation and 15–35% of the annual direct normal irradiation, while clouds attenuate 25–30% and 35–50% respectively. Dust is responsible for 30–50% of the overall attenuation by aerosols and is the main regulator of the variability of total aerosol. All-sky annual global horizontal irradiation increased significantly in the period of study by 2%, which was mainly attributed to changes in cloudiness. more
Application Atmosphere CM-SAF Climate Data Records

Effect of Aerosols, Tropospheric NO2 and Clouds on Surface Solar Radiation over the Eastern Mediterranean (Greece)

Author(s):
Alexandri, G.; Georgoulias, A.K.; Balis, D.
Publication title: Remote Sensing
2021
 | Volume: 13 | Issue: 13
2021
DOI: https://doi.org/10.3390/rs13132587
Abstract:
In this work, the effect that two basic air quality indexes, aerosols and tropospheric NO2, exert on surface solar radiation (SSR) is studied, along w… In this work, the effect that two basic air quality indexes, aerosols and tropospheric NO2, exert on surface solar radiation (SSR) is studied, along with the effect of liquid and ice clouds over 16 locations in Greece, in the heart of the Eastern Mediterranean. State-of-the-art satellite-based observations and climatological data for the 15-year period 2005–2019, and a radiative transfer system based on a modified version of the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model are used. Our SSR simulations are in good agreement with ground observations and two satellite products. It is shown that liquid clouds dominate, with an annual radiative effect (RE) of −36 W/m2, with ice clouds (−19 W/m2) and aerosols (−13 W/m2) following. The radiative effect of tropospheric NO2 is smaller by two orders of magnitude (−0.074 W/m2). Under clear skies, REaer is about 3–4 times larger than for liquid and ice cloud-covered skies, while RENO2 doubles. The radiative effect of all the parameters exhibits a distinct seasonal cycle. An increase in SSR is observed for the period 2005–2019 (positive trends ranging from 0.01 to 0.52 W/m2/year), which is mostly related to a decrease in the aerosol optical depth and the liquid cloud fraction. more
Application Atmosphere CM-SAF Climate Data Records

Current and future potential of solar and wind energy over Africa using the RegCM4 CORDEX-CORE ensemble

Author(s):
Sawadogo, W.; Reboita, M.S.; Faye, A.; da Rocha, R.P.; Odoulami, R.C.; Olusegun, C.F.; Adeniyi, M.O.; Abiodun, B.J.; Sylla, M.B.; Diallo, I.; Coppola, E.; Giorgi, F.
Publication title: Climate Dynamics
2021
 | Volume: 57 | Issue: 5-6
2021
DOI: 10.1007/s00382-020-05377-1
Abstract:
Renewable energy is key for the development of African countries, and knowing the best location for the implementation of solar and wind energy projec… Renewable energy is key for the development of African countries, and knowing the best location for the implementation of solar and wind energy projects is important within this context. The purpose of this study is to assess the impact of climate change on solar and wind energy potential over Africa under low end (RCP2.6) and high end (RCP8.5) emission scenarios using a set of new high resolution (25 km) simulations with the Regional Climate Model version 4 (RegCM4) produced as part of the CORDEX-CORE initiative. The projections focus on two periods: (i) the near future (2021–2040) and ii) the mid-century future (2041–2060). The performance of the RegCM4 ensemble mean (Rmean) in simulating relevant present climate variables (1995–2014) is first evaluated with respect to the ERA5 reanalysis and satellite-based data. The Rmean reproduces reasonably well the observed spatial patterns of solar irradiance, air temperature, total cloud cover, wind speed at 100 m above the ground level, photovoltaic power potential (PVP), concentrated solar power output (CSPOUT) and wind power density (WPD) over Africa, though some biases are still evident, especially for cloud-related variables. For the future climate, the sign of the changes is consistent in both scenarios but with more intense magnitude in the middle of the century RCP8.5 scenario. Considering the energy variables, the Rmean projects a general decrease in PVP, which is more pronounced in the mid-century future and under RCP8.5 (up to 2%). Similarly, a general increase in CSPOUT (up to 2%) is projected over the continent under both the RCP2.6 and RCP8.5 scenarios. The projection in WPD shows a similar change (predominant increase) in the near and mid-century future slices under both RCPs with a maximum increase of 20%. The present study suggests that the RCP2.6 emission scenario, in general, favours the implementation of renewable energy in Africa compared to the RCP8.5. © 2020, The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

Coral Skeletal Luminescence Records Changes in Terrestrial Chromophoric Dissolved Organic Matter in Tropical Coastal Waters

Author(s):
Kaushal, N.; Sanwlani, N.; Tanzil, J.T.I.; Cherukuru, N.; Sahar, S.; Müller, M.; Mujahid, A.; Lee, J.N.; Goodkin, N.F.; Martin, P.
Publication title: Geophysical Research Letters
2021
 | Volume: 48 | Issue: 8
2021
DOI: 10.1029/2020GL092130
Abstract:
Terrigenous dissolved organic matter (tDOM) carried by rivers represents an important carbon flux to the coastal ocean, which is thought to be increas… Terrigenous dissolved organic matter (tDOM) carried by rivers represents an important carbon flux to the coastal ocean, which is thought to be increasing globally. Because tDOM is rich in light-absorbent chromophoric dissolved organic matter (CDOM), it may also reduce the amount of sunlight available in coastal ecosystems. Despite its biogeochemical and ecological significance, there are few long-term records of tDOM, hindering our understanding of its drivers and dynamics. Corals incorporate terrestrial humic acids, an important constituent of CDOM, resulting in luminescent bands that have been previously linked to rainfall and run-off. We show that luminescence green-to-blue (G/B) ratios in a coral core growing in waters affected by peatland run-off correlate strongly with remote sensing-derived CDOM absorption. The 24-year monthly resolution reconstructed record shows that rainfall controls land-to-ocean tDOM flux from this protected peatland catchment, and suggests an additional impact by solar radiation, which degrades tDOM at sea. © 2021. The Authors. more
Application Atmosphere CM-SAF Climate Data Records Ocean

Contribution of changes in snow cover extent to shortwave radiation perturbations at the top of the atmosphere over the northern hemisphere during 2000–2019

Author(s):
Chen, X.; Yang, Y.; Yin, C.
Publication title: Remote Sensing
2021
 | Volume: 13 | Issue: 23
2021
DOI: 10.3390/rs13234938
Abstract:
Snow-induced radiative forcing (SnRF), defined as the instantaneous perturbation of the Earth’s shortwave radiation at the top of the atmosphere (TOA)… Snow-induced radiative forcing (SnRF), defined as the instantaneous perturbation of the Earth’s shortwave radiation at the top of the atmosphere (TOA), results from variations in the terrestrial snow cover extent (SCE), and is critical for the regulation of the Earth’s energy budget. However, with the growing seasonal divergence of SCE over the Northern Hemisphere (NH) in the past two decades, novel insights pertaining to SnRF are lacking. Consequently, the contribution of SnRF to TOA shortwave radiation anomalies still remains unclear. Utilizing the latest datasets of snow cover, surface albedo, and albedo radiative kernels, this study investigated the distribution of SnRF over the NH and explored its changes from 2000 to 2019. The 20-year averaged annual mean SnRF in the NH was −1.13 ± 0.05 W m−2, with a weakening trend of 0.0047 Wm−2 yr−1 (p &lt; 0.01) during 2000–2019, indicating that an extra 0.094 W m−2 of shortwave radiation was absorbed by the Earth climate system. Moreover, changes in SnRF were highly correlated with satellite-observed TOA shortwave flux anomalies (r = 0.79, p &lt; 0.05) during 2000–2019. Additionally, a detailed contribution analysis revealed that the SnRF in snow accumulation months, from March to May, accounted for 58.10% of the annual mean SnRF variability across the NH. These results can assist in providing a better understanding of the role of snow cover in Earth’s climate system in the context of climate change. Although the rapid SCE decline over the NH has a hiatus for the period during 2000–2019, SnRF continues to follow a weakening trend. Therefore, this should be taken into consideration in current climate change models and future climate projections. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. more
Application CM-SAF Climate Data Records Cryosphere

Climatological analysis of solar and wind energy in Germany using the Grosswetterlagen classification

Author(s):
Drücke, J.
Publication title: Renewable Energy
2021
 | Volume: 164 | Issue: February
2021
DOI: 10.1016/j.renene.2020.10.102
Abstract:
Solar and wind energy play an important role in current and future energy supply in Germany and Europe. The production of renewable energy highly depe… Solar and wind energy play an important role in current and future energy supply in Germany and Europe. The production of renewable energy highly depends on weather conditions resulting in an increasing impact of meteorological fluctuations on energy production. Here, climatological data of solar radiation and wind speed are used to simulate hourly capacity factors for solar and wind energy for Germany from 1995 to 2015. Using renewable energy production data for 2015 these data are converted into time series of generated electrical power. Events with very low energy production, i.e., shortfall events, have been identified and related to large-scale weather regimes over Europe. In Germany, on average about twice as much electrical energy is generated from wind compared to solar radiation; in addition there is a distinct annual cycle with an equal share of generated energy during summer and a 70/30% wind/solar share in winter. There is an unambiguous dependency of wind and solar energy production on weather regimes. Shortfall events in Germany only occur in winter, often associated with a high pressure system over Central Europe. During this weather regime, the renewable energy potential in Northern and Southeastern Europe is above average, possibly allowing to balance shortfall events in Germany. more
Application Atmosphere CM-SAF Climate Data Records

Closing the Water Cycle from Observations across Scales: Where Do We Stand?

Author(s):
Dorigo, Wouter; Dietrich, Stephan; Aires, Filipe; Brocca, Luca; Carter, Sarah; Cretaux, Jean-Francois; Dunkerley, David; Enomoto, Hiroyuki; Forsberg, Rene; Guntner, Andreas; Hegglin, Michaela, I; Hollmann, Rainer; Hurst, Dale F.; Johannessen, Johnny A.; Kummerow, Christian; Lee, Tong; Luojus, Kari; Looser, Ulrich; Miralles, Diego G.; Pellet, Victor; Recknagel, Thomas; Vargas, Claudia Ruz; Schneider, Udo; Schoeneich, Philippe; Schroeder, Marc; Tapper, Nigel; Vuglinsky, Valery; Wagner, Wolfgang; Yu, Lisan; Zappa, Luca; Zemp, Michael; Aich, Valentin
Publication title: BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
2021
 | Volume: 102 | Issue: 10
2021
DOI: 10.1175/BAMS-D-19-0316.1
Abstract:
Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources is increasing, as is human exposure to weather-rela… Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources is increasing, as is human exposure to weather-related extremes (droughts, storms, floods) caused by climate change. Understanding these changes is pivotal for developing mitigation and adaptation strategies. The Global Climate Observing System (GCOS) defines a suite of essential climate variables (ECVs), many related to the water cycle, required to systematically monitor Earth's climate system. Since long-term observations of these ECVs are derived from different observation techniques, platforms, instruments, and retrieval algorithms, they often lack the accuracy, completeness, and resolution, to consistently characterize water cycle variability at multiple spatial and temporal scales. Here, we review the capability of ground-based and remotely sensed observations of water cycle ECVs to consistently observe the hydrological cycle. We evaluate the relevant land, atmosphere, and ocean water storages and the fluxes between them, including anthropogenic water use. Particularly, we assess how well they close on multiple temporal and spatial scales. On this basis, we discuss gaps in observation systems and formulate guidelines for future water cycle observation strategies. We conclude that, while long-term water cycle monitoring has greatly advanced in the past, many observational gaps still need to be overcome to close the water budget and enable a comprehensive and consistent assessment across scales. Trends in water cycle components can only be observed with great uncertainty, mainly due to insufficient length and homogeneity. An advanced closure of the water cycle requires improved model-data synthesis capabilities, particularly at regional to local scales. more
Application CM-SAF Climate Data Records H-SAF Land

Characterizing Buoy Wind Speed Error in High Winds and Varying Sea State with ASCAT and ERA5

Author(s):
Wright, Ethan E.; Bourassa, Mark A.; Stoffelen, Ad; Bidlot, Jean-Raymond
Publication title: REMOTE SENSING
2021
 | Volume: 13 | Issue: 22
2021
DOI: 10.3390/rs13224558
Abstract:
Buoys provide key observations of wind speed over the ocean and are routinely used as a source of validation data for satellite wind products. However… Buoys provide key observations of wind speed over the ocean and are routinely used as a source of validation data for satellite wind products. However, the movement of buoys in high seas and the airflow over waves might cause inaccurate readings, raising concern when buoys are used as a source of wind speed comparison data. The relative accuracy of buoy winds is quantified through a triple collocation (TC) exercise comparing buoy winds to winds from ASCAT and ERA5. Differences between calibrated buoy winds and ASCAT are analyzed through separating the residuals by anemometer height and testing under high wind-wave and swell conditions. First, we converted buoy winds measured near 3, 4, and 5 m to stress-equivalent winds at 10 m (U10S). Buoy U10S from anemometers near 3 m compared notably lower than buoy U10S from anemometers near 4 and 5 m, illustrating the importance of buoy choice in comparisons with remote sensing data. Using TC calibration of buoy U10S to ASCAT in pure wind-wave conditions, we found that there was a small, but statistically significant difference between height adjusted buoy winds from buoys with 4 and 5 m anemometers compared to the same ASCAT wind speed ranges in high seas. However, this result does not follow conventional arguments for wave sheltering of buoy winds, whereby the lower anemometer height winds are distorted more than the higher anemometer height winds in high winds and high seas. We concluded that wave sheltering is not significantly affecting the winds from buoys between 4 and 5 m with high confidence for winds under 18 ms(-1). Further differences between buoy U10S and ASCAT winds are observed in high swell conditions, motivating the need to consider the possible effects of sea state on ASCAT winds. more
Atmosphere Climate Data Records OSI-SAF Validation

Changes in toa sw fluxes over marine clouds when estimated via semiphysical angular distribution models

Author(s):
Tornow, F.; Domenech, C.; Cole, J.N.S.; Madenach, N.; Fischer, J.
Publication title: Journal of Atmospheric and Oceanic Technology
2021
 | Volume: 38 | Issue: 3
2021
DOI: 10.1175/JTECH-D-20-0107.1
Abstract:
Top-of-atmosphere (TOA) shortwave (SW) angular distribution models (ADMs) approximate—per angular direction of an imagined upward hemisphere—the inten… Top-of-atmosphere (TOA) shortwave (SW) angular distribution models (ADMs) approximate—per angular direction of an imagined upward hemisphere—the intensity of sunlight scattered back from a specific Earth– atmosphere scene. ADMs are, thus, critical when converting satellite-borne broadband radiometry into estimated radiative fluxes. This paper applies a set of newly developed ADMs with a more refined scene definition and demonstrates tenable changes in estimated fluxes compared to currently operational ADMs. Newly developed ADMs use a semiphysical framework to consider cloud-top effective radius (Re ) and above-cloud water vapor (ACWV), in addition to accounting for surface wind speed and clouds’ phase, fraction, and optical depth. In effect, instantaneous TOA SW fluxes for marine liquid-phase clouds had the largest flux differences (of up to 25 W m-2) for lower solar zenith angles and cloud optical depth greater than 10 due to extremes in Re or ACWV. In regions where clouds had persistently extreme levels of Re (here mostly for Re &lt; 7 μm and Re &gt; 15 μm) or ACWV, instantaneous fluxes estimated from Aqua, Terra, Meteosat-8, and Meteosat-9 satellites using the two ADMs differed systematically, resulting in significant deviations in daily mean fluxes (up to ±10 W m-2) and monthly mean fluxes (up to ±5 Wm-2). Flux estimates using newly developed, semiphysical ADMs may contribute to a better understanding of solar fluxes over low-level clouds. It remains to be seen whether aerosol indirect effects are impacted by these updates. © 2021 American Meteorological Society. Policy (www.ametsoc.org/PUBSReuseLice. more
Application Atmosphere CM-SAF Climate Data Records

Assessment of the EUMETSAT Multi Decadal Land Surface Albedo Data Record from Meteosat Observations

Author(s):
Lattanzio, Alessio; Grant, Michael; Doutriaux-Boucher, Marie; Roebeling, Rob; Schulz, Jörg
Publication title: Remote Sensing
2021
 | Volume: 13 | Issue: 10
2021
DOI: 10.3390/rs13101992
Abstract:
Surface albedo, defined as the ratio of the surface-reflected irradiance to the incident irradiance, is one of the parameters driving the Earth energy… Surface albedo, defined as the ratio of the surface-reflected irradiance to the incident irradiance, is one of the parameters driving the Earth energy budget and it is for this reason an essential variable in climate studies. Instruments on geostationary satellites provide suitable observations allowing long-term monitoring of surface albedo from space. In 2012, EUMETSAT published Release 1 of the Meteosat Surface Albedo (MSA) data record. The main limitation effecting the quality of this release was non-removed clouds by the incorporated cloud screening procedure that caused too high albedo values, in particular for regions with permanent cloud coverage. For the generation of Release 2, the MSA algorithm has been replaced with the Geostationary Surface Albedo (GSA) one, able to process imagery from any geostationary imager. The GSA algorithm exploits a new, improved, cloud mask allowing better cloud screening, and thus fixing the major limitation of Release 1. Furthermore, the data record has an extended temporal and spatial coverage compared to the previous release. Both Black-Sky Albedo (BSA) and White-Sky Albedo (WSA) are estimated, together with their associated uncertainties. A direct comparison between Release 1 and Release 2 clearly shows that the quality of the retrieval improved significantly with the new cloud mask. For Release 2 the decadal trend is less than 1% over stable desert sites. The validation against Moderate Resolution Imaging Spectroradiometer (MODIS) and the Southern African Regional Science Initiative (SAFARI) surface albedo shows a good agreement for bright desert sites and a slightly worse agreement for urban and rain forest locations. In conclusion, compared with MSA Release 1, GSA Release 2 provides the users with a significantly more longer time range, reliable and robust surface albedo data record. more
Climate Data Records EUM-Secr Land Validation

Assessing prior emergent constraints on surface albedo feedback in CMIP6

Author(s):
Thackeray, C.W.; Hall, A.; Zelinka, M.D.; Fletcher, C.G.
Publication title: Journal of Climate
2021
 | Volume: 34 | Issue: 10
2021
DOI: 10.1175/JCLI-D-20-0703.1
Abstract:
An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of cli… An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAFsnow) and sea ice (SAFice). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAFsnow EC is equally strong in CMIP6 as it was in past generations, while the SAFice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 6 0.05 W m22 K21, or;61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. The NH SAF can be broken down into similar contributions from snow and sea ice over the twenty-first century in CMIP6. Crucially, intermodel variability in seasonal SAFsnow and SAFice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAFice, and to a lesser extent SAFsnow. Ó 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy more
Application CM-SAF Climate Data Records Cryosphere

Assessing climatic benefits from forestation potential in semi-arid lands

Author(s):
Rohatyn, Shani; Rotenberg, Eyal; Yakir, Dan; Carmel, Yohay
Publication title: ENVIRONMENTAL RESEARCH LETTERS
2021
 | Volume: 16 | Issue: 10
2021
DOI: 10.1088/1748-9326/ac29e9
Abstract:
Forestation actions are a major tool for both climate-change mitigation and biodiversity conservation. We address two weaknesses in this approach: the… Forestation actions are a major tool for both climate-change mitigation and biodiversity conservation. We address two weaknesses in this approach: the little attention given to the negative effects of reduced albedo associated with forestation in many regions, and ignoring the potential of drylands that account for 40% of the global potential land area for forestation. We propose an approach to identify suitable land for forestation and quantify its `net equivalent carbon stock change' over 80 years of forest lifetime (NESC), accounting for both carbon sequestration and albedo changes. We combined remote-sensing tools with data-based estimates of surface parameters and with published climate matrices, to identify suitable land for forestation actions. We then calculated the cumulative (over 80 years) `net sequestration potential' (Delta SP), the `emission equivalent of shortwave radiation forcing' (EESF) due to changes in surface albedo, and, in turn, the combined NESC = Delta SP-EESF, of planting forests with >40% tree-cover. Demonstrating our approach in a large climatically diverse state (Queensland), we identified 14.5 million hectares of potential forestation land in its semi-arid land and show that accounting for the EESF, reduces the climatic benefits of the Delta SP by almost 50%. Nevertheless, it results in a total NESC of 0.72 Gt C accumulated by the end of the century, and 80 years of forestation cycle. This estimated NESC is equivalent to 15% of the projected carbon emissions for the same period in Queensland, for a scenario of no change in emission rates during that period. Our approach extends restoration efforts by identifying new land for forestation and carbon sequestration but also demonstrates the importance of quantifying the climatic value of forestation in drylands. more
Application CM-SAF Climate Data Records Land

AR6 Climate Change 2021, The Physical Science Basis - chapter 9: ocean, cryosphere and sea levele change

Author(s):
IPCC
2021
2021
DOI:
Abstract:
This chapter assesses past and projected changes in the ocean, cryosphere and sea level using paleo reconstructions, instrumental observations and mod… This chapter assesses past and projected changes in the ocean, cryosphere and sea level using paleo reconstructions, instrumental observations and model simulations. In the following summary, we update and expand the related assessments from the IPCC Fifth Assessment Report (AR5), the Special Report on Global Warming of 1.5ºC (SR1.5) and the Special Report on Ocean and Cryosphere in a Changing Climate (SROCC). Major advances in this chapter since the SROCC include the synthesis of extended and new observations, which allows for improved assessment of past change, processes and budgets for the last century, and the use of a hierarchy of models and emulators, which provide improved projections and uncertainty estimates of future change. In addition, the systematic use of model emulators makes our projections of ocean heat content, land-ice loss and sea level rise fully consistent both with each other and with the assessed equilibrium climate sensitivity and projections of global surface air temperature across the entire report. In this executive summary, uncertainty ranges are reported as very likely ranges and expressed by square brackets, unless otherwise noted. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

AR6 Climate Change 2021, The Physical Science Basis - chapter 2: changing state of the climate system

Author(s):
IPCC
2021
2021
DOI:
Abstract:
Within Chapter 2, changes are assessed from in situ and remotely sensed data and products and from indirect evidence of longer-term changes based upon… Within Chapter 2, changes are assessed from in situ and remotely sensed data and products and from indirect evidence of longer-term changes based upon a diverse range of climate proxies. The time-evolving availability of observations and proxy information dictate the periods that can be assessed. Wherever possible, recent changes are assessed for their significance in a longer-term context, including target proxy periods, both in terms of mean state and rates of change more
Application Climate Data Records EUM-Secr

Analyzing the Thermodynamic Phase Partitioning of Mixed Phase Clouds Over the Southern Ocean Using Passive Satellite Observations

Author(s):
Coopman, Q.; Hoose, C.; Stengel, M.
Publication title: Geophysical Research Letters
2021
 | Volume: 48 | Issue: 7
2021
DOI: 10.1029/2021GL093225
Abstract:
The thermodynamic phase transition of clouds is still not well understood, therefore, the partitioning of ice and liquid in mixed phase clouds is ofte… The thermodynamic phase transition of clouds is still not well understood, therefore, the partitioning of ice and liquid in mixed phase clouds is often misrepresented in numerical models. We use 12 years of cloud observations from the geostationary Spinning Enhanced Visible and InfraRed Imager over the Southern Ocean to detect clouds which contain both liquid and ice pixels at their tops and we retrieve microphysical and radiative properties in each cloud object. The results show that large cloud droplet effective radius coincides with high ice fraction and high ice optical thickness for cloud top temperatures higher than −8 °C. We also found that the density of ice pixel clusters increases with the cloud ice fraction, for ice fraction lower than 0.5, suggesting a multiplication of ice pockets in line with previous studies, particularly efficient for clouds with high perimeter fractal dimension. © 2021. The Authors. more
Atmosphere CM-SAF Climate Data Records Validation

Analysis of Mineral Aerosol in the Surface Layer over the Caspian Lowland Desert by the Data of 12 Summer Field Campaigns in 2002-2020

Author(s):
Chkhetiani, Otto G.; Vazaeva, Natalia V.; Chernokulsky, Alexander, V; Shukurov, Karim A.; Gubanova, Dina P.; Artamonova, Maria S.; Maksimenkov, Leonid O.; Kozlov, Fedor A.; Kuderina, Tatyana M.
Publication title: ATMOSPHERE
2021
 | Volume: 12 | Issue: 8
2021
DOI: 10.3390/atmos12080985
Abstract:
In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such proces… In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such processes as the entrainment, transport and deposition of aerosols. However, field measurements of the dust emission flux, dust size distribution and its chemical composition under realistic wind conditions remain rare. In this study, we present experimental data over annual expeditions in the arid and semi-arid zones of the Caspian Lowland Desert (Kalmykia, south of Russia); we evaluate characteristics of mineral aerosol concentration and fluxes, estimate its chemical composition and calculate its long-distance transport characteristics. The mass concentration in different years ranges from several tens to several hundred of mu g m(-3). The significant influence of wind velocity on the value of mass and counting concentration and on the proposed entrainment mechanisms is confirmed. An increased content of anthropogenic elements (S, Sn, Pb, Bi, Mo, Ag, Cd, Hg, etc.), which is characteristic for all observation points in the south of the European Russia, is found. The trajectory analysis show that long-range air particles transport from the Caspian Lowland Desert to the central regions of European Russia tends to increase in the recent decades. more
Application Atmosphere CM-SAF Climate Data Records

An Assessment of Land-Atmosphere Interactions over South America Using Satellites, Reanalysis, and Two Global Climate Models

Author(s):
Baker, Jessica C. A.; de Souza, Dayana Castilho; Kubota, Paulo Y.; Buermann, Wolfgang; Coelho, Caio A. S.; Andrews, Martin B.; Gloor, Manuel; Garcia-Carreras, Luis; Figueroa, Silvio N.; Spracklen, Dominick, V
Publication title: JOURNAL OF HYDROMETEOROLOGY
2021
 | Volume: 22 | Issue: 4
2021
DOI: 10.1175/JHM-D-20-0132.1
Abstract:
In South America, land-atmosphere interactions have an important impact on climate, particularly the regional hydrological cycle, but detailed evaluat… In South America, land-atmosphere interactions have an important impact on climate, particularly the regional hydrological cycle, but detailed evaluation of these processes in global climate models has been limited. Focusing on the satellite-era period of 2003-14, we assess land-atmosphere interactions on annual to seasonal time scales over South America in satellite products, a novel reanalysis (ERA5-Land), and two global climate models: the Brazilian Global Atmospheric Model version 1.2 (BAM-1.2) and the U.K. Hadley Centre Global Environment Model version 3 (HadGEM3). We identify key features of South American land-atmosphere interactions represented in satellite and model datasets, including seasonal variation in coupling strength, large-scale spatial variation in the sensitivity of evapotranspiration to surface moisture, and a dipole in evaporative regime across the continent. Differences between products are also identified, with ERA5-Land, HadGEM3, and BAM-1.2 showing opposite interactions to satellites over parts of the Amazon and the Cerrado and stronger land-atmosphere coupling along the North Atlantic coast. Where models and satellites disagree on the strength and direction of land-atmosphere interactions, precipitation biases and misrepresentation of processes controlling surface soil moisture are implicated as likely drivers. These results show where improvement of model processes could reduce uncertainty in the modeled climate response to land-use change, and highlight where model biases could unrealistically amplify drying or wetting trends in future climate projections. Finally, HadGEM3 and BAM-1.2 are consistent with the median response of an ensemble of nine CMIP6 models, showing they are broadly representative of the latest generation of climate models. more
Application Atmosphere CM-SAF Climate Data Records Land

Accounting for inter-annual variability alters long-term estimates of climate suitability

Author(s):
Gardner, A.S.; Gaston, K.J.; Maclean, I.M.D.
Publication title: Journal of Biogeography
2021
 | Volume: 48 | Issue: 8
2021
DOI: 10.1111/jbi.14125
Abstract:
Aim: Species respond to environmental conditions and so reliable assessments of climate suitability are important for predicting how climate change co… Aim: Species respond to environmental conditions and so reliable assessments of climate suitability are important for predicting how climate change could alter their distributions. Long-term average climate data are often used to evaluate the climate suitability of an area, but in these aggregated climate datasets, inter-annual variability is lost. Due to non-linearity in species’ biological responses to climate, estimates of long-term climate suitability from average climate data may be biased and so differ from estimates derived from the average annual suitability over the same period (average response). We investigate the extent to which such differences manifest in a regional assessment of climate suitability for 255 plant species across two 17-year time periods. Location: Cornwall in South-West England provides a case study. Taxon: Plantae. Methods: We run a simple mechanistic climate suitability model and derive quantitative estimates of climate suitability for 1984–2000 and 2001–2017. For each period, we run the model using climate data representing average monthly values for that period. We then run the model for each year using monthly climate data for that year and average the annual suitability scores across each period (average response). We compare estimates of climate suitability from these two approaches. Results: Average climate data gave higher estimates of suitability than the average response, suggesting bias against years of poor suitability in temporally aggregated climate datasets. Differences between suitability estimates were larger in areas of high climate variability and correlated with species’ environmental requirements, being larger for species with small thermal niches and narrow ranges of precipitation tolerance. Main Conclusions: Incorporating inter-annual variability into climate suitability assessments or understanding the extent to which average climate data might obscure this variance will be important to predict reliably the impacts of climate change on species distributions and should be considered when using mechanistic species distribution models. © 2021 The Authors. Journal of Biogeography published by John Wiley & Sons Ltd. more
Application Atmosphere CM-SAF Climate Data Records

A new gas absorption optical depth parameterisation for RTTOV version 13

Author(s):
Hocking, J.; Vidot, J.; Brunel, P.; Roquet, P.; Silveira, B.; Turner, E.; Lupu, C.
Publication title: Geoscientific Model Development
2021
 | Volume: 14 | Issue: 5
2021
DOI: 10.5194/gmd-14-2899-2021
Abstract:
This paper describes a new gas optical depth parameterisation implemented in the most recent release, version 13, of the radiative transfer model RTTO… This paper describes a new gas optical depth parameterisation implemented in the most recent release, version 13, of the radiative transfer model RTTOV (Radiative Transfer for TOVS). RTTOV is a fast, one-dimensional radiative transfer model for simulating top-of-atmosphere visible, infrared, and microwave radiances observed by downward-viewing space-borne passive sensors. A key component of the model is the fast parameterisation of absorption by the various gases in the atmosphere. The existing parameterisation in RTTOV has been extended over many years to allow for additional variable gases in RTTOV simulations and to account for solar radiation and better support geostationary sensors by extending the validity to higher zenith angles. However, there are limitations inherent in the current approach which make it difficult to develop it further, for example by adding new variable gases. We describe a new parameterisation that can be applied across the whole spectrum, that allows for a wide range of zenith angles in support of solar radiation and geostationary sensors, and for which it will be easier to add new variable gases in support of user requirements. Comparisons against line-by-line radiative transfer simulations and against observations in the ECMWF operational system yield promising results, suggesting that the new parameterisation generally compares well with the old one in terms of accuracy. Further validation is planned, including testing in operational numerical weather prediction data assimilation systems.. © 2020 American Society of Mechanical Engineers (ASME). All rights reserved. more
Atmosphere Method NWP-SAF Software for CDR development

Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years

Author(s):
Yang, Dazhi; Bright, Jamie M.
Publication title: SOLAR ENERGY
2020
 | Volume: 210 | Issue: SI
2020
DOI: 10.1016/j.solener.2020.04.016
Abstract:
Gridded solar radiation products, namely satellite-derived irradiance and reanalysis irradiance, are key to the next-generation solar resource assessm… Gridded solar radiation products, namely satellite-derived irradiance and reanalysis irradiance, are key to the next-generation solar resource assessment and forecasting. Since their accuracies are generally lower than that of the ground-based measurements, providing validation of the gridded solar radiation products is necessary in order to understand their qualities and characteristics. This article delivers a worldwide validation of hourly global horizontal irradiance derived from satellite imagery and reanalysis. The accuracies of 6 latest satellite-derived irradiance products (CAMS-RAD, NSRDB, SARAH-2, SARAH-E, CERES-SYN1deg, and Solcast) and 2 latest global reanalysis irradiance products (ERAS and MERRA-2) are verified against the complete records from 57 BSRN stations, over 27 years (1992-2018). This scope of validation is unprecedented in the field of solar energy. Moreover, the importance of using distribution-oriented verification approaches is emphasized. Such approaches go beyond the traditional measure-oriented verification approach, and thus can offer additional insights and flexibility to the verification problem. more
Atmosphere CM-SAF Climate Data Records Validation

Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations

Author(s):
Pinardi, Gaia; Van Roozendael, Michel; Hendrick, François; Theys, Nicolas; Abuhassan, Nader; Bais, Alkiviadis; Boersma, Folkert; Cede, Alexander; Chong, Jihyo; Donner, Sebastian; Drosoglou, Theano; Dzhola, Anatoly; Eskes, Henk; Frieß, Udo; Granville, José; Herman, Jay R.; Holla, Robert; Hovila, Jari; Irie, Hitoshi; Kanaya, Yugo; Karagkiozidis, Dimitris; Kouremeti, Natalia; Lambert, Jean-Christopher; Ma, Jianzhong; Peters, Enno; Piters, Ankie; Postylyakov, Oleg; Richter, Andreas; Remmers, Julia; Takashima, Hisahiro; Tiefengraber, Martin; Valks, Pieter; Vlemmix, Tim; Wagner, Thomas; Wittrock, Folkard
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 11
2020
DOI: 10.5194/amt-13-6141-2020
Abstract:
Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accurac… Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −34 % for GOME-2A and −24 % for OMI. These biases are further reduced to −24 % and −18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements. more
AC-SAF Atmosphere Climate Data Records Validation

Validation of the TROPOspheric Monitoring Instrument (TROPOMI) surface UV radiation product

Author(s):
Lakkala, Kaisa; Kujanpää, Jukka; Brogniez, Colette; Henriot, Nicolas; Arola, Antti; Aun, Margit; Auriol, Frédérique; Bais, Alkiviadis F.; Bernhard, Germar; De Bock, Veerle; Catalfamo, Maxime; Deroo, Christine; Diémoz, Henri; Egli, Luca; Forestier, Jean-Baptiste; Fountoulakis, Ilias; Garane, Katerina; Garcia, Rosa Delia; Gröbner, Julian; Hassinen, Seppo; Heikkilä, Anu; Henderson, Stuart; Hülsen, Gregor; Johnsen, Bjørn; Kalakoski, Niilo; Karanikolas, Angelos; Karppinen, Tomi; Lamy, Kevin; León-Luis, Sergio F.; Lindfors, Anders V.; Metzger, Jean-Marc; Minvielle, Fanny; Muskatel, Harel B.; Portafaix, Thierry; Redondas, Alberto; Sanchez, Ricardo; Siani, Anna Maria; Svendby, Tove; Tamminen, Johanna
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 12
2020
DOI: 10.5194/amt-13-6999-2020
Abstract:
The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmos… The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. The S5P is a Sun-synchronous polar-orbiting satellite providing global daily coverage. The TROPOMI swath is 2600 km wide, and the ground resolution for most data products is 7.2 × 3.5 km2 (5.6 × 3.5 km2 since 6 August 2019) at nadir. The Finnish Meteorological Institute (FMI) is responsible for the development of the TROPOMI UV algorithm and the processing of the TROPOMI surface ultraviolet (UV) radiation product which includes 36 UV parameters in total. Ground-based data from 25 sites located in arctic, subarctic, temperate, equatorial and Antarctic areas were used for validation of the TROPOMI overpass irradiance at 305, 310, 324 and 380 nm, overpass erythemally weighted dose rate/UV index, and erythemally weighted daily dose for the period from 1 January 2018 to 31 August 2019. The validation results showed that for most sites 60 %–80 % of TROPOMI data was within ±20 % of ground-based data for snow-free surface conditions. The median relative differences to ground-based measurements of TROPOMI snow-free surface daily doses were within ±10 % and ±5 % at two-thirds and at half of the sites, respectively. At several sites more than 90 % of cloud-free TROPOMI data was within ±20 % of groundbased measurements. Generally median relative differences between TROPOMI data and ground-based measurements were a little biased towards negative values (i.e. satellite data < ground-based measurement), but at high latitudes where non-homogeneous topography and albedo or snow conditions occurred, the negative bias was exceptionally high: from −30 % to −65 %. Positive biases of 10 %–15 % were also found for mountainous sites due to challenging topography. The TROPOMI surface UV radiation product includes quality flags to detect increased uncertainties in the data due to heterogeneous surface albedo and rough terrain, which can be used to filter the data retrieved under challenging conditions. more
AC-SAF Atmosphere Climate Data Records Validation

Trends in Upper-Tropospheric Humidity: Expansion of the Subtropical Dry Zones?

Author(s):
Tivig, Miriam; Grützun, Verena; John, Viju O.; Buehler, Stefan A.
Publication title: Journal of Climate
2020
 | Volume: 33 | Issue: 6
2020
DOI: 10.1175/JCLI-D-19-0046.1
Abstract:
Abstract Subtropical dry zones, located in the Hadley cells’ subsidence regions, strongly influence regional climate as well as outgoing l… Abstract Subtropical dry zones, located in the Hadley cells’ subsidence regions, strongly influence regional climate as well as outgoing longwave radiation. Changes in these dry zones could have significant impact on surface climate as well as on the atmospheric energy budget. This study investigates the behavior of upper-tropospheric dry zones in a changing climate, using the variable upper-tropospheric humidity (UTH), calculated from climate model experiment output as well as from radiances measured with satellite-based sensors. The global UTH distribution shows that dry zones form a belt in the subtropical winter hemisphere. In the summer hemisphere they concentrate over the eastern ocean basins, where the descent regions of the subtropical anticyclones are located. Recent studies with model and satellite data have found tendencies of increasing dryness at the poleward edges of the subtropical subsidence zones. However, UTH calculated from climate simulations with 25 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) shows these tendencies only for parts of the winter-hemispheric dry belts. In the summer hemisphere, even though differences exist between the simulations, UTH is increasing in most dry zones, particularly in the South and North Pacific Ocean. None of the summer dry zones is expanding in these simulations. Upper-tropospheric dry zones estimated from observational data do not show any robust signs of change since 1979. Apart from a weak drying tendency at the poleward edge of the southern winter-hemispheric dry belt in infrared measurements, nothing indicates that the subtropical dry belts have expanded poleward. more
Application Atmosphere Climate Data Records EUM-Secr

Total column water vapor retrieval for Global Ozone Monitoring Experience-2 (GOME-2) visible blue observations

Author(s):
Chan, Ka Lok; Valks, Pieter; Slijkhuis, Sander; Köhler, Claas; Loyola, Diego
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 8
2020
DOI: 10.5194/amt-13-4169-2020
Abstract:
We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (G… We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Metop satellites. The blue band algorithm allows the retrieval of water vapor from sensors which do not cover longer wavelengths, such as the Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical columns using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from the chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing it to the operational product retrieved in the red spectral band, sun photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5. more
AC-SAF Atmosphere Climate Data Records Validation

The ERA5 global reanalysis

Author(s):
Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horányi, A.; Muñoz-Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D.; Simmons, A.; Soci, C.; Abdalla, S.; Abellan, X.; Balsamo, G.; Bechtold, P.; Biavati, G.; Bidlot, J.; Bonavita, M.; De Chiara, G.; Dahlgren, P.; Dee, D.; Diamantakis, M.; Dragani, R.; Flemming, J.; Forbes, R.; Fuentes, M.; Geer, A.; Haimberger, L.; Healy, S.; Hogan, R.J.; Hólm, E.; Janisková, M.; Keeley, S.; Laloyaux, P.; Lopez, P.; Lupu, C.; Radnoti, G.; de Rosnay, P.; Rozum, I.; Vamborg, F.; Villaume, S.; Thépaut, J.-N.
Publication title: Quarterly Journal of the Royal Meteorological Society
2020
 | Volume: 146 | Issue: 730
2020
DOI: 10.1002/qj.3803
Abstract:
Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis which, once completed, will embody a detailed record of the… Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis which, once completed, will embody a detailed record of the global atmosphere, land surface and ocean waves from 1950 onwards. This new reanalysis replaces the ERA-Interim reanalysis (spanning 1979 onwards) which was started in 2006. ERA5 is based on the Integrated Forecasting System (IFS) Cy41r2 which was operational in 2016. ERA5 thus benefits from a decade of developments in model physics, core dynamics and data assimilation. In addition to a significantly enhanced horizontal resolution of 31 km, compared to 80 km for ERA-Interim, ERA5 has hourly output throughout, and an uncertainty estimate from an ensemble (3-hourly at half the horizontal resolution). This paper describes the general set-up of ERA5, as well as a basic evaluation of characteristics and performance, with a focus on the dataset from 1979 onwards which is currently publicly available. Re-forecasts from ERA5 analyses show a gain of up to one day in skill with respect to ERA-Interim. Comparison with radiosonde and PILOT data prior to assimilation shows an improved fit for temperature, wind and humidity in the troposphere, but not the stratosphere. A comparison with independent buoy data shows a much improved fit for ocean wave height. The uncertainty estimate reflects the evolution of the observing systems used in ERA5. The enhanced temporal and spatial resolution allows for a detailed evolution of weather systems. For precipitation, global-mean correlation with monthly-mean GPCP data is increased from 67% to 77%. In general, low-frequency variability is found to be well represented and from 10 hPa downwards general patterns of anomalies in temperature match those from the ERA-Interim, MERRA-2 and JRA-55 reanalyses. © 2020 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. more
Application Climate Data Records Cryosphere OSI-SAF

The climate monitoring SAF outgoing longwave radiation from AVHRR

Author(s):
Clerbaux, N.; Akkermans, T.; Baudrez, E.; Blazquez, A.V.; Moutier, W.; Moreels, J.; Aebi, C.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 6
2020
DOI: 10.3390/rs12060929
Abstract:
Data from the Advanced Very High Resolution Radiometer (AVHRR) have been used to create several long-duration data records of geophysical variables de… Data from the Advanced Very High Resolution Radiometer (AVHRR) have been used to create several long-duration data records of geophysical variables describing the atmosphere and land and water surfaces. In the Climate Monitoring Satellite Application Facility (CM SAF) project, AVHRR data are used to derive the Cloud, Albedo, and Radiation (CLARA) climate data records of radiation components (i.a., surface albedo) and cloud properties (i.a., cloud cover). This work describes the methodology implemented for the additional estimation of the Outgoing Longwave Radiation (OLR), an important Earth radiation budget component, that is consistent with the other CLARA variables. A first step is the estimation of the instantaneous OLR from the AVHRR observations. This is done by regressions on a large database of collocated observations between AVHRR Channel 4 (10.8 μm) and 5 (12 μm) and the OLR from the Clouds and Earth's Radiant Energy System (CERES) instruments. We investigate the applicability of this method to the first generation of AVHRR instrument (AVHRR/1) for which no Channel 5 observation is available. A second step concerns the estimation of daily and monthly OLR from the instantaneous AVHRR overpasses. This step is especially important given the changes in the local time of the observations due to the orbital drift of the NOAA satellites. We investigate the use of OLR in the ERA5 reanalysis to estimate the diurnal variation. The developed approach proves to be valuable to model the diurnal change in OLR due to day/night time warming/cooling over clear land. Finally, the resulting monthly mean AVHRR OLR product is intercompared with the CERES monthly mean product. For a typical configuration with one morning and one afternoon AVHRR observation, the Root Mean Square (RMS) difference with CERES monthly mean OLR is about 2 Wm-2 at 1 x 1 resolution. We quantify the degradation of the OLR product when only one AVHRR instrument is available (as is the case for some periods in the 1980s) and also the improvement when more instruments are available (e.g., using METOP-A, NOAA-15, NOAA-18, and NOAA-19 in 2012). The degradation of the OLR product from AVHRR/1 instruments is also quantified, which is done by "masking" the Channel 5 observations. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. more
Application Atmosphere CM-SAF Climate Data Records

Ten-Year Assessment of IASI Radiance and Temperature

Author(s):
Bouillon, Marie; Safieddine, Sarah; Hadji-Lazaro, Juliette; Whitburn, Simon; Clarisse, Lieven; Doutriaux-Boucher, Marie; Coppens, Dorothée; August, Thomas; Jacquette, Elsa; Clerbaux, Cathy
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 15
2020
DOI: 10.3390/rs12152393
Abstract:
The Infrared Atmospheric Sounding Interferometers (IASIs) are three instruments flying on board the Metop satellites, launched in 2006 (IASI-A), 2012 … The Infrared Atmospheric Sounding Interferometers (IASIs) are three instruments flying on board the Metop satellites, launched in 2006 (IASI-A), 2012 (IASI-B), and 2018 (IASI-C). They measure infrared radiance from the Earth and atmosphere system, from which the atmospheric composition and temperature can be retrieved using dedicated algorithms, forming the Level 2 (L2) product. The operational near real-time processing of IASI data is conducted by the EUropean organisation for the exploitation of METeorological SATellites (EUMETSAT). It has improved over time, but due to IASI’s large data flow, the whole dataset has not yet been reprocessed backwards. A necessary step that must be completed before initiating this reprocessing is to uniformize the IASI radiance record (Level 1C), which has also changed with time due to various instrumental and software modifications. In 2019, EUMETSAT released a reprocessed IASI-A 2007–2017 radiance dataset that is consistent with both the L1C product generated after 2017 and with IASI-B. First, this study aimed to assess the changes in radiance associated with this update by comparing the operational and reprocessed datasets. The differences in the brightness temperature ranged from 0.02 K at 700 cm−1 to 0.1 K at 2200 cm−1. Additionally, two major updates in 2010 and 2013 were seen to have the largest impact. Then, we investigated the effects on the retrieved temperatures due to successive upgrades to the Level 2 processing chain. We compared IASI L2 with ERA5 reanalysis temperatures. We found differences of ~5–10 K at the surface and between 1 and 5 K in the atmosphere. These differences decreased abruptly after the release of the IASI L2 processor version 6 in 2014. These results suggest that it is not recommended to use the IASI inhomogeneous temperature products for trend analysis, both for temperature and trace gas trends. more
Climate Data Records EUM-Secr Validation

Superparameterised cloud effects in the EMAC general circulation model (v2.50) - Influences of model configuration

Author(s):
Rybka, H.; Tost, H.
Publication title: Geoscientific Model Development
2020
 | Volume: 13 | Issue: 6
2020
DOI: 10.5194/gmd-13-2671-2020
Abstract:
A new module has been implemented in the fifth generation of the ECMWF/Hamburg (ECHAM5)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (E… A new module has been implemented in the fifth generation of the ECMWF/Hamburg (ECHAM5)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model that simulates cloud-related processes on a much smaller grid. This so-called superparameterisation acts as a replacement for the convection parameterisation and large-scale cloud scheme. The concept of embedding a cloud-resolving model (CRM) inside of each grid box of a general circulation model leads to an explicit representation of cloud dynamics. The new model component is evaluated against observations and the conventional usage of EMAC using a convection parameterisation. In particular, effects of applying different configurations of the superparameterisation are analysed in a systematical way. Consequences of changing the CRM's orientation, cell size and number of cells range from regional differences in cloud amount up to global impacts on precipitation distribution and its variability. For some edge case setups, the analysed climate state of superparameterised simulations even deteriorates from the mean observed energy budget. In the current model configuration, different climate regimes can be formed that are mainly driven by some of the parameters of the CRM. Presently, the simulated total cloud cover is at the lower edge of the CMIP5 model ensemble. However, certain "tuning" of the current model configuration could improve the slightly underestimated cloud cover, which will result in a shift of the simulated climate. The simulation results show that especially tropical precipitation is better represented with the superparameterisation in the EMAC model configuration. Furthermore, the diurnal cycle of precipitation is heavily affected by the choice of the CRM parameters. However, despite an improvement of the representation of the continental diurnal cycle in some configurations, other parameter choices result in a deterioration compared to the reference simulation using a conventional convection parameterisation. The ability of the superparameterisation to represent latent and sensible heat flux climatology is independent of the chosen CRM setup. Evaluation of in-atmosphere cloud amounts depending on the chosen CRM setup shows that cloud development can significantly be influenced on the large scale using a too-small CRM domain size. Therefore, a careful selection of the CRM setup is recommended using 32 or more CRM cells to compensate for computational expenses. © 2020 Copernicus GmbH. All rights reserved. more
Application Atmosphere CM-SAF Climate Data Records

State of the Climate in 2019

Author(s):
Blunden, J.; Arndt, D. S.
Publication title: Bulletin of the American Meteorological Society
2020
 | Volume: 101 | Issue: 8
2020
DOI: 10.1175/2020BAMSStateoftheClimate.1
Abstract:
In 2019, the dominant greenhouse gases released into Earth’s atmosphere continued to increase. The annual global average carbon diox… In 2019, the dominant greenhouse gases released into Earth’s atmosphere continued to increase. The annual global average carbon dioxide concentration at Earth’s surface was 409.8 ± 0.1 ppm, an increase of 2.5 ± 0.1 ppm over 2018, and the highest in the modern instrumental record and in ice core records dating back 800000 years. Combined, greenhouse gases and several halogenated gases contributed 3.14 W m−2to radiative forcing, representing a 45% increase since 1990. Carbon dioxide is responsible for about 65% of this radiative forcing. The annual net global uptake of ~2.4 billion metric tons of carbon dioxide by oceans was the highest in the record dating to 1982 and 33% higher than the 1997–2017 average.A weak El Niño at the beginning of 2019 transitioned to ENSO-neutral conditions by mid-year. Even so, the annual global surface temperature across land and oceans was still among the three highest in records dating to the mid- to late 1800s. July 2019 was Earth’s hottest month on record. Well over a dozen countries across Africa, Europe, Asia, Australia, and the Caribbean reported record high annual temperatures. In North America, Alaska experienced its warmest year on record, while the high northern latitudes that encompass the Arctic were second warmest, behind only 2016. Stations in several countries, including Vietnam, the Netherlands, Belgium, Luxembourg, France, and the United Kingdom, set new all-time daily high temperature records for their nations. Australia set a new nationally averaged daily maximum temperature record of 41.9°C on 18 December, breaking the previous record set in 2013 by 1.6°C. Daily temperatures surpassed 40°C for the first time in Belgium and the Netherlands. Lake temperatures increased on average across the globe in 2019; observed lakes in the Northern Hemisphere were covered in ice seven days fewer than the 1981–2010 average, according to phenological indicators. Over land, the growing season was an average of eight days longer than the 2000–10 average in the NH.Above Earth’s surface, the annual lower troposphere tem-perature was third highest to record high, and the lower strato-sphere temperature was third lowest to record low, depending on the dataset analyzed. Middle- and upper-stratospheric temperatures were lowest on record since satellite records be-gan in 1979. In September, Antarctica experienced a dramatic upper-atmosphere warming event that led to the smallest ozone hole since the early 1980s. Below-average Antarctic sea ice extent persisted throughout 2019, continuing a trend that began in September 2016. Net sea ice extent was below the 1981–2010 average for all days of the year, and January and June each set a new low monthly mean sea ice extent record. The Antarctic ice sheet continued to lose mass, with the highest rates of loss occurring in West Antarctica and Wilkes Land, East Antarctica. Across the cryosphere, alpine glaciers continued to lose mass for the 32nd consecutive year. Permafrost temperatures in the European Alps were slightly below the record temperatures measured in 2015, while record high permafrost temperatures were observed at a majority of the observation sites across the high northern latitudes. For the first time in the observational record at 26 sites in interior Alaska and the Seward Peninsula, the active layer did not freeze completely, a result of long-term permafrost warming and back-to-back relatively mild and snowy winters.In March, when Arctic sea ice reached its annual maximum extent, thin, first-year ice comprised ~77% of all ice, compared to about 55% in the 1980s. In September, the minimum sea ice extent tied for the second smallest extent in the 41-year satel-lite record. In the Bering Sea, increasing ocean temperatures and reduced sea ice—which was the lowest on record there for the second consecutive winter—are leading to shifts in fish distributions within some of the most valuable fisheries in the world. Larger and more abundant boreal species, as opposed to smaller and less abundant Arctic species, dominated a large portion of the Arctic shelf in 2018 and 2019. During the 2019 melt season, the extent and magnitude of ice loss over the Greenland ice sheet rivaled 2012, the previous year of record ice loss. Melting of glaciers and ice sheets, along with warming oceans, account for the trend in rising global mean sea level. In 2019, global mean sea level set a new record for the eighth consecutive year, reaching 87.6 mm above the 1993 average when satellite measurements began, with an annual average increase of 6.1 mm from 2018. Ocean heat content measured to 700 m depth was record high, and the globally averaged sea surface temperature was the second highest on record, surpassed only by the record El Niño year of 2016. In October, the Indian Ocean dipole exhibited its greatest magnitude since 1997, associated with dramatic upper ocean warming in the western Indian Ocean basin. While ENSO conditions during 2019 appeared to have limited impacts, many climate events were influenced by the strong positive IOD, which contributed to a large rainfall deficit from the eastern Indian Ocean to the South Pacific Ocean east of Australia. Record heat and dryness in Australia intensified drought conditions already in place following below-average rainfall in 2017 and 2018, leading to severe impacts during late austral spring and summer, including catastrophic wildfires. Smoke from these wildfires, along with the volcanic eruptions of Raikoke (Russia) and Ulawun (Papua New Guinea), helped load the stratosphere with aerosol levels unprecedented since the post-Mt. Pinatubo era of the early 1990s. Indonesia also suffered severe drought and extreme wildfires toward the end of 2019; no rainfall was observed in the East Sumba District of the East Nusa Tenggara Province for 263 days.Conversely, the positive IOD also contributed to excess rainfall over the Horn of Africa from August through December, resulting in widespread flooding across East Africa. Elsewhere, India experienced one of its heaviest summer monsoon rains since 1995 despite a delayed and suppressed monsoon during June. In the United States, rapid snowmelt in the spring, as well as heavy and frequent precipitation in the first half of the year, contributed to extensive flooding in the Midwest throughout spring and summer, notably the Mississippi and Missouri basins. Dry conditions persisted over large parts of western South Africa, in some locations having continued for approximately seven years. Antecedent dry conditions and extreme summer heat waves pushed most of Europe into extreme drought. Due in part to precipitation deficits during December 2018 to January 2019—the peak of the rainy season—wildfires scorched vast areas of the southern Amazonian forests in Bolivia, Brazil, and Peru, as well as in northern Paraguay, later in 2019. Millions of trees and animals perished, with some local extinctions reported. In Siberia, fire activity during the sum-mer was both strong and farther north than usual. This led to a new record of 27 teragrams (1012 g) of carbon emitted from fires in the Arctic, which was more than twice as high than in any preceding year. Closer to the equator, 96 named tropical storms were ob-served during the Northern and Southern Hemisphere storm seasons, well above the 1981–2010 average of 82. Five tropical cyclones reached Saffir–Simpson scale Category 5 intensity. In the North Atlantic basin, Hurricane Dorian caused unprec-edented and tremendous devastation, with over 70 fatalities and damages totaling $3.4 billion (U.S. dollars) in The Bahamas. Tropical Cyclones Idai and Kenneth severely impacted south-eastern Africa in March and April, respectively. Idai resulted in total damages of at least $2.2 billion (U.S. dollars), the costli-est storm on record for the South Indian Ocean basin, as well as the deadliest with over 1200 fatalities across Mozambique, Zimbabwe, Malawi, and Madagascar. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Spatiotemporal variability and trends in global solar radiation over Poland based on satellite-derived data (1986–2015)

Author(s):
Kulesza, Kinga
Publication title: International Journal of Climatology
2020
 | Volume: 40 | Issue: 15
2020
DOI: 10.1002/joc.6596
Abstract:
Incoming solar radiation is the most important factor shaping climate system on Earth and the main element of the surface heat balance. The main aim o… Incoming solar radiation is the most important factor shaping climate system on Earth and the main element of the surface heat balance. The main aim of this study was to investigate the changes in the amount of global solar radiation reaching the Earth's surface in Poland during the 30-year period 1986–2015. Trends in changes and fluctuations in the size of global solar radiation over Poland were determined. The solar radiation was described based on satellite products originating from the Surface Incoming Shortwave Radiation product from the Surface Solar Radiation Data Set – Heliosat, Edition 2 (SARAH-2). The average annual sum of global solar radiation over Poland amounted to 3,902 MJ·m−2. The average annual radiation sums were the smallest in northern Poland and mountain basins, while they were the largest in southern Poland. The average annual radiation sum over Poland increased by 7.16 MJ·m−2·year−1 on average. The areas with the largest increase in the amount of solar radiation had the smallest average radiation sums during the multi-year period (Pomerania, Northern Poland), and those where the increase in radiation was moderate had the highest average radiation sums (Central and Southern Poland). This shows that the spatial differentiation of the amount of solar radiation over Poland was gradually decreasing during this period. A several-year cycle (of 12–13 years) of annual fluctuations in global solar radiation sums was observed using wavelet analysis. The cycle was visible between the early 1990s and 2005. It resulted from the medium-term cyclical component (an 11.3-year cycle which was the strongest until 2010) that occurred in summer. In the long term, the occurrence of cycles in the time series of solar radiation may result from cyclical or quasi-cyclical changes in aerosol concentration, but this requires a separate study and further in-depth research based on much longer data series. more
Application Atmosphere CM-SAF Climate Data Records

Spatial Evaluation and Assimilation of SMAP, SMOS, and ASCAT Satellite Soil Moisture Products Over Africa Using Statistical Techniques

Author(s):
Mousa, B. G.; Shu, Hong
Publication title: Earth and Space Science
2020
 | Volume: 7 | Issue: 1
2020
DOI: 10.1029/2019EA000841
Abstract:
The limited number of in situ stations of surface soil moisture (SM) in Africa creates a shortage in the validation of SM satellite products. Therefor… The limited number of in situ stations of surface soil moisture (SM) in Africa creates a shortage in the validation of SM satellite products. Therefore, this study investigates the performance of Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and the H113 product from the Advanced Scatterometer (ASCAT) on the regional scale over Africa through these goals: (1) validate of satellite SM products against in situ stations and SM data from the ERA-Interim atmospheric reanalysis product, (2) study the spatiotemporal variability of satellite SM products on the regional scale, and (3) evaluate the regional scale error patterns and investigate regions where the assimilation of satellites SM data may add improvement to ERA-Interim. Standard statistical metrics, hovmöller diagrams, and the Triple Collocation (TC) model were used to achieve these goals. Land cover data, Normalized Difference Vegetation Index, and precipitation data were used to interpret results. The validation results based on statistical metrics and TC indicate that over the desert and shrub, passive products showed better performance than ASCAT, while over moderate vegetation areas (grassland), SMAP had the best among SM products. Over high densely vegetated regions, ASCAT showed a high comparatively performance than passive products. The potential regions for assimilation of satellite data sets were selected to be over savannas and grassland regions for ASCAT, and over shrub and grassland regions for SMAP. In particular, SMAP and ASCAT SM data sets are considered more stable than SMOS for data assimilation and capturing the spatial distribution of SM on the regional scale over Africa. more
Application Climate Data Records H-SAF Land

Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions

Author(s):
Kern, S.; Lavergne, T.; Notz, D.; Toudal Pedersen, L.; Tonboe, R.
Publication title: Cryosphere
2020
 | Volume: 14 | Issue: 7
2020
DOI: 10.5194/tc-14-2469-2020
Abstract:
We report on results of a systematic inter-comparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from s… We report on results of a systematic inter-comparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite passive microwave (PMW) observations for the Arctic during summer. The products are compared against SIC and net ice surface fraction (ISF) - SIC minus the per-grid-cell melt pond fraction (MPF) on sea ice - as derived from MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations and observed from ice-going vessels. Like in Kern et al. (2019), we group the 10 products based on the concept of the SIC retrieval used. Group I consists of products of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) and European Space Agency (ESA) Climate Change Initiative (CCI) algorithms. Group II consists of products derived with the Comiso bootstrap algorithm and the National Oceanographic and Atmospheric Administration (NOAA) National Snow and Ice Data Center (NSIDC) SIC climate data record (CDR). Group III consists of Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) and National Aeronautics and Space Administration (NASA) Team (NT) algorithm products, and group IV consists of products of the enhanced NASA Team algorithm (NT2). We find widespread positive and negative differences between PMW and MODIS SIC with magnitudes frequently reaching up to 20 %-25 % for groups I and III and up to 30 %-35 % for groups II and IV. On a pan-Arctic scale these differences may cancel out: Arctic average SIC from group I products agrees with MODIS within 2 %-5 % accuracy during the entire melt period from May through September. Group II and IV products overestimate MODIS Arctic average SIC by 5 %-10 %. Out of group III, ASI is similar to group I products while NT SIC underestimates MODIS Arctic average SIC by 5 %-10 %. These differences, when translated into the impact computing Arctic sea-ice area (SIA), match well with the differences in SIA between the four groups reported for the summer months by Kern et al. (2019). MODIS ISF is systematically overestimated by all products; NT provides the smallest overestimations (up to 25 %) and group II and IV products the largest overestimations (up to 45 %). The spatial distribution of the observed overestimation of MODIS ISF agrees reasonably well with the spatial distribution of the MODIS MPF and we find a robust linear relationship between PMW SIC and MODIS ISF for group I and III products during peak melt, i.e. July and August. We discuss different cases taking into account the expected influence of ice surface properties other than melt ponds, i.e. wet snow and coarse-grained snow/refrozen surface, on brightness temperatures and their ratios used as input to the SIC retrieval algorithms. Based on this discussion we identify the mismatch between the actually observed surface properties and those represented by the ice tie points as the most likely reason for (i) the observed differences between PMW SIC and MODIS ISF and for (ii) the often surprisingly small difference between PMW and MODIS SIC in areas of high melt pond fraction. We conclude that all 10 SIC products are highly inaccurate during summer melt. We hypothesize that the unknown number of melt pond signatures likely included in the ice tie points plays an important role - particularly for groups I and II - and recommend conducting further research in this field. © Author(s) 2020. more
Climate Data Records Cryosphere OSI-SAF Validation

Satellite observations of aerosols and clouds over southern China from 2006 to 2015: Analysis of changes and possible interaction mechanisms

Author(s):
Benas, N.; Fokke Meirink, J.; Karlsson, K.-G.; Stengel, M.; Stammes, P.
Publication title: Atmospheric Chemistry and Physics
2020
 | Volume: 20 | Issue: 1
2020
DOI: 10.5194/acp-20-457-2020
Abstract:
Aerosol and cloud properties over southern China during the 10-year period 2006-2015 are analysed based on observations from passive and active satell… Aerosol and cloud properties over southern China during the 10-year period 2006-2015 are analysed based on observations from passive and active satellite sensors and emission data. The results show a strong decrease in aerosol optical depth (AOD) over the study area, accompanied by an increase in liquid cloud cover and cloud liquid water path (LWP). The most significant changes occurred mainly in late autumn and early winter: AOD decreased by about 35%, coinciding with an increase in liquid cloud fraction by 40% and a near doubling of LWP in November and December. Analysis of emissions suggests that decreases in carbonaceous aerosol emissions from biomass burning activities were responsible for part of the AOD decrease, while inventories of other, anthropogenic emissions mainly showed increases. Analysis of precipitation changes suggests that an increase in precipitation also contributed to the overall aerosol reduction. Possible explanatory mechanisms for these changes were examined, including changes in circulation patterns and aerosol-cloud interactions (ACIs). Further analysis of changes in aerosol vertical profiles demonstrates a consistency of the observed aerosol and cloud changes with the aerosol semi-direct effect, which depends on relative heights of the aerosol and cloud layers: fewer absorbing aerosols in the cloud layer would lead to an overall decrease in the evaporation of cloud droplets, thus increasing cloud LWP and cover. While this mechanism cannot be proven based on the present observation-based analysis, these are indeed the signs of the reported changes. © Author(s) 2020. more
Application Atmosphere CM-SAF Climate Data Records

Reference-Quality Emission and Backscatter Modeling for the Ocean

Author(s):
English, Stephen; Prigent, Catherine; Johnson, Ben; Yueh, Simon; Dinnat, Emmanuel; Boutin, Jacqueline; Newman, Stuart; Anguelova, Magdalena; Meissner, Thomas; Kazumori, Masahiro; Weng, Fuzhong; Supply, Alexandre; Kilic, Lise; Bettenhausen, Michael; Stoffelen, Ad; Accadia, Christophe
Publication title: Bulletin of the American Meteorological Society
2020
 | Volume: 101 | Issue: 10
2020
DOI: 10.1175/BAMS-D-20-0085.1
Climate Data Records Method NWP-SAF Ocean

Random forest regression for improved mapping of solar irradiance at high latitudes

Author(s):
Babar, B.; Luppino, L.T.; Boström, T.; Anfinsen, S.N.
Publication title: Solar Energy
2020
 | Volume: 198
2020
DOI: 10.1016/j.solener.2020.01.034
Abstract:
Datasets from meteorological reanalyses and retrievals from satellites are the available sources of large-scale information about solar radiation. How… Datasets from meteorological reanalyses and retrievals from satellites are the available sources of large-scale information about solar radiation. However, both the reanalyses and the satellite-based estimates can be severely biased, especially in high latitude regions. In this study, surface solar irradiance estimates from the ECMWF Reanalysis 5 (ERA5) and the Cloud, Albedo, Radiation dataset Edition 2 (CLARA-A2) were used as input to a random forest regression (RFR) model to construct a novel dataset with higher accuracy and precision than the input datasets. For daily averages of global horizontal irradiance (GHI) at Norwegian sites, CLARA-A2 and ERA5 respectively produced a root mean squared deviation (RMSD) of 17.9 Wm−2 and 27.1 Wm−2, a mean absolute deviation (MAD) of 11.9 Wm−2 and 17.5 Wm−2, and a bias of −1.5 Wm−2 and 4.3 Wm−2. In contrast, the proposed regression model provided an RMSD of 16.2 Wm−2, an MAD of 10.8 Wm−2, and a bias of 0.0 Wm−2. This shows that the RFR model is both accurate and precise, and significantly reduces both dispersion and bias in the new dataset with respect to the constituent sources. A sky-stratification analysis was performed and it was found that the proposed model provides better estimates under all sky conditions with particular improvements in intermediate-cloudy conditions. The proposed regression model was also tested on five Swedish locations and it was found to improve surface solar irradiance estimates to a similar degree as for the Norwegian locations, thus proving its consistency under similar climatic conditions. © 2020 International Solar Energy Society more
Application Atmosphere CM-SAF Climate Data Records

Present-Day Greenland Ice Sheet Climate and Surface Mass Balance in CESM2

Author(s):
van Kampenhout, L.; Lenaerts, J.T.M.; Lipscomb, W.H.; Lhermitte, S.; Noël, B.; Vizcaíno, M.; Sacks, W.J.; van den Broeke, M.R.
Publication title: Journal of Geophysical Research: Earth Surface
2020
 | Volume: 125 | Issue: 2
2020
DOI: 10.1029/2019JF005318
Abstract:
The response of the Greenland Ice Sheet (GrIS) to a warmer climate is uncertain on long time scales. Climate models, such as those participating in th… The response of the Greenland Ice Sheet (GrIS) to a warmer climate is uncertain on long time scales. Climate models, such as those participating in the Coupled Model Intercomparison Project phase 6 (CMIP6), are used to assess this uncertainty. The Community Earth System Model version 2.1 (CESM2) is a CMIP6 model capable of running climate simulations with either one-way coupling (fixed ice sheet geometry) or two-way coupling (dynamic geometry) to the GrIS. The model features prognostic snow albedo, online downscaling using elevation classes, and a firn pack to refreeze percolating melt water. Here we evaluate the representation of the GrIS surface energy balance and surface mass balance in CESM2 at 1° resolution with fixed GrIS geometry. CESM2 agrees closely with ERA-Interim reanalysis data for key controls on GrIS SMB: surface pressure, sea ice extent, 500 hPa geopotential height, wind speed, and 700 hPa air temperature. Cloudsat-CALIPSO data show that supercooled liquid-containing clouds are adequately represented, whereas comparisons to Moderate Resolution Imaging Spectroradiometer and CM SAF Cloud, Albedo, and Surface Radiation data set from Advanced Very High Resolution Radiometer data second edition data suggest that CESM2 underestimates surface albedo. The seasonal cycle and spatial patterns of surface energy balance and surface mass balance components in CESM2 agree well with regional climate model RACMO2.3p2, with GrIS-integrated melt, refreezing, and runoff bracketed by RACMO2 counterparts at 11 and 1 km. Time series of melt, runoff, and SMB show a break point around 1990, similar to RACMO2. These results suggest that GrIS SMB is realistic in CESM2, which adds confidence to coupled ice sheet-climate experiments that aim to assess the GrIS contribution to future sea level rise. ©2020. The Authors. more
Application CM-SAF Climate Data Records Cryosphere Validation

Probabilistic cloud masking for the generation of CM SAF cloud climate data records from AVHRR and SEVIRI sensors

Author(s):
Karlsson, K.-G.; Johansson, E.; Håkansson, N.; Sedlar, J.; Eliasson, S.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 4
2020
DOI: 10.3390/rs12040713
Abstract:
Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generat… Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generation, cloud screening must be balanced, so both false cloud-free and false cloudy retrievals are minimized. Many methods used in recent CDRs show signs of clear-conservative cloud screening leading to overestimated cloudiness. This study presents a new cloud screening approach for Advanced Very-High-Resolution Radiometer (AVHRR) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery based on the Bayesian discrimination theory. The method is trained on high-quality cloud observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The method delivers results designed for optimally balanced cloud screening expressed as cloud probabilities together with information on for which clouds (minimum cloud optical thickness) the probabilities are valid. Cloud screening characteristics over 28 different Earth surface categories were estimated. Using independent CALIOP observations (including all observed clouds) in 2010 for validation, the total global hit rates for AVHRR data and the SEVIRI full disk were 82% and 85%, respectively. High-latitude oceans had the best performance, with a hit rate of approximately 93%. The results were compared to the CM SAF cLoud, Albedo, and surface RAdiation dataset from AVHRR data-second edition (CLARA-A2) CDR and showed general improvements over most global regions. Notably, the Kuipers' Skill Score improved, verifying a more balanced cloud screening. The new method will be used to prepare the new CLARA-A3 and CLAAS-3 (CLoud property dAtAset using SEVIRI, Edition 3) CDRs in the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project. © 2020 by the author. more
Atmosphere CM-SAF Climate Data Records Method

Precipitation regime classification based on cloud-top temperature time series for spatially-varied parameterization of precipitation models

Author(s):
Lu, S.; ten Veldhuis, M.-C.; van de Giesen, N.; Heemink, A.; Verlaan, M.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 2
2020
DOI: 10.3390/rs12020289
Abstract:
Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-de… Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delineation boundaries of precipitation regimes should be accurately identified. Existing approaches to characterize precipitation regimes by seasonal or other climatological properties do not account for small scale spatial-temporal variability. Precipitation time series can be used to account for this small-scale variability in regime classification. Unfortunately, precipitation products with global coverage perform poorly at small time scales over data scarce regions. A methodology of using satellite-based cloud-top temperature (CTT) time series as a proxy of precipitation time series for precipitation regime classification was developed, and its potential and uncertainty were analyzed. A precipitation regime in this study was defined on the basis of characteristic small-scale temporal distribution and variability of precipitation at a given place. Dynamic time warping was used to calculate the distance between two time series. Criteria to select the optimal temporal scale of time series for clustering and the number of clusters were also developed. The method was validated over Germany and applied to Tanzania, characterized by complex climatology and low density ground observations. This approach was evaluated against precipitation regime classification based on a satellite precipitation product. Results show that CTT outcompetes satellite-based precipitation for classification of precipitation regime classification. The CTT-based classification can be used as precursor to spatially adapted precipitation estimation algorithms where parameters are calibrated by gauge data or other ground-based precipitation observations, and parameterization can be used for satellite-precipitation estimates, precipitation forecasts in numerical or stochastic weather models, etc. © 2020 by the authors. more
Application Atmosphere CM-SAF Climate Data Records

Photovoltaic power potential in West Africa using long-term satellite data

Author(s):
Neher, Ina; Crewell, Susanne; Meilinger, Stefanie; Pfeifroth, Uwe; Trentmann, Jörg
Publication title: Atmospheric Chemistry and Physics
2020
 | Volume: 20 | Issue: 21
2020
DOI: 10.5194/acp-20-12871-2020
Abstract:
This paper addresses long-term historical changes in solar irradiance in West Africa (3 to 20∘ N and 20∘ W to 16∘ E) and the implications for photovol… This paper addresses long-term historical changes in solar irradiance in West Africa (3 to 20∘ N and 20∘ W to 16∘ E) and the implications for photovoltaic systems. Here, we use satellite irradiance (Surface Solar Radiation Data Set – Heliosat, Edition 2.1 – SARAH-2.1) and temperature data from a reanalysis (ERA5) to derive photovoltaic yields. Based on 35 years of data (1983–2017), the temporal and regional variability as well as long-term trends in global and direct horizontal irradiance are analyzed. Furthermore, a detailed time series analysis is undertaken at four locations. According to the high spatial resolution SARAH-2.1 data record (0.05∘×0.05∘), solar irradiance is largest (up to a 300 W m−2 daily average) in the Sahara and the Sahel zone with a positive trend (up to 5 W m−2 per decade) and a lower temporal variability ( more
Application Atmosphere CM-SAF Climate Data Records

Performance of Radiative Transfer Models in the Microwave Region

Author(s):
Moradi, I.; Goldberg, M.; Brath, M.; Ferraro, R.; Buehler, S.A.; Saunders, R.; Sun, N.
Publication title: Journal of Geophysical Research: Atmospheres
2020
 | Volume: 125 | Issue: 6
2020
DOI: 10.1029/2019JD031831
Abstract:
We compared two fast radiative transfer models, Community Radiative Transfer Model (CRTM) and Radiative Transfer for TIROS Operational Vertical Sounde… We compared two fast radiative transfer models, Community Radiative Transfer Model (CRTM) and Radiative Transfer for TIROS Operational Vertical Sounder (RTTOV), with the LBL model Atmospheric Radiative Transfer Simulator (ARTS). We used the measurements from Advanced Technology Microwave Sounder (ATMS) and the Global Precipitation Measurement Microwave Imager (GMI) for evaluation of the radiative transfer models. The models in comparison with the observations and each other performed very well with a mean difference less than 0.5 K for the temperature sounding channels operating near the oxygen absorption band at 60 GHz. There was a difference of up to 1 K among the models as well as compared with the observations for humidity sounding channels operating around water vapor absorption line at 183 GHz. The mean difference between the simulations and observations was up to 6 K for surface sensitive channels. Water vapor and surface sensitive channels also showed to be more sensitive than the temperature sounding channels to the spectroscopy models used to calculate the absorption coefficients. There was a small difference, less than 0.1 K, between brightness temperatures calculated using traditional boxcar and actual Sensor or Spectral Response Functions, except for a difference of 0.25 K for ATMS Channel 6. Double difference technique showed about 1 K difference between water vapor channels from ATMS instruments onboard N20 and National Polar-orbiting Partnership (NPP). However, comparison of a new version of ATMS/NPP observations recently generated using an enhanced calibration algorithm with ATMS/N20 observations showed that the differences between the two instruments are less than 0.5 K after improving the ATMS/NPP calibration. © 2020. American Geophysical Union. All Rights Reserved. more
Atmosphere NWP-SAF Software for CDR development Validation

Open-Source Satellite-Derived Solar Resource Databases Comparison and Validation for Indonesia

Author(s):
Harsarapama, Anindio P.
Publication title: Journal of renewable energy
2020
2020
DOI: 10.1155/2020/2134271
Abstract:
Solar resource data derived from satellite imagery are widely available nowadays, either as an open-source or paid database. This article is intended … Solar resource data derived from satellite imagery are widely available nowadays, either as an open-source or paid database. This article is intended to assess open-source databases, which cover the region of Indonesia. Here, four known solar resource databases, which spatially cover the Indonesian archipelago, have been used, namely, Prediction of Worldwide Energy Resource (POWER), Surface Solar Radiation–Heliosat-East (SARAH-E), CM SAF Cloud, Albedo, Radiation edition 2 (CLARA-A2), and SolarGIS. In addition, a minor portion of the Meteonorm database by Meteotest, around five sample points across Indonesia, has been assessed in terms of coherency to the four mentioned databases. Correlation coefficient and relative bias of the multiyear monthly mean annual cycle global horizontal irradiation (GHI) between pairs of databases are inspected. Three out of four databases are then validated through the available irradiation ground measurement data provided by the World Radiation Data Centre (WRDC). The correlation between each pair varies mostly between 0.7 and 1, which shows that the four databases to a certain extent agree on how the intermonthly variation would behave throughout the year. On the other hand, the validation result reveals that the three databases, i.e., POWER, CLARA-A2, and SARAH-E, are suffering from positive bias error ranging from 3% to 7%. Despite that fact, the correlation between measured and estimated values is still acceptable with SARAH-E showing the best performance among the three. Careful selections and adjustment enable the possibility of these databases to be utilized as a tool for depicting interannual and intermonthly variations of solar irradiation throughout the Indonesian archipelago. more
Atmosphere CM-SAF Climate Data Records Validation

Opportunistic Constant Target Matching—A New Method for Satellite Intercalibration

Author(s):
Buehler, Stefan A.; Prange, Marc; Mrziglod, John; John, Viju O.; Burgdorf, Martin; Lemke, Oliver
Publication title: Earth and Space Science
2020
 | Volume: 7 | Issue: 5
2020
DOI: 10.1029/2019EA000856
Abstract:
Opportunistic constant target matching is a new method for satellite intercalibration. It solves a long-standing issue with the traditional simultaneo… Opportunistic constant target matching is a new method for satellite intercalibration. It solves a long-standing issue with the traditional simultaneous nadir overpass (SNO) method, namely, that it typically provides only data points with cold brightness temperatures for humidity sounding instruments on sun-synchronous satellites. In the new method, a geostationary infrared sensor (SEVIRI) is used to select constant target matches for two different microwave sensors (MHS on NOAA 18 and Metop A). We discuss the main assumptions and limitations of the method and explore its statistical properties with a simple Monte Carlo simulation. The method was tested in a simple case study with real observations for this combination of satellites for MHS Channel 3 at 183 ± 1 GHz, the upper tropospheric humidity channel. For the studied 3-month test period, real observations are found to behave consistently with the simulations, increasing our confidence that the method can be a valuable tool for intercalibration efforts. For the selected case study, the new method confirms that the bias between NOAA 18 and Metop A MHS Channel 3 is very small, with absolute value below 0.05 K. more
Climate Data Records EUM-Secr Method

On the land-sea contrast in the surface solar radiation (Ssr) in the baltic region

Author(s):
Lindfors, A.V.; Hertsberg, A.; Riihelä, A.; Carlund, T.; Trentmann, J.; Müller, R.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 21
2020
DOI: 10.3390/rs12213509
Abstract:
The climatological surface solar radiation (SSR; also called global radiation), which is largely dependent on cloud conditions, is an important indica… The climatological surface solar radiation (SSR; also called global radiation), which is largely dependent on cloud conditions, is an important indicator of the solar energy production potential. In the Baltic area, previous studies have indicated lower cloud amounts over seas than over land, in particular during the summer. However, the existing literature on the SSR climate or how it translates into solar energy potential has not paid much attention to how the SSR behaves quantitatively in relation to the coastline. In this paper, we have studied the climatological land–sea contrast of the SSR over the Baltic area. For this, we used two satellite climate data records, CLARA-A2 and SARAH-2, together with a coastline data base and ground-based pyranometer measurements of the SSR. We analyzed the behaviour of the climatological mean SSR over the period 2003–2013 as a function of the distance to the coastline. The results show that off-shore locations on average receive higher SSR than inland areas and that the land–sea contrast in the SSR is strongest during the summer. Furthermore, the land–sea contrast in the summer time SSR exhibits similar behavior in various parts of the Baltic. For CLARA-A2, which shows better agreement with the ground-based measurements than SARAH-2, the annual SSR is 8% higher 20 km off the coastline than 20 km inland. For summer, i.e., June–August, this difference is 10%. The observed land–sea contrast in the SSR is further shown to correspond closely to the behavior of clouds. Here, convective clouds play an important role as they tend to form over inland areas rather than over the seas during the summer part of the year. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. more
Application Atmosphere CM-SAF Climate Data Records Validation

On the determination of coherent solar climates over a tropical island with a complex topography

Author(s):
Mialhe, Pauline; Pohl, Benjamin; Morel, Béatrice; Trentmann, Jörg; Jumaux, Guillaume; Bonnardot, François; Bessafi, Miloud; Chabriat, Jean-Pierre
Publication title: Solar Energy
2020
 | Volume: 206
2020
DOI: 10.1016/j.solener.2020.04.049
Abstract:
Many tropical islands aim at developing a greener self-sufficient energy production systems based on renewable energy, notably solar-generated electri… Many tropical islands aim at developing a greener self-sufficient energy production systems based on renewable energy, notably solar-generated electricity. This work explores the mean diurnal and annual solar cycles over La Réunion island (southwest Indian Ocean: 21°S, 55.5°E), and their spatial behavior, using the Solar surfAce RAdiation Heliosat – East (SARAH-E) satellite-derived data at high spatial (0.05°×0.05°) and time (hourly) resolutions over period 1999–2016. Comparisons of the SARAH-E data with ground-based measurements over the period 2011–2015 show differences of ~15% for diurnal-seasonal variations. The solar resource over the island displays strong spatial variability, with differences larger than 100 Wm-2 between coastal and mountainous zones. The mean solar resource is lower on the island than on the nearby sea by ~20%. The strongest interactions between the diurnal and annual cycles are found at the windward mid-slopes and near the active volcano, in line with the well-known cloud processes encountered there. A clustering of solar zones, based on diurnal-seasonal cycles, structures the island into a dipole that opposes the western to the eastern side of the island. more
Application Atmosphere CM-SAF Climate Data Records

Observed Temperature Changes in the Troposphere and Stratosphere from 1979 to 2018

Author(s):
Steiner, A. K.; Ladstädter, F.; Randel, W. J.; Maycock, A. C.; Fu, Q.; Claud, C.; Gleisner, H.; Haimberger, L.; Ho, S.-P.; Keckhut, P.; Leblanc, T.; Mears, C.; Polvani, L. M.; Santer, B. D.; Schmidt, T.; Sofieva, V.; Wing, R.; Zou, C.-Z.
Publication title: Journal of Climate
2020
 | Volume: 33 | Issue: 19
2020
DOI: 10.1175/JCLI-D-19-0998.1
Abstract:
Abstract Temperature observations of the upper-air atmosphere are now available for more than 40 years from both ground- and satellite-bas… Abstract Temperature observations of the upper-air atmosphere are now available for more than 40 years from both ground- and satellite-based observing systems. Recent years have seen substantial improvements in reducing long-standing discrepancies among datasets through major reprocessing efforts. The advent of radio occultation (RO) observations in 2001 has led to further improvements in vertically resolved temperature measurements, enabling a detailed analysis of upper-troposphere/lower-stratosphere trends. This paper presents the current state of atmospheric temperature trends from the latest available observational records. We analyze observations from merged operational satellite measurements, radiosondes, lidars, and RO, spanning a vertical range from the lower troposphere to the upper stratosphere. The focus is on assessing climate trends and on identifying the degree of consistency among the observational systems. The results show a robust cooling of the stratosphere of about 1–3 K, and a robust warming of the troposphere of about 0.6–0.8 K over the last four decades (1979–2018). Consistent results are found between the satellite-based layer-average temperatures and vertically resolved radiosonde records. The overall latitude–altitude trend patterns are consistent between RO and radiosonde records. Significant warming of the troposphere is evident in the RO measurements available after 2001, with trends of 0.25–0.35 K per decade. Amplified warming in the tropical upper-troposphere compared to surface trends for 2002–18 is found based on RO and radiosonde records, in approximate agreement with moist adiabatic lapse rate theory. The consistency of trend results from the latest upper-air datasets will help to improve understanding of climate changes and their drivers. more
Application Atmosphere Climate Data Records ROM-SAF

Observed and CMIP5-Simulated Radiative Flux Variability Over West Africa

Author(s):
Mackie, A.; Wild, M.; Brindley, H.; Folini, D.; Palmer, P.I.
Publication title: Earth and Space Science
2020
 | Volume: 7 | Issue: 5
2020
DOI: 10.1029/2019EA001017
Abstract:
We explore the ability of general circulation models in the Coupled Model Intercomparison Project (CMIP5) to recreate observed seasonal variability in… We explore the ability of general circulation models in the Coupled Model Intercomparison Project (CMIP5) to recreate observed seasonal variability in top-of-the-atmosphere and surface radiation fluxes over West Africa. This tests CMIP5 models' ability to describe the radiative energy partitioning, which is fundamental to our understanding of the current climate and its future changes. We use 15 years of the monthly Clouds and the Earth's Radiant Energy System Energy Balanced and Filled (EBAF) product, alongside other satellite, reanalysis, and surface station products. We find that the CMIP5 multimodel mean is generally within the reference product range, with annual mean CMIP5 multimodel mean—EBAF of −0.5 W m−2 for top-of-the-atmosphere reflected shortwave radiation, and 4.6 W m−2 in outgoing longwave radiation over West Africa. However, the range in annual mean of the model seasonal cycles is large (37.2 and 34.0 W m−2 for reflected shortwave radiation and outgoing longwave radiation, respectively). We use seasonal and regional contrasts in all-sky fluxes to infer that the representation of the West African monsoon in numerical models affects radiative energy partitioning. Using clear-sky surface fluxes, we find that the models tend to have more downwelling shortwave and less downwelling longwave radiation than EBAF, consistent with past research. We find models that are drier and have lower aerosol loading tend to show the largest differences. We find evidence that aerosol variability has a larger effect in modulating downwelling shortwave radiation than water vapor in EBAF, while the opposite effect is seen in the majority of CMIP5 models. ©2020. The Authors. more
Application Atmosphere CM-SAF Climate Data Records

Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6

Author(s):
Waliser, Duane; Gleckler, Peter J.; Ferraro, Robert; Taylor, Karl E.; Ames, Sasha; Biard, James; Bosilovich, Michael G.; Brown, Otis; Chepfer, Helene; Cinquini, Luca; Durack, Paul J.; Eyring, Veronika; Mathieu, Pierre-Philippe; Lee, Tsengdar; Pinnock, Simon; Potter, Gerald L.; Rixen, Michel; Saunders, Roger; Schulz, Jörg; Thépaut, Jean-Noël; Tuma, Matthias
Publication title: Geoscientific Model Development
2020
 | Volume: 13 | Issue: 7
2020
DOI: 10.5194/gmd-13-2945-2020
Abstract:
Abstract. The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model e… Abstract. The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets observed variables that can be compared to CMIP model variables; (2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output; (3) provides brief technical documentation for each dataset, designed for nonexperts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits, and limitations; and (4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80; many are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top-of-atmosphere longwave and shortwave radiation; and ozone (O3), methane (CH4), and carbon dioxide (CO2) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g., FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO2). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g., daily) and/or regional products are now receiving more attention. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including (1) an updated obs4MIPs data specifications document that provides additional search facets and generally improves congruence with CMIP6 specifications for model datasets, (2) a set of six easily understood indicators that help guide users as to a dataset's maturity and suitability for application, and (3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth system models used in CMIP. more
Atmosphere Cryosphere EUM-Secr International cooperation Land Method Ocean

Investigating the sensitivity to resolving aerosol interactions in downscaling regional model experiments with WRFv3.8.1 over Europe

Author(s):
Pavlidis, V.; Katragkou, E.; Prein, A.; Georgoulias, A.K.; Kartsios, S.; Zanis, P.; Karacostas, T.
Publication title: Geoscientific Model Development
2020
 | Volume: 13 | Issue: 6
2020
DOI: 10.5194/gmd-13-2511-2020
Abstract:
In this work we present downscaling experiments with the Weather Research and Forecasting model (WRF) to test the sensitivity to resolving aerosol-rad… In this work we present downscaling experiments with the Weather Research and Forecasting model (WRF) to test the sensitivity to resolving aerosol-radiation and aerosol-cloud interactions on simulated regional climate for the EURO-CORDEX domain. The sensitivities mainly focus on the aerosol-radiation interactions (direct and semi-direct effects) with four different aerosol optical depth datasets (Tegen, MAC-v1, MACC, GOCART) being used and changes to the aerosol absorptivity (single scattering albedo) being examined. Moreover, part of the sensitivities also investigates aerosol-cloud interactions (indirect effect). Simulations have a resolution of 0.44 and are forced by the ERA-Interim reanalysis. A basic evaluation is performed in the context of seasonal-mean comparisons to ground-based (E-OBS) and satellite-based (CM SAF SARAH, CLARA) benchmark observational datasets. The impact of aerosols is calculated by comparing it against a simulation that has no aerosol effects. The implementation of aerosol-radiation interactions reduces the direct component of the incoming surface solar radiation by 20 %-30% in all seasons, due to enhanced aerosol scattering and absorption. Moreover the aerosol-radiation interactions increase the diffuse component of surface solar radiation in both summer (30 %-40 %) and winter (5 %-8 %), whereas the overall downward solar radiation at the surface is attenuated by 3 %-8 %. The resulting aerosol radiative effect is negative and is comprised of the net effect from the combination of the highly negative direct aerosol effect (-17 to-5Wm-2) and the small positive changes in the cloud radiative effect (C5Wm-2), attributed to the semi-direct effect. The aerosol radiative effect is also stronger in summer (-12Wm-2) than in winter (-2Wm-2).We also show that modelling aerosol-radiation and aerosol-cloud interactions can lead to small changes in cloudiness, mainly regarding low-level clouds, and circulation anomalies in the lower and mid-troposphere, which in some cases, mainly close to the Black Sea in autumn, can be of statistical significance. Precipitation is not affected in a consistent pattern throughout the year by the aerosol implementation, and changes do not exceed-5% except for the case of unrealistically absorbing aerosol. Temperature, on the other hand, systematically decreases by-0.1 to-0.5 °C due to aerosol-radiation interactions with regional changes that can be up to-1.5 °C. © 2020 Authors. more
Application Atmosphere CM-SAF Climate Data Records

Improving ASCAT Soil Moisture Retrievals With an Enhanced Spatially Variable Vegetation Parameterization

Author(s):
Hahn, Sebastian; Wagner, Wolfgang; Steele-Dunne, Susan C.; Vreugdenhil, Mariette; Melzer, Thomas
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2020
2020
DOI: 10.1109/TGRS.2020.3041340
Abstract:
This study investigates the performance of the TU Wien soil moisture retrieval (TUW-SMR) algorithm by adapting the strength of the vegetation correcti… This study investigates the performance of the TU Wien soil moisture retrieval (TUW-SMR) algorithm by adapting the strength of the vegetation correction. The semiempirical change detection method TUW-SMR exploits the multiangle backscatter observations from spaceborne fan-beam scatterometer systems in order to derive surface soil moisture information expressed in the degree of saturation. The vegetation parameterization of TUW-SMR is controlled by the dry and wet crossover angles that are used to determine the dry and wet backscatter reference. Backscatter observations from the Advanced Scatterometer (ASCAT) are used to produce four soil moisture data sets based on different dry and wet crossover angles describing: 1) a static, respectively, no vegetation correction; 2) the currently used seasonal vegetation correction; 3) a stronger seasonal vegetation correction; and 4) a spatially variable seasonal vegetation correction with the stronger vegetation correction over vegetated areas and no vegetation correction over bare land. All four ASCAT soil moisture data sets are evaluated against soil moisture estimates from GLDAS-2.1 Noah land surface model and the European Space Agency (ESA) climate change initiative (CCI) Passive v04.5 soil moisture product using the triple collocation method and traditional correlation analysis. The results show that the spatially variable vegetation correction overall improves soil moisture estimates in both more densely vegetated areas, e.g., in large parts of North America and Europe, and more sparsely vegetated, e.g., Western Africa. Nonetheless, the experiment also provides insight into challenging retrieval conditions where the TUW-SMR fails to take all relevant backscatter processes into account, e.g., wetlands and bare soils with subsurface scattering. more
Climate Data Records H-SAF Land Method

Improved Rain Screening for Ku-Band Wind Scatterometry

Author(s):
Xu, Xingou; Stoffelen, Ad
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2020
 | Volume: 58 | Issue: 4
2020
DOI: 10.1109/TGRS.2019.2951726
Abstract:
Spaceborne scatterometers for ocean surface winds usually operate in Ku- or C-band. Rather strict quality control (QC) procedures are included in the … Spaceborne scatterometers for ocean surface winds usually operate in Ku- or C-band. Rather strict quality control (QC) procedures are included in the Ku-band wind retrieval chain for labeling rain-contaminated observations. Existing QC factors represent the deviation of measurements from the wind geophysical model function (GMF) modeled measurement surface. Other QC indicators flag outliers by examining neighborhood consistency. In this article, spatial heterogeneity of rain is further exploited by a new indicator for Ku-band QC, namely, JOSS, the speed component of the observation cost function, JO, of the selected solution (JOS) in the 2-D variational ambiguity removal (2-DVAR) step of the wind retrieval. First, the characteristics of 2-DVAR speeds in rainy condition are analyzed, and then, the ability of JOSS in quality labeling is proposed and verified by applying it to the Ku-band scatterometer on-board ScatSat. Its effectiveness for rain screening is confirmed with collocated references from the C-band scatterometer on-board the MetOp-B satellite, which are much less affected by rain. With reference to collocated rain rates from the Global Precipitation Mission (GPM), the more direct relations to rain and wind speed errors of the newly proposed QC indicator JOSS than existing QC indicators, including JOS, are illustrated by the analysis of its correlation with rain rates. In a novel approach, JOSS is applied to accept (unflag) more than 75% of the data rejected by the widely applied maximum likelihood estimation (MLE) thresholds (i.e., correct false alarms) in the tropics. The promising results open a new opportunity for improving QC of rain in the Ku-band wind scatterometry benefitting scatterometer applications. more
Atmosphere Climate Data Records OSI-SAF Validation

Global scale error assessments of soil moisture estimates from microwave-based active and passive satellites and land surface models over forest and mixed irrigated/dryland agriculture regions

Author(s):
Kim, Hyunglok; Wigneron, Jean-Pierre; Kumar, Sujay; Dong, Jianzhi; Wagner, Wolfgang; Cosh, Michael H.; Bosch, David D.; Collins, Chandra Holifield; Starks, Patrick J.; Seyfried, Mark; Lakshmi, Venkataraman
Publication title: Remote Sensing of Environment
2020
 | Volume: 251
2020
DOI: 10.1016/j.rse.2020.112052
Abstract:
Over the past four decades, satellite systems and land surface models have been used to estimate global-scale surface soil moisture (SSM). However, in… Over the past four decades, satellite systems and land surface models have been used to estimate global-scale surface soil moisture (SSM). However, in areas such as densely vegetated and irrigated regions, obtaining accurate SSM remains challenging. Before using satellite and model-based SSM estimates over these areas, we should understand the accuracy and error characteristics of various SSM products. Thus, this study aimed to compare the error characteristics of global-scale SSM over vegetated and irrigated areas as obtained from active and passive satellites and model-based data: Advanced Scatterometer (ASCAT), Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture Active Passive (SMAP), European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5), and Global Land Data Assimilation System (GLDAS). We employed triple collocation analysis (TCA) and caluclated conventional error metrics from in-situ SSM measurements. We also considered all possible triplets from 6 different products and showed the viability of considering the standard deviation of TCA-based numbers in producing robust results. Over forested areas, it was expected that model-based SSM data might provide more accurate SSM estimates than satellites due to the intrinsic limitations of microwave-based systems. Alternately, over irrigated regions, observation-based SSM data were expected to be more accurate than model-based products because land surface models (LSMs) cannot capture irrigation signals caused by human activities. Contrary to these expectations, satellite-based SSM estimates from ASCAT, SMAP, and SMOS showed fewer errors than ERA5 and GLDAS SSM products over vegetated conditions. Furthermore, over irrigated areas, ASCAT, SMOS, and SMAP outperformed other SSM products; however, model-based data from ERA5 and GLDAS outperformed AMSR2. Our results emphasize that, over irrgated areas, considering satellite-based SSM data as alternatives to model-based SSM data sometimes produces misleading results; and considering model-based data as alternatives to satellite-based SSM data in forested areas can also sometimes be misleading. In addition, we discovered that no products showed much degradation in TCA-based errors under different vegetated conditions, while different irrigation conditions impacted both satellite and model-based SSM data sets. The present research demonstrates that limitations in satellite and modeled SSM data can be overcome in many areas through the synergistic use of satellite and model-based SSM products, excluding areas where satellite-based data are masked out. In fact, when four satellite and model data sets are used selectively, the probability of obtaining SSM with stronger signal than noise can be close to 100%. more
Climate Data Records H-SAF Land Validation

Extending the Global Space-Based Inter-Calibration System (GSICS) to Tie Satellite Radiances to an Absolute Scale

Author(s):
Hewison, Tim J.; Doelling, David R.; Lukashin, Constantine; Tobin, David; O. John, Viju; Joro, Sauli; Bojkov, Bojan
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 11
2020
DOI: 10.3390/rs12111782
Abstract:
The Global Space-based Inter-Calibration System (GSICS) routinely monitors the calibration of various channels of Earth-observing satellite instrument… The Global Space-based Inter-Calibration System (GSICS) routinely monitors the calibration of various channels of Earth-observing satellite instruments and generates GSICS Corrections, which are functions that can be applied to tie them to reference instruments. For the infrared channels of geostationary imagers GSICS algorithms are based on comparisons of collocated observations with hyperspectral reference instruments; whereas Pseudo Invariant Calibration Targets are currently used to compare the counterpart channels in the reflected solar band to multispectral reference sensors. This paper discusses how GSICS products derived from both approaches can be tied to an absolute scale using specialized satellite reference instruments with SI-traceable calibration on orbit. This would provide resilience against gaps between reference instruments and drifts in their calibration outside their overlap period and allow construction of robust and harmonized data records from multiple satellite sources to build Fundamental Climate Data Records, as well as more uniform environmental retrievals in both space and time, thus improving inter-operability. more
EUM-Secr International cooperation Validation

Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record

Author(s):
Gleisner, Hans; Lauritsen, Kent B.; Nielsen, Johannes K.; Syndergaard, Stig
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 6
2020
DOI: 10.5194/amt-13-3081-2020
Abstract:
Abstract. We here present results from an evaluation of the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) gridded monthly mea… Abstract. We here present results from an evaluation of the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) gridded monthly mean climate data record (CDR v1.0), based on Global Positioning System (GPS) radio occultation (RO) data from the CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate), and Metop satellite missions. Systematic differences between RO missions, as well as differences of RO data relative to ERA-Interim reanalysis data, are quantified. The methods used to generate gridded monthly mean data are described, and the correction of monthly mean RO climatologies for sampling errors, which is essential for combining data from RO missions with different sampling characteristics, is evaluated. We find good overall agreement between the ROM SAF gridded monthly mean CDR and the ERA-Interim reanalysis, particularly in the 8–30 km height interval. Here, the differences largely reflect time-varying biases in ERA-Interim, suggesting that the RO data record has a better long-term stability than ERA-Interim. Above 30–40 km altitude, the differences are larger, particularly for the pre-COSMIC era. In the 8–30 km altitude region, the observational data record exhibits a high degree of internal consistency between the RO satellite missions, allowing us to combine data into multi-mission records. For global mean bending angle, the consistency is better than 0.04 %, for refractivity it is better than 0.05 %, and for global mean dry temperature the consistency is better than 0.15 K in this height interval. At altitudes up to 40 km, these numbers increase to 0.08 %, 0.11 %, and 0.50 K, respectively. The numbers can be up to a factor of 2 larger for certain latitude bands compared to global means. Below about 8 km, the RO mission differences are larger, reducing the possibilities to generate multi-mission data records. We also find that the residual sampling errors are about one-third of the original and that they include a component most likely related to diurnal or semi-diurnal cycles. more
Atmosphere Climate Data Records ROM-SAF Validation

Evaluating and improving the treatment of gases in radiation schemes: the Correlated K-Distribution Model Intercomparison Project (CKDMIP)

Author(s):
Hogan, Robin J.; Matricardi, Marco
Publication title: GEOSCIENTIFIC MODEL DEVELOPMENT
2020
 | Volume: 13 | Issue: 12
2020
DOI: 10.5194/gmd-13-6501-2020
Abstract:
Most radiation schemes in weather and climate models use the “correlated k distribution” (CKD) method to treat gas absorption, which approximates a br… Most radiation schemes in weather and climate models use the “correlated k distribution” (CKD) method to treat gas absorption, which approximates a broadband spectral integration by N pseudo-monochromatic calculations. Larger N means more accuracy and a wider range of gas concentrations can be simulated but at greater computational cost. Unfortunately, the tools to perform this efficiency-accuracy trade-off (e.g. to generate separate CKD models for applications such as short-range weather forecasting to climate modelling) are unavailable to the vast majority of users of radiation schemes. This paper describes the experimental protocol for the Correlated K-Distribution Model Intercomparison Project (CKDMIP), whose purpose is to use benchmark line-by-line calculations: (1) to evaluate the accuracy of existing CKD models, (2) to explore how accuracy varies with N for CKD models submitted by CKDMIP participants, (3) to understand how different choices in the way that CKD models are generated affect their accuracy for the same N, and (4) to generate freely available datasets and software facilitating the development of new gas-optics tools. The datasets consist of the high-resolution longwave and shortwave absorption spectra of nine gases for a range of atmospheric conditions, realistic and idealized. Thirty-four concentration scenarios for the well-mixed greenhouse gases are proposed to test CKD models from palaeo- to future-climate conditions. We demonstrate the strengths of the protocol in this paper by using it to evaluate the widely used Rapid Radiative Transfer Model for General Circulation Models (RRTMG). more
Application Atmosphere NWP-SAF Software for CDR development

ERAstar: A High-Resolution Ocean Forcing Product

Author(s):
Trindade, Ana; Portabella, Marcos; Stoffelen, Ad; Lin, Wenming; Verhoef, Anton
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2020
 | Volume: 58 | Issue: 2
2020
DOI: 10.1109/TGRS.2019.2946019
Abstract:
To address the growing demand for accurate high-resolution ocean wind forcing from the ocean modeling community, we develop a new forcing product, ERA… To address the growing demand for accurate high-resolution ocean wind forcing from the ocean modeling community, we develop a new forcing product, ERA*, by means of a geolocated scatterometer-based correction applied to the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis or ERA-interim (hereafter referred to as ERAi). This method successfully corrects for local wind vector biases present in the ERAi output globally. Several configurations of the ERA* are tested using complementary scatterometer data [advanced scatterometer (ASCAT)-A/B and oceansat-2 scatterometer (OSCAT)] accumulated over different temporal windows, verified against independent scatterometer data [HY-2A scatterometer (HSCAT)], and evaluated through spectral analysis to assess the geophysical consistency of the new stress equivalent wind fields (U10S). Due to the high quality of the scatterometer U10S, ERA* contains some of the physical processes missing or misrepresented in ERAi. Although the method is highly dependent on sampling, it shows potential, notably in the tropics. Short temporal windows are preferred, to avoid oversmoothing of the U10S fields. Thus, corrections based on increased scatterometer sampling (use of multiple scatterometers) are required to capture the detailed forcing errors. When verified against HSCAT, the ERA* configurations based on multiple scatterometers reduce the vector root-mean-square difference about 10% with respect to that of ERAi. ERA* also shows a significant increase in small-scale true wind variability, observed in the U10S spectral slopes. In particular, the ERA* spectral slopes consistently lay between those of HSCAT and ERAi, but closer to HSCAT, suggesting that ERA* effectively adds spatial scales of about 50 km, substantially smaller than those resolved by global numerical weather prediction (NWP) output over the open ocean (about 150 km). more
Application Atmosphere Climate Data Records OSI-SAF

Does ASCAT observe the spring reactivation in temperate deciduous broadleaf forests?

Author(s):
Pfeil, Isabella; Wagner, Wolfgang; Forkel, Matthias; Dorigo, Wouter; Vreugdenhil, Mariette
Publication title: Remote Sensing of Environment
2020
 | Volume: 250
2020
DOI: 10.1016/j.rse.2020.112042
Abstract:
Scatterometer observations over land are sensitive to the water content in soil and vegetation, but have been rarely used to study seasonal changes in… Scatterometer observations over land are sensitive to the water content in soil and vegetation, but have been rarely used to study seasonal changes in the plant water status and seasonal development of deciduous trees. Here we use Advanced Scatterometer (ASCAT) observations to investigate the sensitivity of C-band backscatter to spring phenology of temperate deciduous broadleaf forests in Austria. ASCAT's multi-angle looking capability enables the observation of backscatter over a large range of incidence angles. The vegetation status affects the slope of the backscatter-incidence angle relationship. We discovered a maximum in the slope around the month April, hereafter referred to as spring peak, predominantly in regions covered by deciduous broadleaf forest. We hypothesized that the spring peak indicates the average timing of leaf emergence in the deciduous trees in the sensor footprint. The hypothesis was tested by comparing the timing of the spring peak to leaf unfolding observations from the PEP725 phenology database, to the increase of leaf area index (LAI) during spring, and to temperature. Our results demonstrate a good agreement between the ASCAT spring peaks, phenology observations and temperature conditions. The steepest increase in LAI however lags behind the ASCAT peak by several days to a few weeks, suggesting that the spring peak in fact marks the timing of maximum woody water content, which occurs right before leaf emergence. Based on these observations, we conclude that the ASCAT signal has a high sensitivity to spring reactivation and in particular water uptake of bare deciduous broadleaf trees. Our findings might provide the basis for novel developments to estimate eco-physiological changes of forests during spring at large scales. more
Application Climate Data Records H-SAF Land

Diurnal black-sky surface albedo parameterization of snow

Author(s):
Manninen, T.; Jääskeläinen, E.; Riihelä, A.
Publication title: Journal of Applied Meteorology and Climatology
2020
 | Volume: 59 | Issue: 9
2020
DOI: 10.1175/JAMC-D-20-0036.1
Abstract:
Surface albedo, the fraction of incoming solar radiation reflected hemispherically by the surface, is an essential climate variable (ECV) directly rel… Surface albedo, the fraction of incoming solar radiation reflected hemispherically by the surface, is an essential climate variable (ECV) directly related to the energy budget of Earth. The presence and properties of snow cover alter surface albedo significantly, with variability in temporal scales reaching from seasonal to diurnal. The diurnal variation of snow albedo is typically parameterized with the solar zenith angle, but it cannot take into account asymmetry with respect to midday. Using the solar azimuth angle instead is suggested, since especially in the melting season the snow albedo varies highly asymmetrically during the day. To derive a general time-and latitude-independent formula, the azimuth angle values are normalized. Baseline Surface Radiation Network data are used to derive an empirical formula for the diurnal variation of snow black-sky surface albedo. The overall accuracy is on the order of 0.02, and the relative accuracy is about 3%. © 2020 American Meteorological Society. more
CM-SAF Climate Data Records Cryosphere Validation

Dissecting effects of orbital drift of polar-orbiting satellites on accuracy and trends of climate data records of cloud fractional cover

Author(s):
Bojanowski, J.S.; Musiał, J.P.
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 12
2020
DOI: 10.5194/amt-13-6771-2020
Abstract:
Radiometers such as the AVHRR (Advanced Very High Resolution Radiometer) mounted aboard a series of NOAA and MetOp (Meteorological Operational) polaro… Radiometers such as the AVHRR (Advanced Very High Resolution Radiometer) mounted aboard a series of NOAA and MetOp (Meteorological Operational) polarorbiting satellites provide 4-decade-long global climate data records (CDRs) of cloud fractional cover. Generation of such long datasets requires combining data from consecutive satellite platforms. A varying number of satellites operating simultaneously in the morning and afternoon orbits, together with satellite orbital drift, cause the uneven sampling of the cloudiness diurnal cycle along a course of a CDR. This in turn leads to significant biases, spurious trends, and inhomogeneities in the data records of climate variables featuring the distinct diurnal cycle (such as clouds). To quantify the uncertainty and magnitude of spurious trends in the AVHRR-based cloudiness CDRs, we sampled the 30 min reference CM SAF (European Organisation for the Exploitation of Meteorological Satellites EUMETSAT Satellite Application Facility on Climate Monitoring) Cloud Fractional Cover dataset derived from Meteosat First and Second Generation (COMET) at times of the NOAA and MetOp satellite overpasses. The sampled cloud fractional cover (CFC) time series were aggregated to monthly means and compared with the reference COMET dataset covering the Meteosat disc (up to 60° N, S, W, and E). For individual NOAA and MetOp satellites the errors in mean monthly CFC reach ±10 % (bias) and ±7 % per decade (spurious trends). For the combined data record consisting of several NOAA and MetOp satellites, the CFC bias is 3 %, and the spurious trends are 1 % per decade. This study proves that before 2002 the AVHRR-derived CFC CDRs do not comply with the GCOS (Global Climate Observing System) temporal stability requirement of 1 % CFC per decade just due to the satellite orbital-drift effect. After this date the requirement is fulfilled due to the numerous NOAA and MetOp satellites operating simultaneously. Yet, the time series starting in 2003 is shorter than 30 years, which makes it difficult to draw reliable conclusions about longterm changes in CFC. We expect that the error estimates provided in this study will allow for a correct interpretation of the AVHRR-based CFC CDRs and ultimately will contribute to the development of a novel satellite orbital-drift correction methodology widely accepted by the AVHRR-based CDR providers. © 2020 Author(s). more
Atmosphere CM-SAF Climate Data Records Validation

Consistency and structural uncertainty of multi-mission GPS radio occultation records

Author(s):
Steiner, Andrea K.; Ladstädter, Florian; Ao, Chi O.; Gleisner, Hans; Ho, Shu-Peng; Hunt, Doug; Schmidt, Torsten; Foelsche, Ulrich; Kirchengast, Gottfried; Kuo, Ying-Hwa; Lauritsen, Kent B.; Mannucci, Anthony J.; Nielsen, Johannes K.; Schreiner, William; Schwärz, Marc; Sokolovskiy, Sergey; Syndergaard, Stig; Wickert, Jens
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 5
2020
DOI: 10.5194/amt-13-2547-2020
Abstract:
Abstract. Atmospheric climate monitoring requires observations of high quality that conform to the criteria of the Global Climate Observing System (GC… Abstract. Atmospheric climate monitoring requires observations of high quality that conform to the criteria of the Global Climate Observing System (GCOS). Radio occultation (RO) data based on Global Positioning System (GPS) signals are available since 2001 from several satellite missions with global coverage, high accuracy, and high vertical resolution in the troposphere and lower stratosphere. We assess the consistency and long-term stability of multi-satellite RO observations for use as climate data records. As a measure of long-term stability, we quantify the structural uncertainty of RO data products arising from different processing schemes. We analyze atmospheric variables from bending angle to temperature for four RO missions, CHAMP, Formosat-3/COSMIC, GRACE, and Metop, provided by five data centers. The comparisons are based on profile-to-profile differences aggregated to monthly medians. Structural uncertainty in trends is found to be lowest from 8 to 25 km of altitude globally for all inspected RO variables and missions. For temperature, it is more
Atmosphere Climate Data Records ROM-SAF Validation

Comparison of surface solar irradiance from ground observations and satellite data (1990–2016) over a complex orography region (piedmont—Northwest Italy)

Author(s):
Manara, V.; Stocco, E.; Brunetti, M.; Diolaiuti, G.A.; Fugazza, D.; Pfeifroth, U.; Senese, A.; Trentmann, J.; Maugeri, M.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 23
2020
DOI: https://doi.org/10.3390/rs12233882
Abstract:
Climate Monitoring Satellite Application Facility (CM SAF) surface solar irradiance (SSI) products were compared with ground-based observations over t… Climate Monitoring Satellite Application Facility (CM SAF) surface solar irradiance (SSI) products were compared with ground-based observations over the Piedmont region (north-western Italy) for the period 1990–2016. These products were SARAH-2.1 (Surface Solar Radiation DataSet—Heliosat version 2.1) and CLARA-A2 (Cloud, Albedo and Surface Radiation dataset version A2). The aim was to contribute to the discussion on the representativeness of satellite SSI data including a focus on high-elevation areas. The comparison between SSI averages shows that for low OCI (orographic complexity index) stations, satellite series have higher values than corresponding ground-based observations, whereas for high OCI stations, SSI values for satellite records are mainly lower than for ground stations. The comparison between SSI anomalies highlights that satellite records have an excellent performance in capturing SSI day-to-day variability of ground-based low OCI stations. In contrast, for high OCI stations, the agreement is much lower, due to the higher uncertainty in both satellite and ground-based records. Finally, if the temporal trends are considered, average low-elevation ground-based SSI observations show a positive trend, whereas satellite records do not highlight significant trends. Focusing on high-elevation stations, the observed trends for ground-based and satellite records are more similar with the only exception of summer. This divergence seems to be due to the relevant role of atmospheric aerosols on SSI trends. more
Atmosphere CM-SAF Climate Data Records Validation

Comparison of long-term solar radiation trends from CM SAF satellite products with ground-based data at the Iberian Peninsula for the period 1985–2015

Author(s):
Montero-Martín, Javier; Antón, Manuel; Vaquero-Martínez, Javier; Sanchez-Lorenzo, Arturo
Publication title: Atmospheric Research
2020
 | Volume: 236
2020
DOI: 10.1016/j.atmosres.2019.104839
Abstract:
The aim of this work is to analyse the quality of long-term trends of surface incoming shortwave solar radiation (SIS) derived from two satellite data… The aim of this work is to analyse the quality of long-term trends of surface incoming shortwave solar radiation (SIS) derived from two satellite datasets from the EUMETSAT Satellite Application on Climate Monitoring (CM SAF): the SIS Data Set from the Advanced Very High-Resolution Radiometer (AVHRR) data, Edition 2 (CLARA-A2), and the SIS Data Set-Heliosat, Edition 2 (SARAH-2). In order to achieve this goal, reference ground-based SIS measurements recorded at 12 stations over the Iberian Peninsula for the period 1985–2015 are used in this study. Firstly, the two satellite datasets have been compared against ground-based SIS measurements at 12 surface sites, showing a good agreement (i.e., R = 0.83 in SARAH-2 and R = 0.80 in CLARA-A2 on an annual basis). However, the two satellite datasets substantially underestimate the SIS trends found for the ground-based measurements. Thus, while the ground-based SIS data reported trends between −0.5 and + 6.5 Wm−2decade−1 (with statistical significance at 95% level at most stations), the satellite datasets gave trends lower for all locations (without statistical significance); between −0.4 and + 3.8 Wm−2decade−1 for CLARA-A2, and between +0.2 and + 2.8 Wm−2decade−1 for SARAH-2. It is worth to mention that the seasonal analysis of the SIS trends for both ground-based and satellite data displays a reasonably good agreement in spring (i.e., high positive trends), in accordance with the notable decline in the cloudiness for this season in the study region. By contrast, satellite products exhibit smaller SIS anomalies than ground-based data in summer, particularly from the beginning 2000s, which could be related to well-known decrease in the aerosol load over the study region. more
Atmosphere CM-SAF Climate Data Records Validation

Comparison of Advanced Technology Microwave Sounder Biases Estimated Using Radio Occultation and Hurricane Florence (2018) Captured by NOAA-20 and S-NPP

Author(s):
Tian, Xiaoxu; Zou, Xiaolei
Publication title: Advances in Atmospheric Sciences
2020
 | Volume: 37 | Issue: 3
2020
DOI: 10.1007/s00376-019-9119-5
Abstract:
The second Advanced Technology Microwave Sounder (ATMS) was onboard the National Oceanic and Atmospheric Administration (NOAA)-20 satellite when launc… The second Advanced Technology Microwave Sounder (ATMS) was onboard the National Oceanic and Atmospheric Administration (NOAA)-20 satellite when launched on 18 November 2017. Using nearly six months of the earliest NOAA-20 observations, the biases of the ATMS instrument were compared between NOAA-20 and the Suomi National Polar-Orbiting Partnership (S-NPP) satellite. The biases of ATMS channels 8 to 13 were estimated from the differences between antenna temperature observations and model simulations generated from Meteorological Operational (MetOp)-A and MetOp-B satellites’ Global Positioning System (GPS) radio occultation (RO) temperature and water vapor profiles. It was found that the ATMS onboard the NOAA-20 satellite has generally larger cold biases in the brightness temperature measurements at channels 8 to 13 and small standard deviations. The observations from ATMS on both S-NPP and NOAA-20 are shown to demonstrate an ability to capture a less than 1-h temporal evolution of Hurricane Florence (2018) due to the fact that the S-NPP orbits closely follow those of NOAA-20. more
Application Atmosphere Climate Data Records ROM-SAF

Cloudiness information services for solar energy management in West Africa

Author(s):
Danso, D.K.; Anquetin, S.; Diedhiou, A.; Adamou, R.
Publication title: Atmosphere
2020
 | Volume: 11 | Issue: 8
2020
DOI: https://doi.org/10.3390/atmos11080857
Abstract:
In West Africa (WA), interest in solar energy development has risen in recent years with many planned and ongoing projects currently in the region. Ho… In West Africa (WA), interest in solar energy development has risen in recent years with many planned and ongoing projects currently in the region. However, a major drawback to this development in the region is the intense cloud cover that reduces the incoming solar radiation when present and causes fluctuations in solar power production. Therefore, understanding the occurrence of clouds and their link to the surface solar radiation in the region is important for making plans to manage future solar energy production. In this study, we use the state-of-the-art European Centre for Medium-range Weather Forecasts ReAnalysis (ERA5) dataset to examine the occurrence and persistence of cloudy and clear-sky conditions in the region. Then, we investigate the effects of cloud cover on the quantity and variability of the incoming solar radiation. The cloud shortwave radiation attenuation (CRA↓SW) is used to quantify the amount of incoming solar radiation that is lost due to clouds. The results showed that the attenuation of incoming solar radiation is stronger in all months over the southern part of WA near the Guinea Coast. Across the whole region, the maximum attenuation occurs in August, with a mean CRA↓SW of about 55% over southern WA and between 20% and 35% in the Sahelian region. Southern WA is characterized by a higher occurrence of persistent cloudy conditions, while the Sahel region and northern WA are associated with frequent clear-sky conditions. Nonetheless, continuous periods with extremely low surface solar radiation were found to be few over the whole region. The analysis also showed that the surface solar radiation received from November to April only varies marginally from one year to the other. However, there is a higher uncertainty during the core of the monsoon season (June to October) with regard to the quantity of incoming solar radiation. The results obtained show the need for robust management plans to ensure the long-term success of solar energy projects in the region more
Atmosphere CM-SAF Climate Data Records Validation

Cloud Cover over the Arabian Peninsula from Global Remote Sensing and Reanalysis Products

Author(s):
Yousef, Latifa A.; Temimi, Marouane; Molini, Annalisa; Weston, Michael; Wehbe, Youssef; Mandous, Abdulla Al
Publication title: Atmospheric Research
2020
 | Volume: 238
2020
DOI: 10.1016/j.atmosres.2020.104866
Abstract:
Clouds – their coverage, nature, and interactions with the energy budget of the planet – represent one of the primary sources of uncertainty in future… Clouds – their coverage, nature, and interactions with the energy budget of the planet – represent one of the primary sources of uncertainty in future climate prediction. Despite the crucial role of desert clouds in the distribution of water and energy budgets, their climatology is still largely incomplete. With arid regions projected to become dryer under global warming conditions, understanding the characteristics of their cloud cover can provide critical insights. In this work, cloud coverage was investigated over one of the Earth's most arid regions – the Arabian Peninsula. Four total cloud cover (TCC) products, namely the International Satellite Cloud Climatology Project H (ISCCP), the CM SAF Cloud, Albedo and Surface Radiation AVHRR 2 (CLARA) satellite datasets, the National Centers for Environmental Prediction – National Center for Atmospheric Research (NCEP–NCAR) Reanalysis (R-2) (NCEP) and the ECMWF Interim Re-Analysis (ERA) reanalyses, were used to construct a climatology of desert clouds over the peninsula between 1984 and 2009, accounting for the different products' uncertainties and limitations. Satellite retrievals and reanalysis fields were first validated against ground observations from the United Arab Emirates, for which homogeneity assessments were conducted. The validation was done using statistical indicators, including Normalized Root Mean Square Errors (nRMSE), relative biases (rBIAS), and correlation coefficients, on monthly and seasonal scales. The ISCCP dataset resulted in the highest correlations with the ground observations (overall 0.38) and the lowest nRMSE (overall 0.54), while CLARA had the lowest rBIAS (overall 0.02). All products showed discrepancies when compared to the ground observations, both annually and on a seasonal basis. When extended to the entire Arabian Peninsula, the satellite and reanalysis products showed decreasing spring and increasing summer (except for ISCCP) TCC evolution across the region. At inter-annual scales, the TCC over the peninsula showed a significant discontinuity in 1998. This shift could be linked to the forcing of the El Niño Southern Oscillation on water vapor transport over the region, as well as to documented artifacts in satellite retrievals and model outputs. These discrepancies are indicative of a need for detailed assessments to be made of the uncertainties existing in TCC data for the Arabian Peninsula. Plain Language Summary Clouds represent a primary source of uncertainty in future climate predictions. This is particularly pronounced in dryland clouds, given their sporadic and intermittent nature. With global warming predicted to enhance aridification trends in terrestrial arid zones, historical cloudiness trends over arid and hyper arid regions are very important – yet their climatology to date is still largely incomplete. The quality of observations and/or model outputs are an important consideration, making validation and intercomparison assessments imperative. This work investigated cloud cover over the Arabian Peninsula, one of the most arid regions on the Earth. Four cloud cover datasets were used, derived from satellite measurements and atmospheric reanalysis model outputs. The selected study period was between 1984 and 2009. The four datasets were initially compared with observations taken at ground stations in the United Arab Emirates. The four products were then studied over the entire Arabian Peninsula. Results showed that cloud cover displayed marked seasonal characteristics and large inter-annual temporal evolution. An abrupt change in regional cloud cover time series was found to occur in 1998. This could be attributed to the forcing of the El Niño Southern Oscillation, although significant documented uncertainties in satellite products over this time span call for deeper investigations of this causal relation. more
Atmosphere CM-SAF Climate Data Records Validation

Changes in satellite-based cloud parameters in the Baltic Sea region during spring and summer (1982–2015)

Author(s):
Post, Piia
Publication title: Advances in Science and Research
2020
 | Volume: 17
2020
DOI: 10.5194/asr-17-219-2020
Abstract:
The satellite-based cloud climate data record CLARA-A2 has been used to analyse regional average time-series and regional maps of trends in the Baltic… The satellite-based cloud climate data record CLARA-A2 has been used to analyse regional average time-series and regional maps of trends in the Baltic Sea region, 1982–2015. The investigated cloud parameters were total fractional cloud cover and cloud top height. Cloud observations from the Tartu-Tõravere meteorological station were used as reference data for the same period. Fractional cloud cover from CLARA-A2 was in a good agreement with in situ data regarding the maxima and minima years and a downward trend in March over the 1982–2015 period. In June the fractional cloud cover interannual variability was very high and no clear trend was seen. For cloud top heights summer and spring regional averages showed opposite signs of the trend: for June positive and for March negative. Winter and autumn seasons have been left out of analysis due to too large uncertainties in cloud products over latitudes higher than 60∘. more
Application Atmosphere CM-SAF Climate Data Records

Benefits and added value of convection-permitting climate modeling over Fenno-Scandinavia

Author(s):
Lind, P.; Belušić, D.; Christensen, O.B.; Dobler, A.; Kjellström, E.; Landgren, O.; Lindstedt, D.; Matte, D.; Pedersen, R.A.; Toivonen, E.; Wang, F.
Publication title: Climate Dynamics
2020
 | Volume: 55 | Issue: 7-8
2020
DOI: 10.1007/s00382-020-05359-3
Abstract:
Convection-permitting climate models have shown superior performance in simulating important aspects of the precipitation climate including extremes a… Convection-permitting climate models have shown superior performance in simulating important aspects of the precipitation climate including extremes and also to give partly different climate change signals compared to coarser-scale models. Here, we present the first long-term (1998–2018) simulation with a regional convection-permitting climate model for Fenno-Scandinavia. We use the HARMONIE-Climate (HCLIM) model on two nested grids; one covering Europe at 12 km resolution (HCLIM12) using parameterized convection, and one covering Fenno-Scandinavia with 3 km resolution (HCLIM3) with explicit deep convection. HCLIM12 uses lateral boundaries from ERA-Interim reanalysis. Model results are evaluated against reanalysis and various observational data sets, some at high resolutions. HCLIM3 strongly improves the representation of precipitation compared to HCLIM12, most evident through reduced “drizzle” and increased occurrence of higher intensity events as well as improved timing and amplitude of the diurnal cycle. This is the case even though the model exhibits a cold bias in near-surface temperature, particularly for daily maximum temperatures in summer. Simulated winter precipitation is biased high, primarily over complex terrain. Considerable undercatchment in observations may partly explain the wet bias. Examining instead the relative occurrence of snowfall versus rain, which is sensitive to variance in topographic heights it is shown that HCLIM3 provides added value compared to HCLIM12 also for winter precipitation. These results, indicating clear benefits of convection-permitting models, are encouraging motivating further exploration of added value in this region, and provide a valuable basis for impact studies. © 2020, The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

Assimilation of Sentinel 1 and SMAP – based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins

Author(s):
Azimi, Shima; Dariane, Alireza B.; Modanesi, Sara; Bauer-Marschallinger, Bernhard; Bindlish, Rajat; Wagner, Wolfgang; Massari, Christian
Publication title: Journal of Hydrology
2020
 | Volume: 581
2020
DOI: 10.1016/j.jhydrol.2019.124367
Abstract:
In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events in response to the rainfall input… In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events in response to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small ( more
Application Climate Data Records H-SAF Land

Automatic quality control of the Meteosat First Generation measurements

Author(s):
Liefhebber, Freek; Lammens, Sarah; Brussee, Paul W. G.; Bos, André; John, Viju O.; Rüthrich, Frank; Onderwaater, Jacobus; Grant, Michael G.; Schulz, Jörg
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 3
2020
DOI: 10.5194/amt-13-1167-2020
Abstract:
Abstract. Now that the Earth has been monitored by satellites for more than 40 years, Earth observation images can be used to study how the Earth syst… Abstract. Now that the Earth has been monitored by satellites for more than 40 years, Earth observation images can be used to study how the Earth system behaves over extended periods. Such long-term studies require the combination of data from multiple instruments, with the earliest datasets being of particular importance in establishing a baseline for trend analysis. As the quality of these earlier datasets is often lower, careful quality control is essential, but the sheer size of these image sets makes an inspection by hand impracticable. Therefore, one needs to resort to automatic methods to inspect these Earth observation images for anomalies. In this paper, we describe the design of a system that performs an automatic anomaly analysis on Earth observation images, in particular the Meteosat First Generation measurements. The design of this system is based on a preliminary analysis of the typical anomalies that can be found in the dataset. This preliminary analysis was conducted by hand on a representative subset and resulted in a finite list of anomalies that needed to be detected in the whole dataset. The automated anomaly detection system employs a dedicated detection algorithm for each of these anomalies. The result is a system with a high probability of detection and low false alarm rate. Furthermore, most of these algorithms are able to pinpoint the anomalies to the specific pixels affected in the image, allowing the maximum use of the data available. more
Climate Data Records Validation

Assessments of the Retrieval of Atmospheric Profiles from GNSS Radio Occultation Data in Moist Tropospheric Conditions Using Radiosonde Data

Author(s):
Li, Ying; Yuan, Yunbin; Wang, Xiaoming
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 17
2020
DOI: 10.3390/rs12172717
Abstract:
The Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieved temperature and specific humidity profiles can be widely used for weath… The Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieved temperature and specific humidity profiles can be widely used for weather and climate studies in troposphere. However, some aspects, such as the influences of background data on these retrieved moist profiles have not been discussed yet. This research evaluates RO retrieved temperature and specific humidity profiles from Wegener Center for Climate and Global Change (WEGC), Radio Occultation Meteorology Satellite Application Facility (ROM SAF) and University Corporation for Atmospheric Research (UCAR) Boulder RO processing centers by comparing with measurements from 10 selected Integrated Global Radiosonde Archive (IGRA) radiosonde stations in different latitudinal bands over 2007 to 2010. The background profiles used for producing their moist profiles are also compared with radiosonde. We found that RO retrieved temperature profiles from all centers agree well with radiosonde. Mean differences at polar, mid-latitudinal and tropical stations are varying within ±0.2 K, ±0.5 K and from −1 to 0.2 K, respectively, with standard deviations varying from 1 to 2 K for most pressure levels. The differences between RO retrieved and their background temperature profiles for WEGC are varying within ±0.5 K at altitudes above 300 hPa, and the differences for ROM SAF are within ±0.2 K, and that for UCAR are within 0.5 K at altitudes below 300 hPa. Both RO retrieved and background specific humidity above 600 hPa are found to have large positive differences (up to 40%) against most radiosonde measurements. Discrepancies of moist profiles among the three centers are overall minor at altitudes above 300 hPa for temperature and at altitudes above 700 hPa for specific humidity. Specific humidity standard deviations are largest at tropical stations in June July August months. It is expected that the outcome of this research can help readers to understand the characteristics of moist products among centers. more
Atmosphere Climate Data Records ROM-SAF Validation

Assessment of new satellite missions within the framework of numerical weather prediction

Author(s):
Newman, S.; Carminati, F.; Lawrence, H.; Bormann, N.; Salonen, K.; Bell, W.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 10
2020
DOI: 10.3390/rs12101580
Abstract:
Confidence in the use of Earth observations for monitoring essential climate variables (ECVs) relies on the validation of satellite calibration accura… Confidence in the use of Earth observations for monitoring essential climate variables (ECVs) relies on the validation of satellite calibration accuracy to within a well-defined uncertainty. The gap analysis for integrated atmospheric ECV climate monitoring (GAIA-CLIM) project investigated the calibration/validation of satellite data sets using non-satellite reference data. Here, we explore the role of numerical weather prediction (NWP) frameworks for the assessment of several meteorological satellite sensors: the advanced microwave scanning radiometer 2 (AMSR2), microwave humidity sounder-2 (MWHS-2), microwave radiation imager (MWRI), and global precipitation measurement (GPM) microwave imager (GMI). We find departures (observation-model differences) are sensitive to instrument calibration artefacts. Uncertainty in surface emission is identified as a key gap in our ability to validate microwave imagers quantitatively in NWP. The prospects for NWP-based validation of future instruments are considered, taking as examples the microwave sounder (MWS) and infrared atmospheric sounding interferometer-next generation (IASI-NG) on the next generation of European polar-orbiting satellites. Through comparisons with reference radiosondes, uncertainties in NWP fields can be estimated in terms of equivalent top-of-atmosphere brightness temperature. We find NWP-sonde differences are consistent with a total combined uncertainty of 0.15 K for selected temperature sounding channels, while uncertainties for humidity sounding channels typically exceed 1 K. © 2020 by the authors. more
Atmosphere Method NWP-SAF Software for CDR development Validation

Artificial Neural Networks to Retrieve Land and Sea Skin Temperature from IASI

Author(s):
Safieddine, Sarah; Parracho, Ana Claudia; George, Maya; Aires, Filipe; Pellet, Victor; Clarisse, Lieven; Whitburn, Simon; Lezeaux, Olivier; Thépaut, Jean-Noël; Hersbach, Hans; Radnoti, Gabor; Goettsche, Frank; Martin, Maria; Doutriaux-Boucher, Marie; Coppens, Dorothée; August, Thomas; Zhou, Daniel K.; Clerbaux, Cathy
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 17
2020
DOI: 10.3390/rs12172777
Abstract:
Surface skin temperature (Tskin) derived from infrared remote sensors mounted on board satellites provides a continuous observation of Earth’s surface… Surface skin temperature (Tskin) derived from infrared remote sensors mounted on board satellites provides a continuous observation of Earth’s surface and allows the monitoring of global temperature change relevant to climate trends. In this study, we present a fast retrieval method for retrieving Tskin based on an artificial neural network (ANN) from a set of spectral channels selected from the Infrared Atmospheric Sounding Interferometer (IASI) using the information theory/entropy reduction technique. Our IASI Tskin product (i.e., TANN) is evaluated against Tskin from EUMETSAT Level 2 product, ECMWF Reanalysis (ERA5), SEVIRI observations, and ground in situ measurements. Good correlations between IASI TANN and the Tskin from other datasets are shown by their statistic data, such as a mean bias and standard deviation (i.e., [bias, STDE]) of [0.55, 1.86 °C], [0.19, 2.10 °C], [−1.5, 3.56 °C], from EUMETSAT IASI L-2 product, ERA5, and SEVIRI. When compared to ground station data, we found that all datasets did not achieve the needed accuracy at several months of the year, and better results were achieved at nighttime. Therefore, comparison with ground-based measurements should be done with care to achieve the ±2 °C accuracy needed, by choosing, for example, a validation site near the station location. On average, this accuracy is achieved, in particular at night, leading to the ability to construct a robust Tskin dataset suitable for Tskin long-term spatio-temporal variability and trend analysis. more
Application Climate Data Records EUM-Secr

Arctic Sea Ice in CMIP6

Author(s):
Notz, Dirk
Publication title: Geophysical Research Letters
2020
 | Volume: 47 | Issue: 10
2020
DOI: 10.1029/2019GL086749
Abstract:
We examine CMIP6 simulations of Arctic sea-ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea-ice area, capturing… We examine CMIP6 simulations of Arctic sea-ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea-ice area, capturing the observational estimate within the multimodel ensemble spread. The CMIP6 multimodel ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea-ice area to a given amount of anthropogenic CO2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea-ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea-ice free (sea-ice area &lt;1 × 106 km2) in September for the first time before the Year 2050 in each of the four emission scenarios SSP1-1.9, SSP1-2.6, SSP2-4.5, and SSP5-8.5 examined here. © 2020. The Authors. more
Application Climate Data Records Cryosphere OSI-SAF

Antarctic Sea Ice Area in CMIP6

Author(s):
Roach, L.A.; Dörr, J.; Holmes, C.R.; Massonnet, F.; Blockley, E.W.; Notz, D.; Rackow, T.; Raphael, M.N.; O'Farrell, S.P.; Bailey, D.A.; Bitz, C.M.
Publication title: Geophysical Research Letters
2020
 | Volume: 47 | Issue: 9
2020
DOI: 10.1029/2019GL086729
Abstract:
Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high-le… Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high-level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger-than-observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios. ©2020. American Geophysical Union. All Rights Reserved. more
Application Climate Data Records Cryosphere OSI-SAF

Analyzing the arctic feedback mechanism between sea ice and low-level clouds using 34 years of satellite observations

Author(s):
Philipp, D.; Stengel, M.; Ahrens, B.
Publication title: Journal of Climate
2020
 | Volume: 33 | Issue: 17
2020
DOI: 10.1175/JCLI-D-19-0895.1
Abstract:
Satellite-based cloud, radiation flux, and sea ice records covering 34 years are used 1) to investigate autumn cloud cover trends over the Arctic, 2) … Satellite-based cloud, radiation flux, and sea ice records covering 34 years are used 1) to investigate autumn cloud cover trends over the Arctic, 2) to assess its relation with declining sea ice using Granger causality (GC) analysis, and 3) to discuss the contribution of the cloud–sea ice (CSI) feedback to Arctic amplification. This paper provides strong evidence for a positive CSI feedback with the capability to contribute to autumnal Arctic amplification. Positive low-level cloud fractional cover (CFClow) trends over the Arctic ice pack are found in October and November (ON) with magnitudes of up to about 19.6% per decade locally. Statistically significant anticorrelations between sea ice concentration (SIC) and CFClow are observed in ON over melting zones, suggesting an association. The GC analysis indicated a causal two-way interaction between SIC and CFClow. Interpreting the resulting F statistic and its spatial distribution as a relation strength proxy, the influence of SIC on CFClow is likely stronger than the reverse. ERA-Interim reanalysis data suggest that ON CFClow is impacted by sea ice melt through surface–atmosphere coupling via turbulent heat and moisture fluxes. Due to weak solar insolation in ON, net cloud radiative forcing (CRF) exerts a warming effect on the Arctic surface. Increasing CFClow induces a large-scale surface warming trend reaching magnitudes of up to about 18.3 W m22 per decade locally. Sensitivities of total CRF to CFClow ranges between 10.22 and 10.66 W m22 per percent CFClow. Increasing surface warming can cause a melt season lengthening and hinders formation of perennial ice. Ó 2020 American Meteorological Society. more
Application Atmosphere CM-SAF Climate Data Records Cryosphere Validation

Analysis of the Thermodynamic Phase Transition of Tracked Convective Clouds Based on Geostationary Satellite Observations

Author(s):
Coopman, Q.; Hoose, C.; Stengel, M.
Publication title: Journal of Geophysical Research: Atmospheres
2020
 | Volume: 125 | Issue: 11
2020
DOI: 10.1029/2019JD032146
Abstract:
Clouds are liquid at temperature greater than 0°C and ice at temperature below −38°C. Between these two thresholds, the temperature of the cloud therm… Clouds are liquid at temperature greater than 0°C and ice at temperature below −38°C. Between these two thresholds, the temperature of the cloud thermodynamic phase transition from liquid to ice is difficult to predict and the theory and numerical models do not agree: Microphysical, dynamical, and meteorological parameters influence the glaciation temperature. We temporally track optical and microphysical properties of 796 clouds over Europe from 2004 to 2015 with the space-based instrument Spinning Enhanced Visible and Infrared Imager on board the geostationary METEOSAT second generation satellites. We define the glaciation temperature as the mean between the cloud top temperature of those consecutive images for which a thermodynamic phase change in at least one pixel is observed for a given cloud object. We find that, on average, isolated convective clouds over Europe freeze at −21.6°C. Furthermore, we analyze the temporal evolution of a set of cloud properties and we retrieve glaciation temperatures binned by meteorological and microphysical regimes: For example, the glaciation temperature increases up to 11°C when cloud droplets are large, in line with previous studies. Moreover, the correlations between the parameters characterizing the glaciation temperature are compared and analyzed and a statistical study based on principal component analysis shows that after the cloud top height, the cloud droplet size is the most important parameter to determine the glaciation temperature. ©2020. American Geophysical Union. All Rights Reserved. more
Application Atmosphere CM-SAF Climate Data Records

An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2)

Author(s):
Liu, Song; Valks, Pieter; Pinardi, Gaia; Xu, Jian; Argyrouli, Athina; Lutz, Ronny; Tilstra, L. Gijsbert; Huijnen, Vincent; Hendrick, François; Van Roozendael, Michel
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 2
2020
DOI: 10.5194/amt-13-755-2020
Abstract:
An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mas… An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parameterisation over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS (CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a clouds-as-layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current clouds-as-reflecting-boundaries (CRB) model, which assumes that the clouds are Lambertian reflectors. On average, improvements in the AMF calculation affect the tropospheric NO2 columns by ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and the aerosol-induced cloud parameters (implicit aerosol correction). Compared with the implicit aerosol correction utilising the CRB cloud parameters, the use of the CAL approach reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based multi-axis differential optical absorption spectroscopy (MAXDOAS) measurements at different BIRA-IASB stations. At the suburban Xianghe station, the improved tropospheric NO2 dataset shows better agreement with coincident ground-based measurements with a correlation coefficient of 0.94. more
AC-SAF Atmosphere Climate Data Records Validation

A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness

Author(s):
Eliasson, S.; Karlsson, K.-G.; Willén, U.
Publication title: Geoscientific Model Development
2020
 | Volume: 13 | Issue: 1
2020
DOI: 10.5194/gmd-13-297-2020
Abstract:
This paper describes a new satellite simulator for the CLARA-A2 climate data record (CDR). This simulator takes into account the variable skill in clo… This paper describes a new satellite simulator for the CLARA-A2 climate data record (CDR). This simulator takes into account the variable skill in cloud detection in the CLARA-A2 CDR by using a different approach to other similar satellite simulators to emulate the ability to detect clouds. In particular, the paper describes three methods to filter out clouds from climate models undetectable by observations. The first method is comparable to the current simulators in the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP), since it relies on a single visible cloud optical depth at 550 nm (τc) threshold applied globally to delineate cloudy and cloud-free conditions. Methods two and three apply long/lat-gridded values separated by daytime and nighttime conditions. Method two uses gridded varying τc as opposed to method one, which uses just a τc threshold, and method three uses a cloud probability of detection (POD) depending on the model τc. The gridded POD values are from the CLARA-A2 validation study by Karlsson and Håkansson (2018). Methods two and three replicate the relative ease or difficulty for cloud retrievals depending on the region and illumination. They increase the cloud sensitivity where the cloud retrievals are relatively straightforward, such as over midlatitude oceans, and they decrease the sensitivity where cloud retrievals are notoriously tricky, such as where thick clouds may be inseparable from cold snow-covered surfaces, as well as in areas with an abundance of broken and small-scale cumulus clouds such as the atmospheric subsidence regions over the ocean. The simulator, together with the International Satellite Cloud Climatology Project (ISCCP) simulator of the COSP, is used to assess Arctic clouds in the EC-Earth climate model compared to the CLARA-A2 and ISCCP H-Series (ISCCPH) CDRs. Compared to CLARA-A2, EC-Earth generally underestimates cloudiness in the Arctic. However, compared to ISCCP and its simulator, the opposite conclusion is reached. Based on EC-Earth, this paper shows that the simulated cloud mask of CLARA-A2, using method three, is more representative of the CDR than method one used for the ISCCP simulator. The simulator substantially improves the simulation of the CLARA-A2-detected clouds, especially in the polar regions, by accounting for the variable cloud detection skill over the year. The approach to cloud simulation based on the POD of clouds depending on their τc, location, and illumination is the preferred one as it reduces cloudiness over a range of cloud optical depths. Climate model comparisons with satellite-derived information can be significantly improved by this approach, mainly by reducing the risk of misinterpreting problems with satellite retrievals as cloudiness features. Since previous studies found that the CLARA-A2 CDR performs well in the Arctic during the summer months, and that method three is more representative than method one, the conclusion is that EC-Earth likely underestimates clouds in the Arctic summer. © Author(s) 2020. more
Atmosphere CM-SAF Climate Data Records Method

A Sea Surface Temperature data record (2004–2012) from Meteosat Second Generation satellites

Author(s):
Saux Picart, Stéphane; Marsouin, Anne; Legendre, Gérard; Roquet, Hervé; Péré, Sonia; Nano-Ascione, Nolwenn; Gianelli, Thibauld
Publication title: Remote Sensing of Environment
2020
 | Volume: 240
2020
DOI: 10.1016/j.rse.2020.111687
Abstract:
The Ocean and Sea-Ice Satellite Application Facility (OSI-SAF) of the EUropean Organisation for the Exploitation of METeorological Satellites (EUMETSA… The Ocean and Sea-Ice Satellite Application Facility (OSI-SAF) of the EUropean Organisation for the Exploitation of METeorological Satellites (EUMETSAT) has performed a reprocessing of Sea Surface Temperature (SST) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) archive (2004–2012). The retrieval method consists of a non-linear split-window algorithm and an algorithm correction relying on simulations of infrared brightness temperatures performed using atmospheric profiles of water vapour and temperature from a Numerical Weather Prediction model, and a radiative transfer model. The cloud mask used is the Climate SAF reprocessing of the MSG/SEVIRI archive which is consistent over the period considered. Atmospheric Saharan dust has a strong impact on the retrieved SST in the Atlantic and Mediterranean regions, they are taken into consideration through the computation of the Saharan Dust Index (SDI) which is then used to determine an empirical correction applied to SST. The reprocessing has benefited from the experience of the OSI SAF team in operational near real time processing of MSG/SEVIRI data, and the methods have been improved to provide a higher quality SST. The MSG/SEVIRI SST reprocessing dataset consists of hourly level 3 composites of sub-skin temperature projected onto a regular 0.05° grid over the region delimited by 60N,60S and 60W,60E. It has been thoroughly validated against drifting buoys and moored buoys measurements. Results of this validation have shown that the reprocessed data record is of significantly better quality than the OSI SAF operational processing (for instance the day-time robust standard deviation is 0.45 K for the operational processing and 0.35 K for the reprocessed dataset). The data record has been used to characterize the diurnal variability of SST over large temporal and spatial scales. more
Climate Data Records Method OSI-SAF Ocean Validation

A Process-Based Validation of GPM IMERG and Its Sources Using a Mesoscale Rain Gauge Network in the West African Forest Zone

Author(s):
Maranan, Marlon; Fink, Andreas H.; Knippertz, Peter; Amekudzi, Leonard K.; Atiah, Winifred A.; Stengel, Martin
Publication title: Journal of Hydrometeorology
2020
 | Volume: 21 | Issue: 4
2020
DOI: 10.1175/JHM-D-19-0257.1
Abstract:
Abstract Using a two-year dataset (2016–17) from 17 one-minute rain gauges located in the moist forest region of Ghana, the performance of… Abstract Using a two-year dataset (2016–17) from 17 one-minute rain gauges located in the moist forest region of Ghana, the performance of Integrated Multisatellite Retrievals for GPM, version 6b (IMERG), is evaluated based on a subdaily time scale, down to the level of the underlying passive microwave (PMW) and infrared (IR) sources. Additionally, the spaceborne cloud product Cloud Property Dataset Using SEVIRI, edition 2 (CLAAS-2), available every 15 min, is used to link IMERG rainfall to cloud-top properties. Several important issues are identified: 1) IMERG’s proneness to low-intensity false alarms, accounting for more than a fifth of total rainfall; 2) IMERG’s overestimation of the rainfall amount from frequently occurring weak convective events, while that of relatively rare but strong mesoscale convective systems is underestimated, resulting in an error compensation; and 3) a decrease of skill during the little dry season in July and August, known to feature enhanced low-level cloudiness and warm rain. These findings are related to 1) a general oversensitivity for clouds with low ice and liquid water path and a particular oversensitivity for low cloud optical thickness, a problem which is slightly reduced for direct PMW overpasses; 2) a pronounced negative bias for high rain intensities, strongest when IR data are included; and 3) a large fraction of missed events linked with rainfall out of warm clouds, which are inherently misinterpreted by IMERG and its sources. This paper emphasizes the potential of validating spaceborne rainfall products with high-resolution rain gauges on a subdaily time scale, particularly for the understudied West African region. more
Application Atmosphere CM-SAF Climate Data Records

A new satellite-based retrieval of low-cloud liquid-water path using machine learning and meteosat seviri data

Author(s):
Kim, M.; Cermak, J.; Andersen, H.; Fuchs, J.; Stirnberg, R.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 21
2020
DOI: 10.3390/rs12213475
Abstract:
Clouds are one of the major uncertainties of the climate system. The study of cloud processes requires information on cloud physical properties, in pa… Clouds are one of the major uncertainties of the climate system. The study of cloud processes requires information on cloud physical properties, in particular liquid water path (LWP). This parameter is commonly retrieved from satellite data using look-up table approaches. However, existing LWP retrievals come with uncertainties related to assumptions inherent in physical retrievals. Here, we present a new retrieval technique for cloud LWP based on a statistical machine learning model. The approach utilizes spectral information from geostationary satellite channels of Meteosat Spinning-Enhanced Visible and Infrared Imager (SEVIRI), as well as satellite viewing geometry. As ground truth, data from CloudNet stations were used to train the model. We found that LWP predicted by the machine-learning model agrees substantially better with CloudNet observations than a current physics-based product, the Climate Monitoring Satellite Application Facility (CM SAF) CLoud property dAtAset using SEVIRI, edition 2 (CLAAS-2), highlighting the potential of such approaches for future retrieval developments. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. more
Atmosphere CM-SAF Climate Data Records Validation

A Climatological Overview of Arctic Clouds

Author(s):
Devasthale, Abhay
2020
2020
DOI:
Abstract:
The Arctic climate system is complex and clouds are one of its least understood components. Since cloud processes occur from micrometer to synoptic sc… The Arctic climate system is complex and clouds are one of its least understood components. Since cloud processes occur from micrometer to synoptic scales, their couplings with the other components of the Arctic climate system and their overall role in modulating the energy budget at different spatio-temporal scales is challenging to quantify. The in-situ measurements, as limited in space and time as they are, still reveal the complex nature of cloud microphysical and thermodynamical processes in the Arctic. However, the synoptic scale variability of cloud systems can only be obtained from the satellite observations. A considerable progress has been made in the last decade in understanding cloud processes in the Arctic due to the availability of valuable data from the multiple campaigns in the Central Arctic and due to the advances in the satellite remote sensing. This chapter provides an overview of this progress. First an overview of the lessons learned from the recent in-situ measurement campaigns in the Arctic is provided. In particular, the importance of supercooled liquid water clouds, their role in the radiation budget and their interaction with the vertical thermodynamical structure is discussed. In the second part of the chapter, a climatological overview of cloud properties using the state-of-the-art satellite based cloud climate datasets is provided. The agreements and disagreements in these datasets are highlighted. The third and the fourth parts of the chapter highlight two most important processes that are currently being researched, namely cloud response to the rapidly changing sea-ice extent and the role of moisture transport in to the Arctic in governing cloud variability. Both of these processes have implications for the cloud feedback in the Arctic. more
Application Atmosphere CM-SAF Climate Data Records

Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records

Author(s):
Lavergne, Thomas; Sørensen, Atle Macdonald; Kern, Stefan; Tonboe, Rasmus; Notz, Dirk; Aaboe, Signe; Bell, Louisa; Dybkjær, Gorm; Eastwood, Steinar; Gabarro, Carolina; Heygster, Georg; Killie, Mari Anne; Brandt Kreiner, Matilde; Lavelle, John; Saldo, Roberto; Sandven, Stein; Pedersen, Leif Toudal
Publication title: The Cryosphere
2019
 | Volume: 13 | Issue: 1
2019
DOI: 10.5194/tc-13-49-2019
Abstract:
Abstract. We introduce the OSI-450, the SICCI-25km and the SICCI-50km climate data records of gridded global sea-ice concentration. These three record… Abstract. We introduce the OSI-450, the SICCI-25km and the SICCI-50km climate data records of gridded global sea-ice concentration. These three records are derived from passive microwave satellite data and offer three distinct advantages compared to existing records: first, all three records provide quantitative information on uncertainty and possibly applied filtering at every grid point and every time step. Second, they are based on dynamic tie points, which capture the time evolution of surface characteristics of the ice cover and accommodate potential calibration differences between satellite missions. Third, they are produced in the context of sustained services offering committed extension, documentation, traceability, and user support. The three records differ in the underlying satellite data (SMMR &amp; SSM/I &amp; SSMIS or AMSR-E &amp; AMSR2), in the imaging frequency channels (37 GHz and either 6 or 19 GHz), in their horizontal resolution (25 or 50 km), and in the time period they cover. We introduce the underlying algorithms and provide an evaluation. We find that all three records compare well with independent estimates of sea-ice concentration both in regions with very high sea-ice concentration and in regions with very low sea-ice concentration. We hence trust that these records will prove helpful for a better understanding of the evolution of the Earth's sea-ice cover. more
Application Climate Data Records Cryosphere Method OSI-SAF Validation

Validation of HOAPS Rain Retrievals against OceanRAIN In-Situ Measurements over the Atlantic Ocean

Author(s):
Bumke, Karl; Pilch Kedzierski, Robin; Schröder, Marc; Klepp, Christian; Fennig, Karsten
Publication title: Atmosphere
2019
 | Volume: 10 | Issue: 1
2019
DOI: 10.3390/atmos10010015
Abstract:
The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) precipitation estimates have been validated against i… The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) precipitation estimates have been validated against in-situ precipitation measurements from optical disdrometers, available from OceanRAIN (Ocean Rainfall And Ice-phase precipitation measurement Network) over the open-ocean by applying a statistical analysis for binary estimates. In addition to using directly collocated pairs of data, collocated data were merged within a certain temporal and spatial threshold into single events, according to the observation times. Although binary statistics do not show perfect agreement, simulations of areal estimates from the observations themselves indicate a reasonable performance of HOAPS to detect rain. However, there are deficits at low and mid-latitudes. Weaknesses also occur when analyzing the mean precipitation rates; HOAPS underperforms in the area of the intertropical convergence zone, where OceanRAIN observations show the highest mean precipitation rates. Histograms indicate that this is due to an underestimation of the frequency of moderate to high precipitation rates by HOAPS, which cannot be explained by areal averaging. more
Application Atmosphere CM-SAF Climate Data Records Validation

Utility of GNSS Radio Occultation technique for tropopause height investigation over Egypt

Author(s):
Zhran, Mohamed; Mousa, Ashraf; Rabah, Mostafa; Zeidan, Zaki
Publication title: NRIAG Journal of Astronomy and Geophysics
2019
 | Volume: 8 | Issue: 1
2019
DOI: 10.1080/20909977.2019.1617559
Abstract:
Global Navigation Satellite System (GNSS) Radio Occultation (RO) is an active limb sounding technique, where GNSS satellites transmitted signals passi… Global Navigation Satellite System (GNSS) Radio Occultation (RO) is an active limb sounding technique, where GNSS satellites transmitted signals passing through the atmosphere of the Earth and received by a GNSS receiver on low earth orbiter (LEO) satellite. RO provides accurate atmospheric refractivity profile. RO technique has been widely used to study the atmosphere of planets. This paper investigates the use of GNSS RO for tropopause height (TPH) estimation as one of the key climate parameters over Egypt. TPH is also very important in determining the wet delay in GNSS analysis. Two years (2016 and 2017) of MetOP A and B satellites data are used. ROPP software package is used in the analysis. For validation of the results, RO-derived TPH is compared with European Centre for Medium-Range Weather Forecast (ECMWF) model as well as radiosonde (RS). Good agreement and high correlation are found between TPH from RO and ECMWF and RS on the other hand. TPH varies between 14 and 16 km over Egypt. It decreases with latitude and shows no clear trend with longitude. Tropopause temperature is found to increase with latitude. more
Application Atmosphere Climate Data Records ROM-SAF

Towards a Traceable Climate Service: Assessment of Quality and Usability of Essential Climate Variables

Author(s):
Zeng, Yijian; Su, Zhongbo; Barmpadimos, Iakovos; Perrels, Adriaan; Poli, Paul; Boersma, K. Folkert; Frey, Anna; Ma, Xiaogang; de Bruin, Karianne; Goosen, Hasse; John, Viju O.; Roebeling, Rob; Schulz, Jörg; Timmermans, Wim
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 10
2019
DOI: 10.3390/rs11101186
Abstract:
Climate services are becoming the backbone to translate climate knowledge, data & information into climate-informed decision-making at all levels, fro… Climate services are becoming the backbone to translate climate knowledge, data & information into climate-informed decision-making at all levels, from public administrations to business operators. It is essential to assess the technical and scientific quality of the provided climate data and information products, including their value to users, to establish the relation of trust between providers of climate data and information and various downstream users. The climate data and information products (i.e., from satellite, in-situ and reanalysis) shall be fully traceable, adequately documented and uncertainty quantified and can provide sufficient guidance for users to address their specific needs and feedbacks. This paper discusses details on how to apply the quality assurance framework to deliver timely assessments of the quality and usability of Essential Climate Variable (ECV) products. It identifies an overarching structure for the quality assessment of single product ECVs (i.e., consists of only one single variable), multi-product ECVs (i.e., more than one single parameter), thematic products (i.e., water, energy and carbon cycles), as well as the usability assessment. To support a traceable climate service, other than rigorously evaluating the technical and scientific quality of ECV products, which represent the upstream of climate services, how the uncertainty propagates into the resulting benefit (utility) for the users of the climate service needs to be detailed. more
Application EUM-Secr International cooperation Validation

State of the Climate in 2018

Author(s):
Blunden, Jessica; Arndt, Derek S.
Publication title: Bulletin of the American Meteorological Society
2019
 | Volume: 100 | Issue: 9
2019
DOI: 10.1175/2019BAMSStateoftheClimate.1
Abstract:
Abstract Editor’s note: For easy download the posted pdf of the State of the Climate for 2019 is a low-resolution file. A high-resolution … Abstract Editor’s note: For easy download the posted pdf of the State of the Climate for 2019 is a low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations

Author(s):
Brocca, Luca; Filippucci, Paolo; Hahn, Sebastian; Ciabatta, Luca; Massari, Christian; Camici, Stefania; Schüller, Lothar; Bojkov, Bojan; Wagner, Wolfgang
Publication title: Earth System Science Data
2019
 | Volume: 11 | Issue: 4
2019
DOI: 10.5194/essd-11-1583-2019
Abstract:
Abstract. Long-term gridded precipitation products are crucial for several applications in hydrology, agriculture and climate sciences. Currently avai… Abstract. Long-term gridded precipitation products are crucial for several applications in hydrology, agriculture and climate sciences. Currently available precipitation products suffer from space and time inconsistency due to the non-uniform density of ground networks and the difficulties in merging multiple satellite sensors. The recent “bottom-up” approach that exploits satellite soil moisture observations for estimating rainfall through the SM2RAIN (Soil Moisture to Rain) algorithm is suited to build a consistent rainfall data record as a single polar orbiting satellite sensor is used. Here we exploit the Advanced SCATterometer (ASCAT) on board three Meteorological Operational (MetOp) satellites, launched in 2006, 2012, and 2018, as part of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System programme. The continuity of the scatterometer sensor is ensured until the mid-2040s through the MetOp Second Generation Programme. Therefore, by applying the SM2RAIN algorithm to ASCAT soil moisture observations, a long-term rainfall data record will be obtained, starting in 2007 and lasting until the mid-2040s. The paper describes the recent improvements in data pre-processing, SM2RAIN algorithm formulation, and data post-processing for obtaining the SM2RAIN–ASCAT quasi-global (only over land) daily rainfall data record at a 12.5 km spatial sampling from 2007 to 2018. The quality of the SM2RAIN–ASCAT data record is assessed on a regional scale through comparison with high-quality ground networks in Europe, the United States, India, and Australia. Moreover, an assessment on a global scale is provided by using the triple-collocation (TC) technique allowing us also to compare these data with the latest, fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), the Early Run version of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG), and the gauge-based Global Precipitation Climatology Centre (GPCC) products. Results show that the SM2RAIN–ASCAT rainfall data record performs relatively well at both a regional and global scale, mainly in terms of root mean square error (RMSE) when compared to other products. Specifically, the SM2RAIN–ASCAT data record provides performance better than IMERG and GPCC in data-scarce regions of the world, such as Africa and South America. In these areas, we expect larger benefits in using SM2RAIN–ASCAT for hydrological and agricultural applications. The limitations of the SM2RAIN–ASCAT data record consist of the underestimation of peak rainfall events and the presence of spurious rainfall events due to high-frequency soil moisture fluctuations that might be corrected in the future with more advanced bias correction techniques. The SM2RAIN–ASCAT data record is freely available at https://doi.org/10.5281/zenodo.3405563 (Brocca et al., 2019) (recently extended to the end of August 2019). more
Application Climate Data Records H-SAF Land

Satellite passive microwave sea-ice concentration data set intercomparison: Closed ice and ship-based observations

Author(s):
Kern, S.; Lavergne, T.; Notz, D.; Toudal Pedersen, L.; Tage Tonboe, R.; Saldo, R.; Macdonald Sørensen, A.
Publication title: Cryosphere
2019
 | Volume: 13 | Issue: 12
2019
DOI: 10.5194/tc-13-3261-2019
Abstract:
We report on results of a systematic intercomparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution for bot… We report on results of a systematic intercomparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution for both the Arctic and the Antarctic. The products are compared with each other with respect to differences in SIC, sea-ice area (SIA), and sea-ice extent (SIE), and they are compared against a global wintertime near-100% reference SIC data set for closed pack ice conditions and against global year-round ship-based visual observations of the sea-ice cover. We can group the products based on the concept of their SIC retrieval algorithms. Group I consists of data sets using the selfoptimizing EUMETSAT OSI SAF and ESA CCI algorithms. Group II includes data using the Comiso bootstrap algorithm and the NOAA NSIDC sea-ice concentration climate data record (CDR). The standard NASA Team and the ARTIST Sea Ice (ASI) algorithms are put into group III, and NASA Team 2 is the only element of group IV. The three CDRs of group I (SICCI-25km, SICCI-50km, and OSI-450) are biased low compared to a 100% reference SIC data set with biases of-0:4% to-1:0% (Arctic) and-0:3% to-1:1% (Antarctic). Products of group II appear to be mostly biased high in the Arctic by between C1.0% and C3.5 %, while their biases in the Antarctic range from-0:2% to C0.9 %. Group III product biases are different for the Arctic, C0.9% (NASA Team) and-3:7% (ASI), but similar for the Antarctic,-5:4% and-5:6 %, respectively. The standard deviation is smaller in the Arctic for the quoted group I products (1.9%to 2.9 %) and Antarctic (2.5%to 3.1 %) than for group II and III products: 3.6% to 5.0% for the Arctic and 4.0% to 6.5% for the Antarctic. We refer to the paper to understand why we could not give values for group IV here. We discuss the impact of truncating the SIC distribution, as naturally retrieved by the algorithms around the 100% sea-ice concentration end. We show that evaluation studies of such truncated SIC products can result in misleading statistics and favour data sets that systematically overestimate SIC.We describe a method to reconstruct the non-truncated distribution of SIC before the evaluation is performed. On the basis of this evaluation, we open a discussion about the overestimation of SIC in data products, with far-reaching consequences for surface heat flux estimations in winter.We also document inconsistencies in the behaviour of the weather filters used in products of group II, and we suggest advancing studies about the influence of these weather filters on SIA and SIE time series and their trends. © 2019 Royal Society of Chemistry. All rights reserved. more
Climate Data Records Cryosphere OSI-SAF Validation

Recalibration of over 35 Years of Infrared and Water Vapor Channel Radiances of the JMA Geostationary Satellites

Author(s):
Tabata, Tasuku; John, Viju O.; Roebeling, Rob A.; Hewison, Tim; Schulz, Jörg
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 10
2019
DOI: 10.3390/rs11101189
Abstract:
Infrared sounding measurements of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-resolution In… Infrared sounding measurements of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-resolution Infrared Radiation Sounder/2 (HIRS/2) instruments are used to recalibrate infrared (IR; \textasciitilde11 µm) channels and water vapor (WV; \textasciitilde6 µm) channels of the Visible and Infrared Spin Scan Radiometer (VISSR), Japanese Advanced Meteorological Imager (JAMI), and IMAGER instruments onboard the historical geostationary satellites of the Japan Meteorological Agency (JMA). The recalibration was performed using a common recalibration method developed by European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), which can be applied to the historical geostationary satellites to produce Fundamental Climate Data Records (FCDR). Pseudo geostationary imager radiances were computed from the infrared sounding measurements and regressed against the radiances from the geostationary satellites. Recalibration factors were computed from these pseudo imager radiance pairs. This paper presents and evaluates the result of recalibration of longtime-series of IR (1978–2016) and WV (1995–2016) measurements from JMA’s historical geostationary satellites. For the IR data of the earlier satellites (Geostationary Metrological Satellite (GMS) to GMS-4) significant seasonal variations in radiometric biases were observed. This suggests that the sensors on GMS to GMS-4 were strongly affected by seasonal variations in solar illumination. The amplitudes of these seasonal variations range from 3 K for the earlier satellites to \textless0.4 K for the recent satellites (GMS-5, Geostationary Operational Environmental Satellite-9 (GOES-9), Multi-functional Transport Satellite-1R (MTSAT-1R) and MTSAT-2). For the WV data of GOES-9, MTSAT-1R and MTSAT-2, no seasonal variations in radiometric biases were observed. However, for GMS-5, the amplitude of seasonal variation in bias was about 0.5 K. Overall, the magnitude of the biases for GMS-5, MTSAT-1R and MTSAT-2 were smaller than 0.3 K. Finally, our analysis confirms the existence of errors due to atmospheric absorption contamination in the operational Spectral Response Function (SRF) of the WV channel of GMS-5. The method used in this study is based on the principles developed within Global Space-based Inter-calibration System (GSICS). Moreover, presented results contribute to the Inter-calibration of imager observations from time-series of geostationary satellites (IOGEO) project under the umbrella of the World Meteorological Organization (WMO) initiative Sustained and Coordinated Processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM). more
Application Climate Data Records EUM-Secr Validation

On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders

Author(s):
John, Viju O.; Tabata, Tasuku; Rüthrich, Frank; Roebeling, Rob; Hewison, Tim; Stöckli, Reto; Schulz, Jörg
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 10
2019
DOI: 10.3390/rs11101171
Abstract:
This study presents a common recalibration method that has been applied to geostationary imagers’ infrared (IR) and water vapour (WV) channel measurem… This study presents a common recalibration method that has been applied to geostationary imagers’ infrared (IR) and water vapour (WV) channel measurements, referred to as the multi-sensor infrared channel calibration (MSICC) method. The method relies on data of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-Resolution Infrared Radiation Sounder (HIRS/2) on polar orbiting satellites. The geostationary imagers considered here are VISSR/JAMI/IMAGER on JMA’s GMS/MTSAT series and MVIRI/SEVIRI on EUMETSAT’s METEOSAT series. IASI hyperspectral measurements are used to determine spectral band adjustment factors (SBAF) that account for spectral differences between the geostationary and polar orbiting satellite measurements. A new approach to handle the spectral gaps of AIRS measurements using IASI spectra is developed and demonstrated. Our method of recalibration can be directly applied to the lowest level of geostationary measurements available, i.e., digital counts, to obtain recalibrated radiances. These radiances are compared against GSICS-corrected radiances and are validated against SEVIRI radiances, both during overlapping periods. Significant reduction in biases have been observed for both IR and WV channels, 4% and 10%, respectively compared to the operational radiances. more
Application Climate Data Records EUM-Secr Method

On the Accuracy of Vaisala RS41 versus RS92 Upper-Air Temperature Observations

Author(s):
Sun, Bomin; Reale, Tony; Schroeder, Steven; Pettey, Michael; Smith, Ryan
Publication title: Journal of Atmospheric and Oceanic Technology
2019
 | Volume: 36 | Issue: 4
2019
DOI: 10.1175/JTECH-D-18-0081.1
Abstract:
The accuracy of Vaisala RS92 versus RS41 global radiosonde soundings, emphasizing stratospheric temperature, is assessed from January 2015 to June 201… The accuracy of Vaisala RS92 versus RS41 global radiosonde soundings, emphasizing stratospheric temperature, is assessed from January 2015 to June 2017 using ~311 500 RS92 and ~65 800 RS41 profiles and three different reference data sources. First, numerical weather prediction (NWP) model outputs are used as a transfer medium to produce relative RS92 and RS41 comparisons by analyzing observation minus NWP model background (OB–BG) and observation minus analysis (OB–AN) differences using the NOAA Climate Forecast System Reanalysis (CFSR; both comparisons) and the operational European Centre for Medium-Range Weather Forecasts (ECMWF) model (OB–AN comparison only). Second, GPS radio occultation (GPSRO) dry temperature profiles are directly compared with radiosondes, using GPSRO data from the University Corporation for Atmospheric Research (UCAR) Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and EUMETSAT Radio Occultation Meteorology (ROM) Satellite Application Facility (SAF). Third, dual launches (RS92 and RS41 suspended from the same balloon) at five sites allow direct assessments. Comparisons of RS92 versus RS41 from all reference data sources are basically consistent. These two sondes agree well with global average temperature differences more
Application Atmosphere Climate Data Records ROM-SAF

NWCSAF High Resolution Winds (NWC/GEO-HRW) Stand-Alone Software for Calculation of Atmospheric Motion Vectors and Trajectories

Author(s):
García-Pereda, Javier; Fernández-Serdán, José; Alonso, Óscar; Sanz, Adrián; Guerra, Rocío; Ariza, Cristina; Santos, Inés; Fernández, Laura
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 17
2019
DOI: 10.3390/rs11172032
Abstract:
The High Resolution Winds (NWC/GEO-HRW) software is developed by the EUMETSAT Satellite Application Facility on Support to Nowcasting and Very Short R… The High Resolution Winds (NWC/GEO-HRW) software is developed by the EUMETSAT Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting (NWCSAF). It is part of a stand-alone software package for the calculation of meteorological products with geostationary satellite data (NWC/GEO). NWCSAF High Resolution Winds provides a detailed calculation of Atmospheric Motion Vectors (AMVs) and Trajectories, locally and in near real time, using as input geostationary satellite image data, NWP model data, and OSTIA sea surface temperature data. The whole NWC/GEO software package can be obtained after registration at the NWCSAF Helpdesk, www.nwcsaf.org, where users also find support and help for its use. NWC/GEO v2018.1 software version, available since autumn 2019, is able to process MSG, Himawari-8/9, GOES-N, and GOES-R satellite series images, so that AMVs and trajectories can be calculated all throughout the planet Earth with the same algorithm and quality. Considering other equivalent meteorological products, in the ‘2014 and 2018 AMV Intercomparison Studies’ NWCSAF High Resolution Winds compared very positively with six other AMV algorithms for both MSG and Himawari-8/9 satellites. Finally, the Coordination Group for Meteorological Satellites (CGMS) recognized in its ‘2012 Meeting Report’: (1) NWCSAF High Resolution Winds fulfills the requirements to be a portable stand-alone AMV calculation software due to its easy installation and usability. (2) It has been successfully adopted by some CGMS members and serves as an important tool for development. It is modular, well documented, and well suited as stand-alone AMV software. (3) Although alternatives exist as portable stand-alone AMV calculation software, they are not as advanced in terms of documentation and do not have an existing Helpdesk. more
Atmosphere Method NWC-SAF Software for CDR development

Modelling of Wine Production Using Land Surface Temperature and FAPAR—The Case of the Douro Wine Region

Author(s):
Magarreiro, Clarisse; Gouveia, Célia; Barroso, Carla; Trigo, Isabel
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 6
2019
DOI: 10.3390/rs11060604
Abstract:
The vegetative development of grapevines is orchestrated by very specific meteorological conditions. In the wine industry vineyards demand diligent mo… The vegetative development of grapevines is orchestrated by very specific meteorological conditions. In the wine industry vineyards demand diligent monitoring, since quality and productivity are the backbone of the economic potential. Regional climate indicators and meteorological information are essential to winemakers to assure proper vineyard management. Satellite data are very useful in this process since they imply low costs and are easily accessible. This work proposes a statistical modelling approach based on parameters obtained exclusively from satellite data to simulate annual wine production. The study has been developed for the Douro Demarcated Region (DDR) due to its relevance in the winemaking industry. It is the oldest demarcated and controlled winemaking region of the world and listed as one of UNESCO’s World Heritage regions. Monthly variables associated with Land Surface Temperatures (LST) and Fraction of Absorbed Photosynthetic Active Radiation (FAPAR), which is representative of vegetation canopy health, were analysed for a 15-year period (2004 to 2018), to assess their relation to wine production. Results showed that high wine production years are associated with higher than normal FAPAR values during approximately the entire growing season and higher than normal values of surface temperature from April to August. A robust linear model was obtained using the most significant predictors, that includes FAPAR in December and maximum and mean LST values in March and July, respectively. The model explains 90% of the total variance of wine production and presents a correlation coefficient of 0.90 (after cross validation). The retained predictors’ anomalies for the investigated vegetative year (October to July) from 2017/2018 satellite data indicate that the ensuing wine production for the DDR is likely to be below normal, i.e., to be lower than what is considered a high-production year. This work highlights that is possible to estimate wine production at regional scale based solely on low-resolution remotely sensed observations that are easily accessible, free and available for numerous grapevines regions worldwide, providing a useful and easy tool to estimate wine production and agricultural monitoring. more
Application Climate Data Records LSA-SAF Land

Copernicus Marine Service Ocean State Report, Issue 3

Author(s):
von Schuckmann, Karina; Le Traon, Pierre-Yves; Smith, Neville; Pascual, Ananda; Djavidnia, Samuel; Gattuso, Jean-Pierre; Grégoire, Marilaure; Nolan, Glenn; Aaboe, Signe; Aguiar, Eva; Álvarez Fanjul, Enrique; Alvera-Azcárate, Aida; Aouf, Lotfi; Barciela, Rosa; Behrens, Arno; Belmonte Rivas, Maria; Ben Ismail, Sana; Bentamy, Abderrahim; Borgini, Mireno; Brando, Vittorio E.; Bensoussan, Nathaniel; Blauw, Anouk; Bryère, Philippe; Buongiorno Nardelli, Bruno; Caballero, Ainhoa; Çağlar Yumruktepe, Veli; Cebrian, Emma; Chiggiato, Jacopo; Clementi, Emanuela; Corgnati, Lorenzo; de Alfonso, Marta; de Pascual Collar, Álvaro; Deshayes, Julie; Di Lorenzo, Emanuele; Dominici, Jean-Marie; Dupouy, Cécile; Drévillon, Marie; Echevin, Vincent; Eleveld, Marieke; Enserink, Lisette; García Sotillo, Marcos; Garnesson, Philippe; Garrabou, Joaquim; Garric, Gilles; Gasparin, Florent; Gayer, Gerhard; Gohin, Francis; Grandi, Alessandro; Griffa, Annalisa; Gourrion, Jérôme; Hendricks, Stefan; Heuzé, Céline; Holland, Elisabeth; Iovino, Doroteaciro; Juza, Mélanie; Kurt Kersting, Diego; Kipson, Silvija; Kizilkaya, Zafer; Korres, Gerasimos; Kõuts, Mariliis; Lagemaa, Priidik; Lavergne, Thomas; Lavigne, Heloise; Ledoux, Jean-Baptiste; Legeais, Jean-François; Lehodey, Patrick; Linares, Cristina; Liu, Ye; Mader, Julien; Maljutenko, Ilja; Mangin, Antoine; Manso-Narvarte, Ivan; Mantovani, Carlo; Markager, Stiig; Mason, Evan; Mignot, Alexandre; Menna, Milena; Monier, Maeva; Mourre, Baptiste; Müller, Malte; Nielsen, Jacob Woge; Notarstefano, Giulio; Ocaña, Oscar; Pascual, Ananda; Patti, Bernardo; Payne, Mark R.; Peirache, Marion; Pardo, Silvia; Pérez Gómez, Begoña; Pisano, Andrea; Perruche, Coralie; Peterson, K. Andrew; Pujol, Marie-Isabelle; Raudsepp, Urmas; Ravdas, Michalis; Raj, Roshin P.; Renshaw, Richard; Reyes, Emma; Ricker, Robert; Rubio, Anna; Sammartino, Michela; Santoleri, Rosalia; Sathyendranath, Shubha; Schroeder, Katrin; She, Jun; Sparnocchia, Stefania; Staneva, Joanna; Stoffelen, Ad; Szekely, Tanguy; Tilstone, Gavin H.; Tinker, Jonathan; Tintoré, Joaquín; Tranchant, Benoît; Uiboupin, Rivo; Van der Zande, Dimitry; von Schuckmann, Karina; Wood, Richard; Woge Nielsen, Jacob; Zabala, Mikel; Zacharioudaki, Anna; Zuberer, Frédéric; Zuo, Hao
Publication title: Journal of Operational Oceanography
2019
 | Volume: 12 | Issue: sup1
2019
DOI: 10.1080/1755876X.2019.1633075
Application Climate Data Records Cryosphere OSI-SAF

Cloud Detection with Historical Geostationary Satellite Sensors for Climate Applications

Author(s):
Stöckli, Reto; Bojanowski, Jędrzej S.; John, Viju O.; Duguay-Tetzlaff, Anke; Bourgeois, Quentin; Schulz, Jörg; Hollmann, Rainer
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 9
2019
DOI: 10.3390/rs11091052
Abstract:
Can we build stable Climate Data Records (CDRs) spanning several satellite generations? This study outlines how the ClOud Fractional Cover dataset fro… Can we build stable Climate Data Records (CDRs) spanning several satellite generations? This study outlines how the ClOud Fractional Cover dataset from METeosat First and Second Generation (COMET) of the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) was created for the 25-year period 1991–2015. Modern multi-spectral cloud detection algorithms cannot be used for historical Geostationary (GEO) sensors due to their limited spectral resolution. We document the innovation needed to create a retrieval algorithm from scratch to provide the required accuracy and stability over several decades. It builds on inter-calibrated radiances now available for historical GEO sensors. It uses spatio-temporal information and a robust clear-sky retrieval. The real strength of GEO observations—the diurnal cycle of reflectance and brightness temperature—is fully exploited instead of just accounting for single “imagery”. The commonly-used naive Bayesian classifier is extended with covariance information of cloud state and variability. The resulting cloud fractional cover CDR has a bias of 1% Mean Bias Error (MBE), a precision of 7% bias-corrected Root-Mean-Squared-Error (bcRMSE) for monthly means, and a decadal stability of 1%. Our experience can serve as motivation for CDR developers to explore novel concepts to exploit historical sensor data. more
Application Atmosphere CM-SAF Climate Data Records Method Validation

Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

Author(s):
García-Haro, Francisco Javier; Camacho, Fernando; Martínez, Beatriz; Campos-Taberner, Manuel; Fuster, Beatriz; Sánchez-Zapero, Jorge; Gilabert, María Amparo
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 18
2019
DOI: 10.3390/rs11182103
Abstract:
The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and ener… The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation. more
Application Climate Data Records LSA-SAF Land Validation

Climate Data Records from Meteosat First Generation Part III: Recalibration and Uncertainty Tracing of the Visible Channel on Meteosat-2–7 Using Reconstructed, Spectrally Changing Response Functions

Author(s):
Rüthrich, Frank; John, Viju O.; Roebeling, Rob A.; Quast, Ralf; Govaerts, Yves; Woolliams, Emma R.; Schulz, Jörg
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 10
2019
DOI: 10.3390/rs11101165
Abstract:
This paper presents a new Fundamental Climate Data Record (FCDR) for the visible (VIS) channel of the Meteosat Visible and Infrared Imager (MVIRI), wi… This paper presents a new Fundamental Climate Data Record (FCDR) for the visible (VIS) channel of the Meteosat Visible and Infrared Imager (MVIRI), with pixel-level metrologically traceable uncertainties and error covariance estimates. MVIRI has flown onboard Meteosat First Generation (MFG) satellites between 1982 and 2017. It has served the weather forecasting community with measurements of “visible”, “infra-red” and “water vapour” radiance in near real-time. The precision of the pre-launch sensor spectral response function (SRF) characterisation, particularly of the visible band of this sensor type, improved considerably with time, resulting in higher quality radiances towards the end of the MFG program. Despite these improvements, the correction of the degradation of this sensor has remained a challenging task and previous studies have found the SRF degradation to be faster in the blue than in the near-infrared part of the spectrum. With these limitations, the dataset cannot be immediately applied in climate science. In order to provide a data record that is suited for climate studies, the Horizon 2020 project “FIDelity and Uncertainty in Climate-data records from Earth Observation” (FIDUCEO) conducted (1) a thorough metrological uncertainty analysis for each instrument, and (2) a recalibration using enhanced input data such as reconstructed SRFs. In this paper, we present the metrological analysis, the recalibration results and the resulting consolidated FCDR. In the course of this study we were able to trace-back the remaining uncertainties in the calibrated MVIRI reflectances to underlying effects that have distinct physical root-causes and spatial/temporal correlation patterns. SEVIRI and SCIAMACHY reflectances have been used for a validation of the harmonised dataset. The resulting new FCDR is publicly available for climate studies and for the production of climate data records (CDRs) spanning about 35 years. more
Application Climate Data Records EUM-Secr Validation

Climate Data Records from Meteosat First Generation Part II: Retrieval of the In-Flight Visible Spectral Response

Author(s):
Quast, Ralf; Giering, Ralf; Govaerts, Yves; Rüthrich, Frank; Roebeling, Rob
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 5
2019
DOI: 10.3390/rs11050480
Abstract:
How can the in-flight spectral response functions of a series of decades-old broad band radiometers in Space be retrieved post-flight? This question i… How can the in-flight spectral response functions of a series of decades-old broad band radiometers in Space be retrieved post-flight? This question is the key to developing Climate Data Records from the Meteosat Visible and Infrared Imager on board the Meteosat First Generation (MFG) of geostationary satellites, which acquired Earth radiance images in the Visible (VIS) broad band from 1977 to 2017. This article presents a new metrologically sound method for retrieving the VIS spectral response from matchups of pseudo-invariant calibration site (PICS) pixels with datasets of simulated top-of-atmosphere spectral radiance used as reference. Calibration sites include bright desert, open ocean and deep convective cloud targets. The absolute instrument spectral response function is decomposed into generalised Bernstein basis polynomials and a degradation function that is based on plain physical considerations and able to represent typical chromatic ageing characteristics. Retrieval uncertainties are specified in terms of an error covariance matrix, which is projected from model parameter space into the spectral response function domain and range. The retrieval method considers target type-specific biases due to errors in, e.g., the selection of PICS target pixels and the spectral radiance simulation explicitly. It has been tested with artificial and well-comprehended observational data from the Spinning Enhanced Visible and Infrared Imager on-board Meteosat Second Generation and has retrieved meaningful results for all MFG satellites apart from Meteosat-1, which was not available for analysis. more
Application Climate Data Records EUM-Secr Method

Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT

Author(s):
Belmonte Rivas, Maria; Stoffelen, Ad
Publication title: Ocean Science
2019
 | Volume: 15 | Issue: 3
2019
DOI: 10.5194/os-15-831-2019
Abstract:
Abstract. This paper analyzes the differences between ERA-Interim and ERA5 surface winds fields relative to Advanced Scatterometer (ASCAT) ocean vecto… Abstract. This paper analyzes the differences between ERA-Interim and ERA5 surface winds fields relative to Advanced Scatterometer (ASCAT) ocean vector wind observations, after adjustment for the effects of atmospheric stability and density, using stress-equivalent winds (U10S) and air–sea relative motion using ocean current velocities. In terms of instantaneous root mean square (rms) wind speed agreement, ERA5 winds show a 20 % improvement relative to ERA-Interim and a performance similar to that of currently operational ECMWF forecasts. ERA5 also performs better than ERA-Interim in terms of mean and transient wind errors, wind divergence and wind stress curl biases. Yet, both ERA products show systematic errors in the partition of the wind kinetic energy into zonal and meridional, mean and transient components. ERA winds are characterized by excessive mean zonal winds (westerlies) with too-weak mean poleward flows in the midlatitudes and too-weak mean meridional winds (trades) in the tropics. ERA stress curl is too cyclonic in midlatitudes and high latitudes, with implications for Ekman upwelling estimates, and lacks detail in the representation of sea surface temperature (SST) gradient effects (along the equatorial cold tongues and Western Boundary Current (WBC) jets) and mesoscale convective airflows (along the Intertropical Convergence Zone and the warm flanks for the WBC jets). It is conjectured that large-scale mean wind biases in ERA are related to their lack of high-frequency (transient wind) variability, which should be promoting residual meridional circulations in the Ferrel and Hadley cells. more
Application Atmosphere Climate Data Records OSI-SAF

BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia

Author(s):
Su, Chun-Hsu; Eizenberg, Nathan; Steinle, Peter; Jakob, Dörte; Fox-Hughes, Paul; White, Christopher J.; Rennie, Susan; Franklin, Charmaine; Dharssi, Imtiaz; Zhu, Hongyan
Publication title: Geoscientific Model Development
2019
 | Volume: 12 | Issue: 5
2019
DOI: 10.5194/gmd-12-2049-2019
Abstract:
Abstract. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis… Abstract. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand, and Southeast Asia. The production of the reanalysis with approximately 12 km horizontal resolution – BARRA-R – is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, the forcing and observational data used to produce BARRA-R, and analyses results from the 2003–2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed, surface pressure, and precipitation. Comparing against the global reanalyses ERA-Interim and MERRA-2, BARRA-R scores lower root mean square errors when evaluated against (point-scale) 2 m temperature, 10 m wind speed, and surface pressure observations. It also shows reduced biases in daily 2 m temperature maximum and minimum at 5 km resolution and a higher frequency of very heavy precipitation days at 5 and 25 km resolution when compared to gridded satellite and gauge analyses. Some issues with BARRA-R are also identified: biases in 10 m wind, lower precipitation than observed over the tropical oceans, and higher precipitation over regions with higher elevations in south Asia and New Zealand. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale ( more
Application Climate Data Records ROM-SAF

Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method

Author(s):
Urraca, Ruben; Antonanzas, Javier; Sanz-Garcia, Andres; Martinez-de-Pison, Francisco Javier
Publication title: Sensors
2019
 | Volume: 19 | Issue: 11
2019
DOI: 10.3390/s19112483
Abstract:
Different types of measuring errors can increase the uncertainty of solar radiation measurements, but most common quality control (QC) methods do not … Different types of measuring errors can increase the uncertainty of solar radiation measurements, but most common quality control (QC) methods do not detect frequent defects such as shading or calibration errors due to their low magnitude. We recently presented a new procedure, the Bias-based Quality Control (BQC), that detects low-magnitude defects by analyzing the stability of the deviations between several independent radiation databases and measurements. In this study, we extend the validation of the BQC by analyzing the quality of all publicly available Spanish radiometric networks measuring global horizontal irradiance (9 networks, 732 stations). Similarly to our previous validation, the BQC found many defects such as shading, soiling, or calibration issues not detected by classical QC methods. The results questioned the quality of SIAR, Euskalmet, MeteoGalica, and SOS Rioja, as all of them presented defects in more than 40% of their stations. Those studies based on these networks should be interpreted cautiously. In contrast, the number of defects was below a 5% in BSRN, AEMET, MeteoNavarra, Meteocat, and SIAR Rioja, though the presence of defects in networks such as AEMET highlights the importance of QC even when using a priori reliable stations. more
Application Atmosphere CM-SAF Climate Data Records

An Uncertainty Quantified Fundamental Climate Data Record for Microwave Humidity Sounders

Author(s):
Hans, Imke; Burgdorf, Martin; Buehler, Stefan; Prange, Marc; Lang, Theresa; John, Viju
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 5
2019
DOI: 10.3390/rs11050548
Abstract:
To date, there is no long-term, stable, and uncertainty-quantified dataset of upper tropospheric humidity (UTH) that can be used for climate research.… To date, there is no long-term, stable, and uncertainty-quantified dataset of upper tropospheric humidity (UTH) that can be used for climate research. As intermediate step towards the overall goal of constructing such a climate data record (CDR) of UTH, we produced a new fundamental climate data record (FCDR) on the level of brightness temperature for microwave humidity sounders that will serve as basis for the CDR of UTH. Based on metrological principles, we constructed and implemented the measurement equation and the uncertainty propagation in the processing chain for the microwave humidity sounders. We reprocessed the level 1b data to obtain newly calibrated uncertainty quantified level 1c data in brightness temperature. Three aspects set apart this FCDR from previous attempts: (1) the data come in a ready-to-use NetCDF format; (2) the dataset provides extensive uncertainty information taking into account the different correlation behaviour of the underlying errors; and (3) inter-satellite biases have been understood and reduced by an improved calibration. Providing a detailed uncertainty budget on these data, this new FCDR provides valuable information for a climate scientist and also for the construction of the CDR. more
Application Climate Data Records EUM-Secr Method

2018 Atmospheric Motion Vector (AMV) Intercomparison Study

Author(s):
Santek, David; Dworak, Richard; Nebuda, Sharon; Wanzong, Steve; Borde, Régis; Genkova, Iliana; García-Pereda, Javier; Galante Negri, Renato; Carranza, Manuel; Nonaka, Kenichi; Shimoji, Kazuki; Oh, Soo Min; Lee, Byung-Il; Chung, Sung-Rae; Daniels, Jaime; Bresky, Wayne
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 19
2019
DOI: 10.3390/rs11192240
Abstract:
Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, Europ… Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, European Organization for the Exploitation of Meteorological Satellites/EUMETSAT, Japan Meteorological Agency/JMA, Korea Meteorological Administration/KMA, Unites States National Oceanic and Atmospheric Administration/NOAA, and the Satellite Application Facility on Support to Nowcasting and Very short range forecasting/NWCSAF) with JMA’s Himawari-8 satellite data and other common input data are here compared. The comparison is based on two different AMV input datasets, calculated with two different image triplets for 21 July 2016, and the use of a prescribed and a specific configuration. The main results of the study are summarized as follows: (1) the differences in the AMV datasets depend very much on the ‘AMV height assignment’ used and much less on the use of a prescribed or specific configuration; (2) the use of the ‘Common Quality Indicator (CQI)’ has a quantified skill in filtering collocated AMVs for an improved statistical agreement between centers; (3) Among the six AMV operational algorithms verified by this AMV Intercomparison, JMA AMV algorithm has the best overall performance considering all validation metrics, mainly due to its new height assignment method: ‘Optimal estimation method considering the observed infrared radiances, the vertical profile of the Numerical Weather Prediction wind, and the estimated brightness temperature using a radiative transfer model’. more
Atmosphere NWC-SAF Software for CDR development Validation

Validation of the IASI FORLI/Eumetsat ozone products usingsatellite (GOME-2), ground-based (Brewer-Dobson, SAOZ) andozonesonde measurements

Author(s):
Boynard, Anne; Hurtmans, Daniel; Garane, Katerina; Goutail, Florence; Hadji-Lazaro, Juliette; Koukouli, Maria Elissavet; Wespes, Catherine; Keppens, Arno; Pommereau, Jean-Pierre; Pazmino, Andrea; Balis, Dimitris; Loyola, Diego; Valks, Pieter; Coheur, Pierre-François; Clerbaux, Cathy
2018
2018
DOI:
Abstract:
Abstract. This paper assesses the quality of IASI/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrie… Abstract. This paper assesses the quality of IASI/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrieved with the Fast Optimal Retrievals on Layers for IASI Ozone (FORLI-O3) v20151001 software for nine years (2008–2017) through an extensive inter-comparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). IASI-A and IASI-B Total O3 Columns (TOCs) are generally consistent, with a global mean difference less than 0.3 % for both day- and nighttime measurements, IASI-A being slightly higher than IASI-B. A global difference less than 2.4 % is found for the tropospheric (TROPO) O3 column product (IASI-A being lower than IASI-B), which is partly due to a temporary issue related to IASI-A viewing angle in 2015. Our validation shows that IASI-A and IASI-B TOCs are consistent with GOME-2, Dobson, Brewer and SAOZ retrieved ones, with global mean differences in the range 0.1–2 % depending on the instruments. The IASI-A and ground-based TOC comparison for the period 2008–July 2017 shows good long-term stability (negative trends within 3 % decade−1). The comparison results between IASI-A and IASI-B against smoothed ozonesonde partial O3 columns vary in altitude and latitude, with maximum standard deviation for the 300–150 hPa column (20–40 %) due to strong ozone variability and a priori uncertainty. The worst agreement with the ozonesondes and with UV-vis retrieved TOC [satellite and ground] is found at the southern high latitudes. Compared to ozonesonde data, IASI-A and IASI-B O3 products overestimate the O3 abundance in the stratosphere (up to 20 % for the 150–25 hPa column) and underestimates the O3 abundance in the troposphere (within 10 % for the mid-latitudes and ~ 18 % for the tropics). Based on the period 2011–2016, non-significant drift is found for the northern hemispheric tropospheric columns while a small drift prevails for the period before 2011. more
AC-SAF Atmosphere Climate Data Records Validation

Validation of CM SAF CLARA-A2 and SARAH-E Surface Solar Radiation Datasets over China

Author(s):
Wang, Yawen; Trentmann, Jörg; Yuan, Wenping; Wild, Martin
Publication title: Remote Sensing
2018
 | Volume: 10 | Issue: 12
2018
DOI: 10.3390/rs10121977
Abstract:
To achieve high-quality surface solar radiation (SSR) data for climate monitoring and analysis, the two satellite-derived monthly SSR datasets of CM S… To achieve high-quality surface solar radiation (SSR) data for climate monitoring and analysis, the two satellite-derived monthly SSR datasets of CM SAF CLARA-A2 and SARAH-E have been validated against a homogenized ground-based dataset covering 59 stations across China for 1993–2015 and 1999–2015, respectively. The satellite products overestimate surface solar irradiance by 10.0 W m−2 in CLARA-A2 and 7.5 W m−2 in SARAH-E on average. A strong urbanization effect has been noted behind the large positive bias in China. The bias decreased after 2004, possibly linked to a weakened attenuating effect of aerosols on radiation in China. Both satellite datasets can reproduce the monthly anomalies of SSR, indicated by a significant correlation around 0.8. Due to the neglection of temporal aerosol variability in the satellite algorithms, the discrepancy between the satellite-estimated and ground-observed SSR trends slightly increases in 1999–2015 as compared to 1993–2015. The seasonal performance of the satellite products shows a better accuracy during warm than cold seasons. With respect to the spatial performance, the effects from anthropogenic aerosols, dust aerosols and high elevation and snow-covered surfaces should be well considered in the satellite SSR retrievals to further improve the performance in the eastern, northwestern and southwestern parts of China, respectively. more
Application Atmosphere CM-SAF Climate Data Records Validation

The EU-FP7 ERA-CLIM2 Project Contribution to Advancing Science and Production of Earth System Climate Reanalyses

Author(s):
Buizza, Roberto; Brönnimann, Stefan; Haimberger, Leopold; Laloyaux, Patrick; Martin, Matthew J.; Fuentes, Manuel; Alonso-Balmaseda, Magdalena; Becker, Andreas; Blaschek, Michael; Dahlgren, Per; de Boisseson, Eric; Dee, Dick; Doutriaux-Boucher, Marie; Feng, Xiangbo; John, Viju O.; Haines, Keith; Jourdain, Sylvie; Kosaka, Yuki; Lea, Daniel; Lemarié, Florian; Mayer, Michael; Messina, Palmira; Perruche, Coralie; Peylin, Philippe; Pullainen, Jounie; Rayner, Nick; Rustemeier, Elke; Schepers, Dinand; Saunders, Roger; Schulz, Jörg; Sterin, Alexander; Stichelberger, Sebastian; Storto, Andrea; Testut, Charles-Emmanuel; Valente, Maria-Antóonia; Vidard, Arthur; Vuichard, Nicolas; Weaver, Anthony; While, James; Ziese, Markus
Publication title: Bulletin of the American Meteorological Society
2018
 | Volume: 99 | Issue: 5
2018
DOI: 10.1175/BAMS-D-17-0199.1
Abstract:
Abstract The European Reanalysis of Global Climate Observations 2 (ERA-CLIM2) is a European Union Seventh Framework Project started in January 2014 an… Abstract The European Reanalysis of Global Climate Observations 2 (ERA-CLIM2) is a European Union Seventh Framework Project started in January 2014 and due to be completed in December 2017. It aims to produce coupled reanalyses, which are physically consistent datasets describing the evolution of the global atmosphere, ocean, land surface, cryosphere, and the carbon cycle. ERA-CLIM2 has contributed to advancing the capacity for producing state-of-the-art climate reanalyses that extend back to the early twentieth century. ERA-CLIM2 has led to the generation of the first European ensemble of coupled ocean, sea ice, land, and atmosphere reanalyses of the twentieth century. The project has funded work to rescue and prepare observations and to advance the data-assimilation systems required to generate operational reanalyses, such as the ones planned by the European Union Copernicus Climate Change Service. This paper summarizes the main goals of the project, discusses some of its main areas of activities, and presents some of its key results. more
Application EUM-Secr International cooperation

State of the Climate in 2017

Author(s):
Hartfield, Gail; Blunden, Jessica; Arndt, Derek S.
Publication title: Bulletin of the American Meteorological Society
2018
 | Volume: 99 | Issue: 8
2018
DOI: 10.1175/2018BAMSStateoftheClimate.1
Abstract:
Abstract Editor’s note: For easy download the posted pdf of the State of the Climate for 2018 is a low-resolution file. A high-resolution … Abstract Editor’s note: For easy download the posted pdf of the State of the Climate for 2018 is a low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Satellite or ground-based measurements for production of site specific hourly irradiance data: Which is most accurate and where?

Author(s):
Palmer, Diane; Koubli, Elena; Cole, Ian; Betts, Tom; Gottschalg, Ralph
Publication title: Solar Energy
2018
 | Volume: 165
2018
DOI: 10.1016/j.solener.2018.03.029
Abstract:
Site-specific satellite-derived hourly global horizontal irradiance is compared with that obtained from extrapolation and interpolation of values meas… Site-specific satellite-derived hourly global horizontal irradiance is compared with that obtained from extrapolation and interpolation of values measured by ground-based weather stations. A national assessment of three satellite models and two ground-based techniques is described. A number of physiographic factors are examined to allow identification of the optimal resource. The chief influences are determined as: factors associated with latitude; terrain ruggedness; and weather station clustering/density. Whilst these factors act in combination, weather station density was found to be fundamental for a country like the UK, with its ever-changing weather. The decision between satellite and ground-based irradiance data based on accuracy is not straightforward. It depends on the exactitude of the selected satellite model and the concentration of pyranometric stations. more
Atmosphere CM-SAF Climate Data Records Validation

Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

Author(s):
Nightingale, Joanne; Boersma, Klaas; Muller, Jan-Peter; Compernolle, Steven; Lambert, Jean-Christopher; Blessing, Simon; Giering, Ralf; Gobron, Nadine; De Smedt, Isabelle; Coheur, Pierre; George, Maya; Schulz, Jörg; Wood, Alexander
Publication title: Remote Sensing
2018
 | Volume: 10 | Issue: 8
2018
DOI: 10.3390/rs10081254
Abstract:
Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of… Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts, and manage natural resources. Policymakers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products, as well as the reference measurements used to calibrate, validate, or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service (C3S), the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite-derived datasets, by prototyping a generic system for the implementation and evaluation of quality assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface albedo, leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO). The provision of standardised QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products and their specific applications. more
AC-SAF Application Atmosphere EUM-Secr International cooperation Land Validation

Observations for Reanalyses

Author(s):
Brönnimann, Stefan; Allan, Rob; Atkinson, Christopher; Buizza, Roberto; Bulygina, Olga; Dahlgren, Per; Dee, Dick; Dunn, Robert; Gomes, Pedro; John, Viju O.; Jourdain, Sylvie; Haimberger, Leopold; Hersbach, Hans; Kennedy, John; Poli, Paul; Pulliainen, Jouni; Rayner, Nick; Saunders, Roger; Schulz, Jörg; Sterin, Alexander; Stickler, Alexander; Titchner, Holly; Valente, Maria Antonia; Ventura, Clara; Wilkinson, Clive
Publication title: Bulletin of the American Meteorological Society
2018
 | Volume: 99 | Issue: 9
2018
DOI: 10.1175/BAMS-D-17-0229.1
Abstract:
Abstract Global dynamical reanalyses of the atmosphere and ocean fundamentally rely on observations, not just for the assimilation (i.e., for the defi… Abstract Global dynamical reanalyses of the atmosphere and ocean fundamentally rely on observations, not just for the assimilation (i.e., for the definition of the state of the Earth system components) but also in many other steps along the production chain. Observations are used to constrain the model boundary conditions, for the calibration or uncertainty determination of other observations, and for the evaluation of data products. This requires major efforts, including data rescue (for historical observations), data management (including metadatabases), compilation and quality control, and error estimation. The work on observations ideally occurs one cycle ahead of the generation cycle of reanalyses, allowing the reanalyses to make full use of it. In this paper we describe the activities within ERA-CLIM2, which range from surface, upper-air, and Southern Ocean data rescue to satellite data recalibration and from the generation of snow-cover products to the development of a global station data metadatabase. The project has not produced new data collections. Rather, the data generated has fed into global repositories and will serve future reanalysis projects. The continuation of this effort is first contingent upon the organization of data rescue and also upon a series of targeted research activities to address newly identified in situ and satellite records. more
Application EUM-Secr International cooperation Validation

Land Surface Albedo Derived on a Ten Daily Basis from Meteosat Second Generation Observations: The NRT and Climate Data Record Collections from the EUMETSAT LSA SAF

Author(s):
Carrer, Dominique; Moparthy, Suman; Lellouch, Gabriel; Ceamanos, Xavier; Pinault, Florian; Freitas, Sandra; Trigo, Isabel
Publication title: Remote Sensing
2018
 | Volume: 10 | Issue: 8
2018
DOI: 10.3390/rs10081262
Abstract:
Land surface albedo determines the splitting of downwelling solar radiation into components which are either reflected back to the atmosphere or absor… Land surface albedo determines the splitting of downwelling solar radiation into components which are either reflected back to the atmosphere or absorbed by the surface. Land surface albedo is an important variable for the climate community, and therefore was defined by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Within the scope of the Satellite Application Facility for Land Surface Analysis (LSA SAF) of EUMETSAT (European Organization for the Exploitation of Meteorological Satellites), a near-real time (NRT) daily albedo product was developed in the last decade from observations provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary satellites of the Meteosat Second Generation (MSG) series. In this study we present a new collection of albedo satellite products based on the same satellite data. The MSG Ten-day Albedo (MTAL) product incorporates MSG observations over 31 days with a frequency of NRT production of 10 days. The MTAL collection is more dedicated to climate analysis studies compared to the daily albedo that was initially designed for the weather prediction community. For this reason, a homogeneous reprocessing of MTAL was done in 2018 to generate a climate data record (CDR). The resulting product is called MTAL-R and has been made available to the community in addition to the NRT version of the MTAL product which has been available for several years. The retrieval algorithm behind the MTAL products comprises three distinct modules: One for atmospheric correction, one for daily inversion of a semi-empirical model of the bidirectional reflectance distribution function, and one for monthly composition, that also determines surface albedo values. In this study the MTAL-R CDR is compared to ground surface measurements and concomitant albedo products collected by sensors on-board polar-orbiting satellites (SPOT-VGT and MODIS). We show that MTAL-R meets the quality requirements if MODIS or SPOT-VGT are considered as reference. This work leads to 14 years of production of geostationary land surface albedo products with a guaranteed continuity in the LSA SAF for the future years with the forthcoming third generation of European geostationary satellites. more
Application Climate Data Records LSA-SAF Land Validation

Evaluating the diurnal cycle of South Atlantic stratocumulus clouds as observed by MSG SEVIRI

Author(s):
Seethala, Chellappan; Meirink, Jan Fokke; Horváth, Ákos; Bennartz, Ralf; Roebeling, Rob
Publication title: Atmospheric Chemistry and Physics
2018
 | Volume: 18 | Issue: 17
2018
DOI: 10.5194/acp-18-13283-2018
Abstract:
Abstract. Marine stratocumulus (Sc) clouds play an essential role in the earth radiation budget. Here, we compare liquid water path (LWP), cloud optic… Abstract. Marine stratocumulus (Sc) clouds play an essential role in the earth radiation budget. Here, we compare liquid water path (LWP), cloud optical thickness (τ), and cloud droplet effective radius (re) retrievals from 2 years of collocated Spinning Enhanced Visible and Infrared Imager (SEVIRI), Moderate Resolution Imaging Spectroradiometer (MODIS), and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations; estimate the effect of biomass burning smoke on passive imager retrievals; and evaluate the diurnal cycle of South Atlantic marine Sc clouds.The effect of absorbing aerosols from biomass burning on the retrievals was investigated using the aerosol index (AI) obtained from the Ozone Monitoring Instrument (OMI). SEVIRI and MODIS LWPs were found to decrease with increasing AI relative to TMI LWP, consistent with well-known negative visible/near-infrared (VIS/NIR) retrieval biases in τ and re. In the aerosol-affected months of July–August–September, SEVIRI LWP – based on the 1.6 µm re – was biased low by 14 g m−2 ( ∼ 16 %) compared to TMI in overcast scenes, while MODIS LWP showed a smaller low bias of 4 g m−2 ( ∼ 5 %) for the 1.6 µm channel and a high bias of 8 g m−2 ( ∼ 10 %) for the 3.7 µm channel compared to TMI. Neglecting aerosol-affected pixels reduced the mean SEVIRI–TMI LWP bias considerably. For 2 years of data, SEVIRI LWP had a correlation with TMI and MODIS LWP of about 0.86 and 0.94, respectively, and biases of only 4–8 g m−2 (5 %–10 %) for overcast cases.The SEVIRI LWP diurnal cycle was in good overall agreement with TMI except in the aerosol-affected months. Both TMI and SEVIRI LWP decreased from morning to late afternoon, after which a slow increase was observed. Terra and Aqua MODIS mean LWPs also suggested a similar diurnal variation. The relative amplitude of the 2-year-mean and seasonal-mean LWP diurnal cycle varied between 35 % and 40 % from morning to late afternoon for overcast cases. The diurnal variation in SEVIRI LWP was mainly due to changes in τ, while re showed only little diurnal variability. more
Application Atmosphere CM-SAF Climate Data Records

Climate Data Records from Meteosat First Generation Part I: Simulation of Accurate Top-of-Atmosphere Spectral Radiance over Pseudo-Invariant Calibration Sites for the Retrieval of the In-Flight Visible Spectral Response

Author(s):
Govaerts, Yves; Rüthrich, Frank; John, Viju; Quast, Ralf
Publication title: Remote Sensing
2018
 | Volume: 10 | Issue: 12
2018
DOI: 10.3390/rs10121959
Abstract:
Meteosat First-Generation satellites have acquired more than 30 years of observations that could potentially be used for the generation of a Climate D… Meteosat First-Generation satellites have acquired more than 30 years of observations that could potentially be used for the generation of a Climate Data Record. The availability of harmonized and accurate a Fundamental Climate Data Record is a prerequisite to such generation. Meteosat Visible and Infrared Imager radiometers suffer from inaccurate pre-launch spectral function characterization and spectral ageing constitutes a serious limitation to achieve such prerequisite. A new method was developed for the retrieval of the pre-launch instrument spectral function and its ageing. This recovery method relies on accurately simulated top-of-atmosphere spectral radiances matching observed digital count values. This paper describes how these spectral radiances are simulated over pseudo-invariant targets such as open ocean, deep convective clouds and bright desert surface. The radiative properties of these targets are described with a limited number of parameters of known uncertainty. Typically, a single top-of-atmosphere radiance spectrum can be simulated with an estimated uncertainty of about 5%. The independent evaluation of the simulated radiance accuracy is also addressed in this paper. It includes two aspects: the comparison with narrow-band well-calibrated radiometers and a spectral consistency analysis using SEVIRI/HRVIS band on board Meteosat Second Generation which was accurately characterized pre-launch. On average, the accuracy of these simulated spectral radiances is estimated to be about ±2%. more
Application Climate Data Records EUM-Secr Method

Bright Prospects for Arctic Sea Ice Prediction on Subseasonal Time Scales

Author(s):
Zampieri, L.; Goessling, H.F.; Jung, T.
Publication title: Geophysical Research Letters
2018
 | Volume: 45 | Issue: 18
2018
DOI: 10.1029/2018GL079394
Abstract:
With retreating sea ice and increasing human activities in the Arctic come a growing need for reliable sea ice forecasts up to months ahead. We exploi… With retreating sea ice and increasing human activities in the Arctic come a growing need for reliable sea ice forecasts up to months ahead. We exploit the subseasonal-to-seasonal prediction database and provide the first thorough assessment of the skill of operational forecast systems in predicting the location of the Arctic sea ice edge on these time scales. We find large differences in skill between the systems, with some showing a lack of predictive skill even at short weather time scales and the best producing skillful forecasts more than 1.5 months ahead. This highlights that the area of subseasonal prediction in the Arctic is in an early stage but also that the prospects are bright, especially for late summer forecasts. To fully exploit this potential, it is argued that it will be imperative to reduce systematic model errors and develop advanced data assimilation capacity. ©2018. The Authors. more
Application Climate Data Records Cryosphere OSI-SAF

Arctic sea-ice change tied to its mean state through thermodynamic processes

Author(s):
Massonnet, François; Vancoppenolle, Martin; Goosse, Hugues; Docquier, David; Fichefet, Thierry; Blanchard-Wrigglesworth, Edward
Publication title: Nature Climate Change
2018
 | Volume: 8 | Issue: 7
2018
DOI: 10.1038/s41558-018-0204-z
Abstract:
One of the clearest manifestations of ongoing global climate change is the dramatic retreat and thinning of the Arctic sea-ice cover1. While all state… One of the clearest manifestations of ongoing global climate change is the dramatic retreat and thinning of the Arctic sea-ice cover1. While all state-of-the-art climate models consistently reproduce the sign of these changes, they largely disagree on their magnitude1,2,3,4, the reasons for which remain contentious3,5,6,7. As such, consensual methods to reduce uncertainty in projections are lacking7. Here, using the CMIP5 ensemble, we propose a process-oriented approach to revisit this issue. We show that intermodel differences in sea-ice loss and, more generally, in simulated sea-ice variability, can be traced to differences in the simulation of seasonal growth and melt. The way these processes are simulated is relatively independent of the complexity of the sea-ice model used, but rather a strong function of the background thickness. The larger role played by thermodynamic processes as sea ice thins8,9 further suggests that the recent10 and projected11 reductions in sea-ice thickness induce a transition of the Arctic towards a state with enhanced volume seasonality but reduced interannual volume variability and persistence, before summer ice-free conditions eventually occur. These results prompt modelling groups to focus their priorities on the reduction of sea-ice thickness biases. more
Application Climate Data Records Cryosphere OSI-SAF

An Overview of European Efforts in Generating Climate Data Records

Author(s):
Su, Z.; Timmermans, W.; Zeng, Y.; Schulz, J.; John, V. O.; Roebeling, R. A.; Poli, P.; Tan, D.; Kaspar, F.; Kaiser-Weiss, A. K.; Swinnen, E.; Toté, C.; Gregow, H.; Manninen, T.; Riihelä, A.; Calvet, J.-C.; Ma, Y.; Wen, J.
Publication title: Bulletin of the American Meteorological Society
2018
 | Volume: 99 | Issue: 2
2018
DOI: 10.1175/BAMS-D-16-0074.1
Abstract:
Abstract The Coordinating Earth Observation Data Validation for Reanalysis for Climate Services project (CORE-CLIMAX) aimed to substantiate how Copern… Abstract The Coordinating Earth Observation Data Validation for Reanalysis for Climate Services project (CORE-CLIMAX) aimed to substantiate how Copernicus observations and products can contribute to climate change analyses. CORE-CLIMAX assessed the European capability to provide climate data records (CDRs) of essential climate variables (ECVs), prepared a structured process to derive CDRs, developed a harmonized approach for validating essential climate variable CDRs, identified the integration of CDRs into the reanalysis chain, and formulated a process to compare the results of different reanalysis techniques. With respect to the Copernicus Climate Change Service (C3S), the systematic application and further development of the CORE-CLIMAX system maturity matrix (SMM) and the spinoff application performance metric (APM) were strongly endorsed to be involved in future implementations of C3S. We concluded that many of the current CDRs are not yet sufficiently mature to be used in reanalysis or applied in climate studies. Thus, the production of consistent high-resolution data records remains a challenge that needs more research urgently. Extending ECVs to close climate cycle budgets (e.g., essential water variables) is a next step linking CDRs to sectoral applications. more
Application EUM-Secr International cooperation Validation

A scalable method for estimating rooftop solar irradiation potential over large regions

Author(s):
Buffat, René; Grassi, Stefano; Raubal, Martin
Publication title: Applied Energy
2018
 | Volume: 216
2018
DOI: 10.1016/j.apenergy.2018.02.008
Abstract:
An estimate of solar irradiation potential over large regions requires the knowledge of the long-term spatio-temporal distribution of the solar radiat… An estimate of solar irradiation potential over large regions requires the knowledge of the long-term spatio-temporal distribution of the solar radiation as well as the identification of the suitable surfaces where the photovoltaic (PV) installations can be built. These main components can be modelled in different ways and are thus affected by different sources of uncertainty. Thus, when estimating the exploitable potential over large regions, it is important to measure the accuracy of the entire process. In this work, we provide a generic method to estimate the solar irradiation potential of rooftops over large regions and an estimate of the corresponding uncertainties when calculating the long-term electricity generation of PV plants. This method uses satellite based solar radiation data covering a period of 22 years, with a temporal resolution of 30 min and a spatial resolution of 3.8–5.6 km. Suitable surfaces on rooftops are identified using Digital Surface Models combined with building footprints. This allows to determine the geometry of rooftops, such as slope, and orientation with a spatial resolution of 0.5 m. Finally, we calculated the electricity generation based on models which take into account all characteristics of PV system components. In order to estimate the accuracy of the model for electricity production, we compared the monthly generation of 500 PV plants in Switzerland consisting of different PV technologies (mono-crystalline, poly-crystalline and thin film) with the estimates. The validation results show a correlation coefficient (R2) of 0.9 and a median monthly relative error between 0.28% (August) and 28.08% (December). The monthly estimates are more accurate during summer time, while spatially and technology-wise no significant differences are found. more
Application Atmosphere CM-SAF Climate Data Records

Validation practices for satellite-based Earth observation data across communities: EO VALIDATION

Author(s):
Loew, Alexander; Bell, William; Brocca, Luca; Bulgin, Claire E.; Burdanowitz, Jörg; Calbet, Xavier; Donner, Reik V.; Ghent, Darren; Gruber, Alexander; Kaminski, Thomas; Kinzel, Julian; Klepp, Christian; Lambert, Jean-Christopher; Schaepman-Strub, Gabriela; Schröder, Marc; Verhoelst, Tijl
Publication title: Reviews of Geophysics
2017
 | Volume: 55 | Issue: 3
2017
DOI: 10.1002/2017RG000562
Abstract:
Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth… Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth Observation (EO) communities to address the validation problem which results in a large variety of methods as well as terminology. This paper reviews state-of-the-art methods of satellite validation and documents their similarities and differences. First, the overall validation objectives and terminologies are specified, followed by a generic mathematical formulation of the validation problem. Metrics currently used as well as more advanced EO validation approaches are introduced thereafter. An outlook on the applicability and requirements of current EO validation approaches and targets is given. more
Application Atmosphere CM-SAF Climate Data Records

Validation and Cross-Validation Methods for ASCAT

Author(s):
Anderson, Craig; Figa-Saldana, Julia; Wilson, John Julian William; Ticconi, Francesca
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
 | Volume: 10 | Issue: 5
2017
DOI: 10.1109/JSTARS.2016.2639784
Abstract:
The advanced scatterometer (ASCAT) is a fan beam scatterometer carried on board the Metop series of satellites. Its primary objective is to measure oc… The advanced scatterometer (ASCAT) is a fan beam scatterometer carried on board the Metop series of satellites. Its primary objective is to measure ocean backscatter for the retrieval of ocean wind vectors. Two ASCAT instruments (ASCAT-A and ASCAT-B) are operational and are independently calibrated using a number of ground-based transponders. The first seven years of data from ASCAT-A have recently been processed into a climate data record. This paper describes a number of methods for cross-validating the data from the two instruments and for assessing the quality and stability of the climate data record. The methods are based on backscatter from the Amazon rainforest, mean backscatter from the open ocean, comparison of measured and modeled ocean backscatter, and ocean cone metrics. These methods show that the climate data record, which covers the period January 2007 to March 2014, has a very high stability (with trends around 0.005 dB per year), good absolute and relative calibration (better than 0.1 dB), and a good across swath calibration (peak to peak variation of less than 0.1 dB). For operational data covering the period April 2015 to March 2016, the methods indicate that ASCAT-B backscatter is around 0.1-0.2 dB higher than ASCAT-A (depending on which beam is considered). This difference is due to a combination of factors: minor changes in calibration algorithms, a minor change in the behavior of the ASCAT-A internal calibration system, and the strategy used to update calibration files in the processing system. more
Climate Data Records EUM-Secr Validation

Toward Scatterometer Winds Assimilation in the Mesoscale HARMONIE Model

Author(s):
Marseille, G.-J.; Stoffelen, A.
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
 | Volume: 10 | Issue: 5
2017
DOI: 10.1109/JSTARS.2016.2640339
Abstract:
Data assimilation (DA) experiments have been conducted with the high-resolution limited-area model HirLAM Aladin Regional Mesoscale Operational NWP In… Data assimilation (DA) experiments have been conducted with the high-resolution limited-area model HirLAM Aladin Regional Mesoscale Operational NWP In Euromed (HARMONIE), which is operational at most weather centers, which are part of the European HirLAM consortium. Recently, the assimilation of scatterometer ocean surface winds was introduced, showing limited forecast skill improvement. Possible explanations are discussed. These include model bias and the time mismatch between observation and analysis time, which introduces nonnegligible correlated errors in a three-dimensional (3-D) variational assimilation system. Also, ignoring the time mismatch increases the innovation, i.e., the observation minus background (model short-term forecast), by about 20% for scatterometer winds. The use of observations as point observations in most DA systems needs reconsideration for mesoscale DA. The introduction of observation operators, taking into account the instrument footprint, would improve the innovation by about 5% for scatterometer winds. Additional directions for improved use of observations in HARMONIE are discussed based on the notice that DA is an inherent deterministic concept. Hence, the selection of the spatial scale for deterministic DA should depend primarily on the 4-D observation coverage rather than the effective model resolution. © 2008-2012 IEEE. more
Application Atmosphere Climate Data Records

Surface reflectivity climatologies from UV to NIR determined from Earth observations by GOME-2 and SCIAMACHY: SURFACE REFLECTIVITY CLIMATOLOGIES

Author(s):
Tilstra, L. G.; Tuinder, O. N. E.; Wang, P.; Stammes, P.
Publication title: Journal of Geophysical Research: Atmospheres
2017
 | Volume: 122 | Issue: 7
2017
DOI: 10.1002/2016JD025940
Abstract:
The primary goal of this paper is to introduce two new surface reflectivity climatologies. The two databases contain the Lambertian-equivalent reflect… The primary goal of this paper is to introduce two new surface reflectivity climatologies. The two databases contain the Lambertian-equivalent reflectivity (LER) of the Earth's surface, and they are meant to support satellite retrieval of trace gases and of cloud and aerosol information. The surface LER databases are derived from the Global Ozone Monitoring Experiment (GOME)-2 and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instruments and can be considered as improved and extended descendants of earlier surface LER climatologies based on the Total Ozone Mapping Spectrometer (TOMS), GOME-1, and Ozone Monitoring Instrument (OMI) instruments. The GOME-2 surface LER database consists of 21 wavelength bands that span the wavelength range from 335 to 772 nm. The SCIAMACHY surface LER database covers the wavelength range between 335 and 1670 nm in 29 wavelength bands. The two databases are made for each month of the year, and their spatial resolution is 1° × 1°. In this paper we present the methods that are used to derive the surface LER; we analyze the spatial and temporal behavior of the surface LER fields and study the amount of residual cloud contamination in the databases. For several surface types we analyze the spectral surface albedo and the seasonal variation. When compared to the existing surface LER databases, both databases are found to perform well. As an example of possible application of the databases we study the performance of the Fast Retrieval Scheme for Clouds from the Oxygen A-band (FRESCO) cloud information retrieval when it is equipped with the new surface albedo databases. We find considerable improvements. The databases introduced here can not only improve retrievals from GOME-2 and SCIAMACHY but also support those from other instruments, such as TROPOspheric Monitoring Instrument (TROPOMI), to be launched in 2017. more
AC-SAF Atmosphere Climate Data Records Method

State of the Climate in 2016

Author(s):
Blunden, Jessica; Arndt, Derek S.
Publication title: Bulletin of the American Meteorological Society
2017
 | Volume: 98 | Issue: 8
2017
DOI: 10.1175/2017BAMSStateoftheClimate.1
Abstract:
Abstract Editor’s note: For easy download the posted pdf of the State of the Climate for 2017 is a low-resolution file. A high-resolution … Abstract Editor’s note: For easy download the posted pdf of the State of the Climate for 2017 is a low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Scientific Developments and the EPS-SG Scatterometer

Author(s):
Stoffelen, Ad; Aaboe, Signe; Calvet, Jean-Christophe; Cotton, James; De Chiara, Giovanna; Saldana, Julia Figa; Mouche, Alexis Aurelien; Portabella, Marcos; Scipal, Klaus; Wagner, Wolfgang
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
 | Volume: 10 | Issue: 5
2017
DOI: 10.1109/JSTARS.2017.2696424
Abstract:
The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned … The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned for launch in 2022, has a direct heritage from the successful advanced scatterometer (ASCAT) flown on the current EPS satellites. In addition, SCA will represent three major innovations with respect to ASCAT, namely: 1) Cross polarization and horizontal copolarization; 2) a nominal spatial resolution of 25 km; and 3) 20% greater spatial coverage than ASCAT. The associated expected science and application benefits that led the SCA design are discussed with respect to ocean, land, and sea ice applications for near-real time, climate monitoring, and research purposes. Moreover, an option to implement an ocean Doppler capability to retrieve the ocean motion vector is briefly discussed as well. In conclusion, the SCA instrument innovations are well set to provide timely benefits in all the main application areas of the scatterometer (winds, soil moisture, sea ice) and can be expected to contribute to new and more sophisticated meteorological, oceanographic, land, sea ice, and climate services in the forthcoming SCA era. more
Application Atmosphere Climate Data Records Land OSI-SAF

Recent Advances in Satellite Data Rescue

Author(s):
Poli, Paul; Dee, Dick P.; Saunders, Roger; John, Viju O.; Rayer, Peter; Schulz, Jörg; Holmlund, Kenneth; Coppens, Dorothee; Klaes, Dieter; Johnson, James E.; Esfandiari, Asghar E.; Gerasimov, Irina V.; Zamkoff, Emily B.; Al-Jazrawi, Atheer F.; Santek, David; Albani, Mirko; Brunel, Pascal; Fennig, Karsten; Schröder, Marc; Kobayashi, Shinya; Oertel, Dieter; Döhler, Wolfgang; Spänkuch, Dietrich; Bojinski, Stephan
Publication title: Bulletin of the American Meteorological Society
2017
 | Volume: 98 | Issue: 7
2017
DOI: 10.1175/BAMS-D-15-00194.1
Abstract:
Abstract To better understand the impacts of climate change, environmental monitoring capabilities must be enhanced by deploying additional and more a… Abstract To better understand the impacts of climate change, environmental monitoring capabilities must be enhanced by deploying additional and more accurate satellite- and ground-based (including in situ) sensors. In addition, reanalysis of observations collected decades ago but long forgotten can unlock precious information about the recent past. Historical, in situ observations mainly cover densely inhabited areas and frequently traveled routes. In contrast, large selections of early meteorological satellite data, waiting to be exploited today, provide information about remote areas unavailable from any other source. When initially collected, these satellite data posed great challenges to transmission and archiving facilities. As a result, data access was limited to the main teams of scientific investigators associated with the instruments. As archive media have aged, so have the mission scientists and other pioneers of satellite meteorology, who sometimes retired in possession of unique and unpublished information. This paper presents examples of recently recovered satellite data records, including satellite imagery, early infrared hyperspectral soundings, and early microwave humidity soundings. Their value for climate applications today can be realized using methods and techniques that were not yet available when the data were first collected, including efficient and accurate observation simulators and data assimilation into reanalyses. Modern technical infrastructure allows serving entire mission datasets online, enabling easy access and exploration by a broad range of users, including new and old generations of climate scientists. more
EUM-Secr International cooperation Method

Postmillennium changes in stratospheric temperature consistently resolved by GPS radio occultation and AMSU observations: Temperature Change from GPS-RO and AMSU

Author(s):
Khaykin, S. M.; Funatsu, B. M.; Hauchecorne, A.; Godin-Beekmann, S.; Claud, C.; Keckhut, P.; Pazmino, A.; Gleisner, H.; Nielsen, J. K.; Syndergaard, S.; Lauritsen, K. B.
Publication title: Geophysical Research Letters
2017
 | Volume: 44 | Issue: 14
2017
DOI: 10.1002/2017GL074353
Abstract:
Temperature changes in the lower and middle stratosphere during 2001–2016 are evaluated using measurements from GPS Radio Occultation (RO) and Advance… Temperature changes in the lower and middle stratosphere during 2001–2016 are evaluated using measurements from GPS Radio Occultation (RO) and Advanced Microwave Sounding Unit (AMSU) aboard the Aqua satellite. After downsampling of GPS-RO profiles according to the AMSU weighting functions, the spatially and seasonally resolved trends from the two data sets are in excellent agreement. The observations indicate that the middle stratosphere has cooled in the time period 2002–2016 at an average rate of −0.14 ± 0.12 to −0.36 ± 0.14 K/decade, while no significant change was found in the lower stratosphere. The meridionally and vertically resolved trends from high-resolution GPS-RO data exhibit a marked interhemispheric asymmetry and highlight a distinct boundary between tropospheric and stratospheric temperature change regimes matching the tropical thermal tropopause. The seasonal pattern of trend reveals significant opposite-sign structures at high and low latitudes, providing indication of seasonally varying change in stratospheric circulation. more
Application Atmosphere Climate Data Records ROM-SAF

Noise performance of microwave humidity sounders over their lifetime

Author(s):
Hans, Imke; Burgdorf, Martin; John, Viju O.; Mittaz, Jonathan; Buehler, Stefan A.
Publication title: Atmospheric Measurement Techniques
2017
 | Volume: 10 | Issue: 12
2017
DOI: 10.5194/amt-10-4927-2017
Abstract:
Abstract. The microwave humidity sounders Special Sensor Microwave Water Vapor Profiler (SSMT-2), Advanced Microwave Sounding Unit-B (AMSU-B) and Micr… Abstract. The microwave humidity sounders Special Sensor Microwave Water Vapor Profiler (SSMT-2), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) to date have been providing data records for 25 years. So far, the data records lack uncertainty information essential for constructing consistent long time data series. In this study, we assess the quality of the recorded data with respect to the uncertainty caused by noise. We calculate the noise on the raw calibration counts from the deep space views (DSVs) of the instrument and the noise equivalent differential temperature (NEΔT) as a measure for the radiometer sensitivity. For this purpose, we use the Allan deviation that is not biased from an underlying varying mean of the data and that has been suggested only recently for application in atmospheric remote sensing. Moreover, we use the bias function related to the Allan deviation to infer the underlying spectrum of the noise. As examples, we investigate the noise spectrum in flight for some instruments. For the assessment of the noise evolution in time, we provide a descriptive and graphical overview of the calculated NEΔT over the life span of each instrument and channel. This overview can serve as an easily accessible information for users interested in the noise performance of a specific instrument, channel and time. Within the time evolution of the noise, we identify periods of instrumental degradation, which manifest themselves in an increasing NEΔT, and periods of erratic behaviour, which show sudden increases of NEΔT interrupting the overall smooth evolution of the noise. From this assessment and subsequent exclusion of the aforementioned periods, we present a chart showing available data records with NEΔT \textless 1 K. Due to overlapping life spans of the instruments, these reduced data records still cover without gaps the time since 1994 and may therefore serve as a first step for constructing long time series. Our method for count noise estimation, that has been used in this study, will be used in the data processing to provide input values for the uncertainty propagation in the generation of a new set of Fundamental Climate Data Records (FCDRs) that are currently produced in the project Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO). more
Climate Data Records EUM-Secr Method

Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment

Author(s):
Thorne, Peter W.; Madonna, Fabio; Schulz, Joerg; Oakley, Tim; Ingleby, Bruce; Rosoldi, Marco; Tramutola, Emanuele; Arola, Antti; Buschmann, Matthias; Mikalsen, Anna C.; Davy, Richard; Voces, Corinne; Kreher, Karin; De Maziere, Martine; Pappalardo, Gelsomina
Publication title: Geoscientific Instrumentation, Methods and Data Systems
2017
 | Volume: 6 | Issue: 2
2017
DOI: 10.5194/gi-6-453-2017
Abstract:
Abstract. There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and ope… Abstract. There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies, etc. The Horizon 2020 project GAIA–CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is correct. Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available and maintains rich metadata. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based on such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate on networks measuring primarily a subset of the atmospheric Essential Climate Variables of interest to GAIA–CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream example applications of the GAIA–CLIM project. However, the approach laid out should be more widely applicable across a broad range of application areas. If broadly adopted, the system-of-systems approach will have potential benefits in guiding users to the most appropriate set of observations for their needs and in highlighting to network owners and operators areas for potential improvement. more
EUM-Secr International cooperation Validation

Long-Term Scatterometer Wind Climate Data Records

Author(s):
Verhoef, Anton; Vogelzang, Jur; Verspeek, Jeroen; Stoffelen, Ad
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
 | Volume: 10 | Issue: 5
2017
DOI: 10.1109/JSTARS.2016.2615873
Abstract:
The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) prod… The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) produces near-real-time scatterometer ocean vector winds since almost 20 years already. Data from the European remote sensing satellites (ERS-1 and ERS-2 scatterometer), QuikSCAT (SeaWinds), Metop (ASCAT), Oceansat 2 (OSCAT), and RapidScat on the International Space Station have been, or are being, produced. The OSI SAF scatterometer products, produced at the Royal Netherlands Meteorological Institute, provide superior comparison to both buoy and numerical weather prediction (NWP) datasets. Moreover, the wind processing software is publicly available through the EUMETSAT NWP SAF. An increasing amount of users employs scatterometer wind data for climate studies. However, the wind retrieval algorithms have been continuously improved over the years and the currently existing archives of near-real-time data are not always suitable to fulfill the need for homogeneous datasets spanning a longer period of time. Currently, only few validated vector wind climate datasets are available. Therefore, the OSI SAF is reprocessing several offline datasets. This paper is focusing on two climate data records from SeaWinds and ASCAT winds, which together span the period from 1999 to 2014. The data are compared to the NWP model and buoy winds. The stability of the wind characteristics is assessed and an attempt is made to attribute temporal changes to climatological and NWP model changes over time. more
Atmosphere Climate Data Records OSI-SAF Validation

Improved Use of Scatterometer Measurements by Using Stress-Equivalent Reference Winds

Author(s):
de Kloe, Jos; Stoffelen, Ad; Verhoef, Anton
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
 | Volume: 10 | Issue: 5
2017
DOI: 10.1109/JSTARS.2017.2685242
Abstract:
Numerical weather prediction (NWP) and buoy ocean surface winds show some systematic differences with satellite scatterometer and radiometer wind meas… Numerical weather prediction (NWP) and buoy ocean surface winds show some systematic differences with satellite scatterometer and radiometer wind measurements, both in statistical results and in local geographical regions. It is possible to rescale these reference winds to remove certain aspects of these systematic differences. Space-borne ocean surface winds actually measure ocean surface roughness, which is related more directly to stress. Air mass density is relevant in the air-sea momentum transfer as captured in the stress vector. Therefore, apart from the already common “neutral wind correction” for atmospheric stratification, also a “mass density wind correction” is investigated here to obtain a better correspondence between satellite stress measurements and buoy or NWP winds. The bicorrected winds are called stress-equivalent winds. Stress-equivalent winds do not strongly depend on the drag formulation used and provide a rather direct standard for comparison and assimilation in user applications. This paper presents details on how this correction is performed and first results that show the benefits of this correction mainly in the extratropical regions. more
Atmosphere Climate Data Records Method OSI-SAF

Impact of AVHRR Channel 3b Noise on Climate Data Records: Filtering Method Applied to the CM SAF CLARA-A2 Data Record

Author(s):
Karlsson, Karl-Göran; Håkansson, Nina; Mittaz, Jonathan; Hanschmann, Timo; Devasthale, Abhay
Publication title: Remote Sensing
2017
 | Volume: 9 | Issue: 6
2017
DOI: 10.3390/rs9060568
Abstract:
A method for reducing the impact of noise in the 3.7 micron spectral channel in climate data records derived from coarse resolution (4 km) global meas… A method for reducing the impact of noise in the 3.7 micron spectral channel in climate data records derived from coarse resolution (4 km) global measurements from the Advanced Very High Resolution Radiometer (AVHRR) data is presented. A dynamic size-varying median filter is applied to measurements guided by measured noise levels and scene temperatures for individual AVHRR sensors on historic National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites in the period 1982–2001. The method was used in the preparation of the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data—Second Edition (CLARA-A2), a cloud climate data record produced by the EUMETSAT Satellite Application Facility for Climate Monitoring (CM SAF), as well as in the preparation of the corresponding AVHRR-based datasets produced by the European Space Agency (ESA) Climate Change Initiative (CCI) project ESA-CLOUD-CCI. The impact of the noise filter was equivalent to removing an artificial decreasing trend in global cloud cover of 1–2% per decade in the studied period, mainly explained by the very high noise levels experienced in data from the first satellites in the series (NOAA-7 and NOAA-9). more
Atmosphere CM-SAF Climate Data Records Method

Extensive validation of CM SAF surface radiation products over Europe

Author(s):
Urraca, Ruben; Gracia-Amillo, Ana M.; Koubli, Elena; Huld, Thomas; Trentmann, Jörg; Riihelä, Aku; Lindfors, Anders V.; Palmer, Diane; Gottschalg, Ralph; Antonanzas-Torres, Fernando
Publication title: Remote Sensing of Environment
2017
 | Volume: 199
2017
DOI: 10.1016/j.rse.2017.07.013
Abstract:
This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to … This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8–13 W/m2, whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements. more
Atmosphere CM-SAF Climate Data Records Validation

Estimation methods for global solar radiation: Case study evaluation of five different approaches in central Spain

Author(s):
Urraca, R.; Martinez-de-Pison, E.; Sanz-Garcia, A.; Antonanzas, J.; Antonanzas-Torres, F.
Publication title: Renewable and Sustainable Energy Reviews
2017
 | Volume: 77
2017
DOI: 10.1016/j.rser.2016.11.222
Abstract:
Solar radiation can be estimated by a variety of methods in an attempt to overcome the limitations of on-ground records. Novel methods are often appea… Solar radiation can be estimated by a variety of methods in an attempt to overcome the limitations of on-ground records. Novel methods are often appearing but these are rarely compared to others from a different approach. This study surveys the main types of estimation methods for daily Global Horizontal Irradiation (GHI), and then, one characteristic technique per group is selected, discarding possible hybrid approaches: a parametric model based on temperatures and precipitation (Antonanzas model), a statistical model (XGBoost), interpolated ground-based measurements (Ordinary Kriging (OK)), a satellite-based dataset (CM-SAF-SARAH), and a reanalysis dataset (ERA-Interim). The techniques are evaluated in relation to the seasonal variation, the clearness index and the spatial performance at 38 grounds stations in central Spain from 2001 to 2013. Three different tiers of estimations were obtained being SARAH and OK the best performing methods overall. The SARAH dataset (MAE=1.10±0.13 MJ/m2, MBE=0.22±0.36 MJ/m2) generated estimates with the lowest spread, but led to a slight overestimation in low-altitude flat areas. The OK (MAE=1.10±0.25 MJ/m2, MBE=0.00±0.31 MJ/m2) outperformed SARAH in these flat areas (high density of stations), but at the expense of a higher variability. Alternatively, SARAH surpassed Ordinary Kriging (OK) when the distance to the closest station exceeded 20–30 km. The ERA-Interim reanalysis and the XGBoost were in the second tier of estimations, and the parametric model yielded the worst results overall. ERA-Interim exhibited a systematic overestimation. The locally trained Antonanzas and XGBoost struggled to model the atmospheric transmissivity, showing large positive errors in spring months and a small underestimation of clear-sky days. Finally, a summary with the strengths and weaknesses of the five methods provides a deeper understanding for the selection of the adequate estimation approach. more
Atmosphere CM-SAF Climate Data Records Validation

CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data

Author(s):
Karlsson, Karl-Göran; Anttila, Kati; Trentmann, Jörg; Stengel, Martin; Fokke Meirink, Jan; Devasthale, Abhay; Hanschmann, Timo; Kothe, Steffen; Jääskeläinen, Emmihenna; Sedlar, Joseph; Benas, Nikos; van Zadelhoff, Gerd-Jan; Schlundt, Cornelia; Stein, Diana; Finkensieper, Stefan; Håkansson, Nina; Hollmann, Rainer
Publication title: Atmospheric Chemistry and Physics
2017
 | Volume: 17 | Issue: 9
2017
DOI: 10.5194/acp-17-5809-2017
Abstract:
Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR dat… Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR data – second edition denoted as CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail, as are some major validation results. Some of the main improvements to the data record come from a major effort in cleaning and homogenizing the basic AVHRR level-1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Arctic summer surface albedo and cloud conditions are provided. more
Atmosphere CM-SAF Climate Data Records Land Validation

Characterisation of Special Sensor Microwave Water Vapor Profiler (SSM/T-2) radiances using radiative transfer simulations from global atmospheric reanalyses

Author(s):
Kobayashi, Shinya; Poli, Paul; John, Viju O.
Publication title: Advances in Space Research
2017
 | Volume: 59 | Issue: 4
2017
DOI: 10.1016/j.asr.2016.11.017
Abstract:
The near-global and all-sky coverage of satellite observations from microwave humidity sounders operating in the 183 GHz band complement radiosonde an… The near-global and all-sky coverage of satellite observations from microwave humidity sounders operating in the 183 GHz band complement radiosonde and aircraft observations and satellite infrared clear-sky observations. The Special Sensor Microwave Water Vapor Profiler (SSM/T-2) of the Defense Meteorological Satellite Program began operations late 1991. It has been followed by several other microwave humidity sounders, continuing today. However, expertise and accrued knowledge regarding the SSM/T-2 data record is limited because it has remained underused for climate applications and reanalyses. In this study, SSM/T-2 radiances are characterised using several global atmospheric reanalyses. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), the first ECMWF reanalysis of the 20th-century (ERA-20C), and the Japanese 55-year Reanalysis (JRA-55) are projected into SSM/T-2 radiance space using a fast radiative transfer model. The present study confirms earlier indications that the polarisation state of SSM/T-2 antenna is horizontal (not vertical) in the limit of nadir viewing. The study also formulates several recommendations to improve use of the SSM/T-2 measurement data in future fundamental climate data records or reanalyses. Recommendations are (1) to correct geolocation errors, especially for DMSP 14; (2) to blacklist poor quality data identified in the paper; (3) to correct for inter-satellite biases, estimated here on the order of 1 K, by applying an inter-satellite recalibration or, for reanalysis, an automated (e.g., variational) bias correction; and (4) to improve precipitating cloud filtering or, for reanalysis, consider an all-sky assimilation scheme where radiative transfer simulations account for the scattering effect of hydrometeors. more
Climate Data Records EUM-Secr Method

Assessment of NOAA NUCAPS upper air temperature profiles using COSMIC GPS radio occultation and ARM radiosondes

Author(s):
Feltz, M. L.; Borg, L.; Knuteson, R. O.; Tobin, D.; Revercomb, H.; Gambacorta, A.
Publication title: Journal of Geophysical Research: Atmospheres
2017
 | Volume: 122 | Issue: 17
2017
DOI: 10.1002/2017JD026504
Abstract:
The U.S. National Oceanic and Atmospheric Administration (NOAA) recently began operational processing to derive vertical temperature profiles from two… The U.S. National Oceanic and Atmospheric Administration (NOAA) recently began operational processing to derive vertical temperature profiles from two new sensors, Cross-Track Infrared Sounder and Advanced Technology Microwave Sounder, which were developed for the next generation of U.S. weather satellites. The NOAA-Unique Combined Atmospheric Processing System (NUCAPS) has been developed by NOAA to routinely process data from future Joint Polar Satellite System operational satellites and the preparatory Suomi-NPP satellite. This paper assesses the NUCAPS vertical temperature profile product from the upper troposphere into the middle stratosphere using radiosonde and GPS radio occultation (RO) data. Radiosonde data from the Department of Energy Atmospheric Radiation Measurement (ARM) program are=] compared to both the NUCAPS and GPS RO temperature products to evaluate bias and RMS errors. At all three fixed ARM sites for time periods investigated the NUCAPS temperature in the 100–40 hPa range is found to have an average bias to the radiosondes of less than 0.45 K and an RMS error of less than 1 K when temperature averaging kernels are applied. At a 95% confidence level, the radiosondes and RO were found to agree within 0.4 K at the North Slope of Alaska site and within 0.83 K at Southern Great Plains and Tropical Western Pacific. The GPS RO-derived dry temperatures, obtained from the University Corporation for Atmospheric Research Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission, are used as a common reference for the intercomparison of NUCAPS temperature products to similar products produced by NASA from Atmospheric Infrared Sounder (AIRS) and by European Organisation for the Exploitation of Meteorological Satellites from MetOp-B Infrared Atmospheric Sounding Interferometer (IASI). For seasonal and zonal scales, the NUCAPS agreement with AIRS and IASI is less than 0.5 K after application of averaging kernels. more
Climate Data Records EUM-Secr Validation

Analysis of Radio Frequency Interference in Metop ASCAT Backscatter Measurements

Author(s):
Ticconi, Francesca; Anderson, Craig; Figa-Saldana, Julia; Wilson, John Julian William; Bauch, Helmut
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
 | Volume: 10 | Issue: 5
2017
DOI: 10.1109/JSTARS.2016.2640561
Abstract:
The advanced scatterometer (ASCAT) is a radar system carried on board the ESA/EUMETSAT METOP series of satellites. It is designed for the purpose of r… The advanced scatterometer (ASCAT) is a radar system carried on board the ESA/EUMETSAT METOP series of satellites. It is designed for the purpose of retrieving wind field over oceans. It also provides information on surface soil moisture content and sea ice. Although ASCAT uses a linear frequency modulated pulse with a center frequency of 5.255 GHz (C-band), it is subject to radio frequency interference (RFI). This paper analyses seven years of ASCAT data and shows an increase of the number of noise outliers and an increase of the noise background level over specific land areas. This suggests that the outliers are not a natural occurrence, but are due to RFI from ground-based equipments. As regards the observed increase of the noise background level, it is not straightforward to associate possible RFI sources which could have caused it. However, since the ASCAT has a dynamic range of about 30 dB, the worse measured increase of 1 dB in the noise floor has almost no impact on performance, in particular, on soil moisture retrieval. In addition, the effect of the noise outliers on the estimate of the ASCAT receiver filter shape function used in the processing is also examined and is found to introduce errors of up to 0.4 dB. However, the occurrence of the noise outliers is generally very low, typically two out of 60 000 noise measurements per day, so the impact on the operational use of ASCAT data for wind vector retrieval is limited. more
Climate Data Records EUM-Secr Method

The GOME-2 instrument on the Metop series of satellites: instrument design, calibration, and level 1 data processing – an overview

Author(s):
Munro, Rosemary; Lang, Rüdiger; Klaes, Dieter; Poli, Gabriele; Retscher, Christian; Lindstrot, Rasmus; Huckle, Roger; Lacan, Antoine; Grzegorski, Michael; Holdak, Andriy; Kokhanovsky, Alexander; Livschitz, Jakob; Eisinger, Michael
Publication title: Atmospheric Measurement Techniques
2016
 | Volume: 9 | Issue: 3
2016
DOI: 10.5194/amt-9-1279-2016
Abstract:
Abstract. The Global Ozone Monitoring Experiment-2 (GOME-2) flies on the Metop series of satellites, the space component of the EUMETSAT Polar System.… Abstract. The Global Ozone Monitoring Experiment-2 (GOME-2) flies on the Metop series of satellites, the space component of the EUMETSAT Polar System. In this paper we will provide an overview of the instrument design, the on-ground calibration and characterization activities, in-flight calibration, and level 0 to 1 data processing. The current status of the level 1 data is presented and points of specific relevance to users are highlighted. Long-term level 1 data consistency is also discussed and plans for future work are outlined. The information contained in this paper summarizes a large number of technical reports and related documents containing information that is not currently available in the published literature. These reports and documents are however made available on the EUMETSAT web pages and readers requiring more details than can be provided in this overview paper will find appropriate references at relevant points in the text. more
Climate Data Records EUM-Secr Method

The EUMETSAT sea ice concentration climate data record

Author(s):
Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Pedersen, Leif Toudal; Høyer, Jacob L.; Kern, Stefan
Publication title: The Cryosphere
2016
 | Volume: 10 | Issue: 5
2016
DOI: 10.5194/tc-10-2275-2016
Abstract:
Abstract. An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (O… Abstract. An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation. more
Climate Data Records Cryosphere Method OSI-SAF Validation

State of the Climate in 2015

Author(s):
Blunden, Jessica; Arndt, Derek S.
Publication title: Bulletin of the American Meteorological Society
2016
 | Volume: 97 | Issue: 8
2016
DOI: 10.1175/2016BAMSStateoftheClimate.1
Abstract:
Editor’s note: For easy download the posted pdf of the State of the Climate for 2016 is a very low-resolution file. A high-resolution copy of the repo… Editor’s note: For easy download the posted pdf of the State of the Climate for 2016 is a very low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Satellite Climate Data Records: Development, Applications, and Societal Benefits

Author(s):
Yang, Wenze; John, Viju; Zhao, Xuepeng; Lu, Hui; Knapp, Kenneth
Publication title: Remote Sensing
2016
 | Volume: 8 | Issue: 4
2016
DOI: 10.3390/rs8040331
Abstract:
This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs) in the context of transitioning research… This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs) in the context of transitioning research to operation (R2O). Requirements and critical procedures of producing various CDRs, including Fundamental CDRs (FCDRs), Thematic CDRs (TCDRs), Interim CDRs (ICDRs), and climate information records (CIRs) are discussed in detail, including radiance/reflectance and the essential climate variables (ECVs) of land, ocean, and atmosphere. Major international CDR initiatives, programs, and projects are summarized. Societal benefits of CDRs in various user sectors, including Agriculture, Forestry, Fisheries, Energy, Heath, Water, Transportation, and Tourism are also briefly discussed. The challenges and opportunities for CDR development, production and service are also addressed. It is essential to maintain credible CDR products by allowing free access to products and keeping the production process transparent by making source code and documentation available with the dataset. more
Application EUM-Secr International cooperation Validation

Identification and intercomparison of surface-based inversions over Antarctica from IASI, ERA-Interim, and Concordiasi dropsonde data: Surface-Based Inversions Over Antarctica

Author(s):
Boylan, Patrick; Wang, Junhong; Cohn, Stephen A.; Hultberg, Tim; August, Thomas
Publication title: Journal of Geophysical Research: Atmospheres
2016
 | Volume: 121 | Issue: 15
2016
DOI: 10.1002/2015JD024724
Abstract:
Surface-based temperature inversions (SBIs) occur frequently over Antarctica and play an important role in climate and weather. Antarctic SBIs are exa… Surface-based temperature inversions (SBIs) occur frequently over Antarctica and play an important role in climate and weather. Antarctic SBIs are examined during the austral spring of 2010 using measurements from dropsondes, ERA-Interim Atmospheric Reanalysis Model, and the recently released version 6 of the Infrared Atmospheric Sounding Interferometer (IASI) level 2 product. A SBI detection algorithm is applied to temperature profiles from these data sets. The results will be used to determine if satellite and reanalysis products can accurately characterize SBIs, and if so, then they may be used to study SBIs outside of the spring 2010 study period. From the dropsonde data, SBIs occur in 20% of profiles over sea ice and 54% of profiles over land. IASI and ERA-Interim surface air temperatures are found to be significantly warmer than dropsonde observations at high plateau regions, while IASI surface air temperatures are colder over sea ice. IASI and ERA-Interim have a cold bias at nearly all levels above the surface when compared to the dropsonde. SBIs are characterized by their frequency, depth, and intensity. It is found that SBIs are more prevalent, deeper, and more intense over the continent than over sea ice, especially at higher surface elevations. Using IASI and ERA-Interim data the detection algorithm has a high probability of detection of SBIs but is found to severely overestimate the depth and underestimate the intensity for both data sets. These overestimation and underestimation are primarily due to the existence of extremely shallow inversion layers that neither satellite nor reanalysis products can resolve. more
Climate Data Records EUM-Secr Validation

HOAPS and ERA-Interim precipitation over the sea: validation against shipboard in situ measurements

Author(s):
Bumke, Karl; König-Langlo, Gert; Kinzel, Julian; Schröder, Marc
Publication title: Atmospheric Measurement Techniques
2016
 | Volume: 9 | Issue: 5
2016
DOI: 10.5194/amt-9-2409-2016
Abstract:
Abstract. The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) and ECMWF (European Centre for Medium-Range… Abstract. The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) and ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis data sets have been validated against in situ precipitation measurements from ship rain gauges and optical disdrometers over the open ocean by applying a statistical analysis for binary estimates. For this purpose collocated pairs of data were merged within a certain temporal and spatial threshold into single events, according to the satellites' overpass, the observation and the ERA-Interim times. HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially in the tropics and subtropics. Although precipitation rates are difficult to compare because along-track point measurements are collocated with areal estimates and the number of available data are limited, we find that HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide average precipitation rate is close to measurements. However, when regionally averaged over latitudinal belts, deviations between the observed mean precipitation rates and ERA-Interim exist. The most obvious ERA-Interim feature is an overestimation of precipitation in the area of the intertropical convergence zone and the southern subtropics over the Atlantic Ocean. For a limited number of snow measurements by optical disdrometers, it can be concluded that both HOAPS and ERA-Interim are suitable for detecting the occurrence of solid precipitation. more
Atmosphere CM-SAF Climate Data Records Validation

Creating Fidelitous Climate Data Records from Meteosat First Generation Observations

Author(s):
Quast, Ralf; Govaerts, Yves; Rüthrich, Frank; Giering, Ralf; Roebeling, Rob
2016
2016
DOI: 10.6084/M9.FIGSHARE.3412201.V1
Abstract:
Essay on the reconstruction of the Meteosat VIS band spectral response function in the course of the FIDUCEO project. Conference paper contributed to … Essay on the reconstruction of the Meteosat VIS band spectral response function in the course of the FIDUCEO project. Conference paper contributed to the ESA Living Planet Symposium, Prague, May 2016:\textlessbr\textgreaterPaper 1442 - Session title: Atmosphere &amp; Climate Posters\textlessstrong\textgreaterATMO-178 - Creating Fidelitous Climate Data Records from Meteosat First Generation VIS Band Observations\textless/strong\textgreater more
Climate Data Records EUM-Secr Method

An assessment of the consistency between satellite measurements of upper tropospheric water vapor: Upper Tropospheric Water Vapor

Author(s):
Chung, Eui-Seok; Soden, Brian J.; Huang, Xianglei; Shi, Lei; John, Viju O.
Publication title: Journal of Geophysical Research: Atmospheres
2016
 | Volume: 121 | Issue: 6
2016
DOI: 10.1002/2015JD024496
Abstract:
We assess the consistency of the satellite-based observations of upper tropospheric water vapor (UTWV) by comparing brightness temperature measurement… We assess the consistency of the satellite-based observations of upper tropospheric water vapor (UTWV) by comparing brightness temperature measurements from the channel 12 of High-Resolution Infrared Radiation Sounder (HIRS), the 183.31 ± 1 GHz channel of Advanced Microwave Sounding Unit-B (AMSU-B)/Microwave Humidity Sounder (MHS), and spectral radiances from the Atmospheric Infrared Sounder (AIRS). All three products exhibit consistent spatial and temporal patterns of interannual variability. On decadal time scales, the spatial patterns of trends are similar between all three products; however, the amplitude of the regional trends is noticeably weaker in the HIRS measurements than in either the AMSU-B/MHS or AIRS data. This presumably reflects the greater clear-sky sampling limitations of HIRS relative to the other products. However, when averaged over tropical or near-global spatial scales, the trends between all three products are statistically indistinguishable from each other. The overall consistency between all three products provides important verification of their credibility for documenting long-term changes in UTWV. A similar analysis is performed for reanalysis-produced and model-simulated UTWV using the HIRS record as a benchmark. On decadal time scales, both reanalysis data sets and the multimodel ensemble mean have difficulty in capturing the observed moistening of climatologically dry regions of the subtropics, although the model-simulated trends are more consistent with the HIRS measurements than the reanalysis data. more
Application Climate Data Records EUM-Secr

A database of global reference sites to support validation of satellite surface albedo datasets (SAVS 1.0)

Author(s):
Loew, Alexander; Bennartz, Ralf; Fell, Frank; Lattanzio, Alessio; Doutriaux-Boucher, Marie; Schulz, Jörg
Publication title: Earth System Science Data
2016
 | Volume: 8 | Issue: 2
2016
DOI: 10.5194/essd-8-425-2016
Abstract:
Abstract. Validating the accuracy and long-term stability of terrestrial satellite data products necessitates a network of reference sites. This paper… Abstract. Validating the accuracy and long-term stability of terrestrial satellite data products necessitates a network of reference sites. This paper documents a global database of more than 2000 sites globally which have been characterized in terms of their spatial heterogeneity. The work was motivated by the need for potential validation sites for geostationary surface albedo data products, but the resulting database is useful also for other applications. The database (SAVS 1.0) is publicly available through the EUMETSAT website (http://savs.eumetsat.int/, doi:10.15770/EUM_SEC_CLM_1001). Sites can be filtered according to different criteria, providing a flexible way to identify potential validation sites for further studies and a traceable approach to characterize the heterogeneity of these reference sites. The present paper describes the detailed information on the generation of the SAVS 1.0 database and its characteristics. more
Climate Data Records EUM-Secr Land Validation

Validation of CM SAF Surface Solar Radiation Datasets over Finland and Sweden

Author(s):
Riihelä, Aku; Carlund, Thomas; Trentmann, Jörg; Müller, Richard; Lindfors, Anders
Publication title: Remote Sensing
2015
 | Volume: 7 | Issue: 6
2015
DOI: 10.3390/rs70606663
Abstract:
Accurate determination of the amount of incoming solar radiation at Earth’s surface is important for both climate studies and solar power applications… Accurate determination of the amount of incoming solar radiation at Earth’s surface is important for both climate studies and solar power applications. Satellite-based datasets of solar radiation offer wide spatial and temporal coverage, but careful validation of their quality is a necessary prerequisite for reliable utilization. Here we study the retrieval quality of one polar-orbiting satellite-based dataset (CLARA-A1) and one geostationary satellite-based dataset (SARAH), using in situ observations of solar radiation from the Finnish and Swedish meteorological measurement networks as reference. Our focus is on determining dataset quality over high latitudes as well as evaluating daily mean retrievals, both of which are aspects that have drawn little focus in previous studies. We find that both datasets are generally capable of retrieving the levels and seasonal cycles of solar radiation in Finland and Sweden well, with some limitations. SARAH exhibits a slight negative bias and increased retrieval uncertainty near the coverage edge, but in turn offers better precision (less scatter) in the daily mean retrievals owing to the high sampling rate of geostationary imaging. more
Atmosphere CM-SAF Climate Data Records Validation

Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

Author(s):
Grossi, M.; Valks, P.; Loyola, D.; Aberle, B.; Slijkhuis, S.; Wagner, T.; Beirle, S.; Lang, R.
Publication title: Atmospheric Measurement Techniques
2015
 | Volume: 8 | Issue: 3
2015
DOI: 10.5194/amt-8-1111-2015
Abstract:
Abstract. Knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this wo… Abstract. Knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors aboard EUMETSAT's MetOp-A and MetOp-B satellites and perform an extensive inter-comparison in order to evaluate their consistency and temporal stability. For the analysis, the GOME-2 data sets are generated by DLR in the framework of the EUMETSAT O3M-SAF project using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines a H2O and O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O total column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. The overall consistency between measurements from the newer GOME-2 instrument on board of the MetOp-B platform and the GOME-2/MetOp-A data is evaluated in the overlap period (December 2012–June 2014). Furthermore, we compare GOME-2 results with independent TCWV data from the ECMWF ERA-Interim reanalysis, with SSMIS satellite measurements during the full period January 2007–June 2014 and against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project (January 2007–December 2008). Global mean biases as small as ±0.035 g cm−2 are found between GOME-2A and all other data sets. The combined SSM/I-MERIS sample and the ECMWF ERA-Interim data set are typically drier than the GOME-2 retrievals, while on average GOME-2 data overestimate the SSMIS measurements by only 0.006 g cm−2. However, the size of these biases is seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, which include only data over ocean. The seasonal behaviour is not as evident when comparing GOME-2 TCWV to the ECMWF ERA-Interim and the SSM/I+MERIS data sets, since the different biases over land and ocean surfaces partly compensate each other. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three data sets, especially for land areas, although some discrepancies (bias larger than ±0.5 g cm−2) over ocean and over land areas with high humidity or a relatively large surface albedo are observed. more
AC-SAF Atmosphere Climate Data Records Validation

The CM SAF ATOVS tropospheric water vapour and temperature data record: overview of methodology and evaluation

Author(s):
Courcoux, N.; Schröder, M.
Publication title: Earth System Science Data Discussions
2015
 | Volume: 8 | Issue: 1
2015
DOI: 10.5194/essdd-8-127-2015
Abstract:
Abstract. Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric wat… Abstract. Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric water vapour and temperature data record has been released by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring (CM SAF). ATOVS observations from the National Oceanic and Atmospheric Agency (NOAA)-15 through NOAA-19 and EUMETSAT's Meteorological operational (Metop-A) satellites have been consistently reprocessed to generate 13 years (1999–2011) of global water vapour and temperature daily and monthly means with a spatial resolution of 90 km × 90 km. After pre-processing, an optimal estimation scheme has been applied to the observations to simultaneously infer temperature and water vapour profiles. In a post-processing step an objective interpolation method (Kriging) has been applied to allow for gap filling. The product suite includes total precipitable water vapour (TPW), layer integrated water vapour (LPW) and layer mean temperature for five tropospheric layers, as well as specific humidity and temperature at six tropospheric levels and is referenced under doi:10.5676/EUM_SAF_CM/WVT_ATOVS/V001. To our knowledge this is the first time that the ATOVS record (1998–now) has been consistently reprocessed (1999–2011) to retrieve water vapour and temperature products. TPW and LPW products were compared to corresponding products from the Global Climate Observing System (GCOS) Upper-Air Network (GUAN) radiosonde observations and from the Atmospheric InfraRed Sounder (AIRS) version 5 satellite data record. The TPW shows a good agreement with the GUAN radiosonde data: average bias and root mean square error (RMSE) are −0.2 and 3.3 kg m−2, respectively. The maximum absolute (relative) bias and RMSE values decrease (increase) strongly with height. While the RMSE relative to AIRS is generally smaller, the TPW bias relative to AIRS is larger with dominant contributions from precipitating areas. The consistently reprocessed ATOVS data record exhibits an improved quality and an improved stability relative to the operational CM SAF ATOVS products when compared to the TPW from GUAN radiosonde data over the period 2004–2011. Finally, it became evident that the change in the number of satellites used for the retrieval combined with the use of the Kriging leads to breakpoints in the ATOVS data record so that a variability analysis of the data record is not recommended for the time period from January 1999 to January 2001. more
Atmosphere CM-SAF Climate Data Records Validation

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

Author(s):
Courcoux, N.; Schröder, M.
Publication title: Earth System Science Data
2015
 | Volume: 7 | Issue: 2
2015
DOI: 10.5194/essd-7-397-2015
Abstract:
Abstract. Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric wat… Abstract. Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric water vapour and temperature data record was released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM~SAF). ATOVS observations from infrared and microwave sounders onboard the National Oceanic and Atmospheric Agency (NOAA)-15–19 satellites and EUMETSAT's Meteorological Operational (Metop-A) satellite have been consistently reprocessed to generate 13 years (1999–2011) of global water vapour and temperature daily and monthly means with a spatial resolution of 90 km × 90 km. The data set is referenced under the following digital object identifier (DOI): doi:10.5676/EUM_SAF_CM/WVT_ATOVS/V001. After preprocessing, a maximum likelihood solution scheme was applied to the observations to simultaneously infer temperature and water vapour profiles. In a post-processing step, an objective interpolation method (Kriging) was applied to allow for gap filling. The product suite includes total precipitable water vapour (TPW), layer-integrated precipitable water vapour (LPW) and layer mean temperature for five tropospheric layers between the surface and 200 hPa, as well as specific humidity and temperature at six tropospheric levels between 1000 and 200 hPa. To our knowledge, this is the first time that the ATOVS record (1998–now) has been consistently reprocessed (1999–2011) to retrieve water vapour. TPW and LPW products were compared to corresponding products from the Global Climate Observing System (GCOS) Upper-Air Network (GUAN) radiosonde observations and from the Atmospheric Infrared Sounder (AIRS) version 5 satellite data record. TPW shows a good agreement with the GUAN radiosonde data: average bias and root mean square error (RMSE) are −0.2 and 3.3 kg m−2, respectively. For LPW, the maximum absolute (relative) bias and RMSE values decrease (increase) strongly with height. The maximum bias and RMSE are found at the lowest layer and are −0.7 and 2.5 kg m−2, respectively. While the RMSE relative to AIRS is generally smaller, the TPW bias relative to AIRS is larger, with dominant contributions from precipitating areas. The consistently reprocessed ATOVS data record exhibits improved quality and stability relative to the operational CM SAF products when compared to the TPW from GUAN radiosonde data over the period 2004–2011. Finally, it became evident that the change in the number of satellites used for the retrieval combined with the use of the Kriging leads to breakpoints in the ATOVS data record; therefore, a variability analysis of the data record is not recommended for the time period from January 1999 to January 2001. more
Atmosphere CM-SAF Climate Data Records Method

State of the Climate in 2014

Author(s):
Blunden, Jessica; Arndt, Derek S.
Publication title: Bulletin of the American Meteorological Society
2015
 | Volume: 96 | Issue: 7
2015
DOI: 10.1175/2015BAMSStateoftheClimate.1
Abstract:
Editors note: For easy download the posted pdf of the State of the Climate for 2014 is a very low-resolution file. A high-resolution copy of the repor… Editors note: For easy download the posted pdf of the State of the Climate for 2014 is a very low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download. more
Application Atmosphere Climate Data Records Cryosphere EUM-Secr International cooperation Land Ocean

Quality assessment and improvement of the EUMETSAT Meteosat Surface Albedo Climate Data Record

Author(s):
Lattanzio, A.; Fell, F.; Bennartz, R.; Trigo, I. F.; Schulz, J.
Publication title: Atmospheric Measurement Techniques
2015
 | Volume: 8 | Issue: 10
2015
DOI: 10.5194/amt-8-4561-2015
Abstract:
Abstract. Surface albedo has been identified as an important parameter for understanding and quantifying the Earth's radiation budget. EUMETSAT genera… Abstract. Surface albedo has been identified as an important parameter for understanding and quantifying the Earth's radiation budget. EUMETSAT generated the Meteosat Surface Albedo (MSA) Climate Data Record (CDR) currently comprising up to 24 years (1982–2006) of continuous surface albedo coverage for large areas of the Earth. This CDR has been created within the Sustained, Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) framework. The long-term consistency of the MSA CDR is high and meets the Global Climate Observing System (GCOS) stability requirements for desert reference sites. The limitation in quality due to non-removed clouds by the embedded cloud screening procedure is the most relevant weakness in the retrieval process. A twofold strategy is applied to efficiently improve the cloud detection and removal. The first step consists of the application of a robust and reliable cloud mask, taking advantage of the information contained in the measurements of the infrared and visible bands. Due to the limited information available from old radiometers, some clouds can still remain undetected. A second step relies on a post-processing analysis of the albedo seasonal variation together with the usage of a background albedo map in order to detect and screen out such outliers. The usage of a reliable cloud mask has a double effect. It enhances the number of high-quality retrievals for tropical forest areas sensed under low view angles and removes the most frequently unrealistic retrievals on similar surfaces sensed under high view angles. As expected, the usage of a cloud mask has a negligible impact on desert areas where clear conditions dominate. The exploitation of the albedo seasonal variation for cloud removal has good potentialities but it needs to be carefully addressed. Nevertheless it is shown that the inclusion of cloud masking and removal strategy is a key point for the generation of the next MSA CDR release. more
Climate Data Records EUM-Secr Land Validation

LSA SAF Meteosat FRP products – Part 1: Algorithms, product contents, and analysis

Author(s):
Wooster, M. J.; Roberts, G.; Freeborn, P. H.; Xu, W.; Govaerts, Y.; Beeby, R.; He, J.; Lattanzio, A.; Fisher, D.; Mullen, R.
Publication title: Atmospheric Chemistry and Physics
2015
 | Volume: 15 | Issue: 22
2015
DOI: 10.5194/acp-15-13217-2015
Abstract:
Abstract. Characterizing changes in landscape fire activity at better than hourly temporal resolution is achievable using thermal observations of acti… Abstract. Characterizing changes in landscape fire activity at better than hourly temporal resolution is achievable using thermal observations of actively burning fires made from geostationary Earth Observation (EO) satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from geostationary EO data, often with the aim of supporting biomass burning fuel consumption and trace gas and aerosol emission calculations. Such Fire Radiative Power (FRP) products are generated operationally from Meteosat by the Land Surface Analysis Satellite Applications Facility (LSA SAF) and are available freely every 15 min in both near-real-time and archived form. These products map the location of actively burning fires and characterize their rates of thermal radiative energy release (FRP), which is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the full spatio-temporal resolution FRP data set derivable from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) imager onboard Meteosat at a 3 km spatial sampling distance (decreasing away from the west African sub-satellite point), whilst the FRP-GRID product is an hourly summary at 5° grid resolution that includes simple bias adjustments for meteorological cloud cover and regional underestimation of FRP caused primarily by underdetection of low FRP fires. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA) detection algorithm used to deliver these products and detail the methods used to generate the atmospherically corrected FRP and per-pixel uncertainty metrics. Using SEVIRI scene simulations and real SEVIRI data, including from a period of Meteosat-8 "special operations", we describe certain sensor and data pre-processing characteristics that influence SEVIRI's active fire detection and FRP measurement capability, and use these to specify parameters in the FTA algorithm and to make recommendations for the forthcoming Meteosat Third Generation operations in relation to active fire measures. We show that the current SEVIRI FTA algorithm is able to discriminate actively burning fires covering down to 10−4 of a pixel and that it appears more sensitive to fire than other algorithms used to generate many widely exploited active fire products. Finally, we briefly illustrate the information contained within the current Meteosat FRP-PIXEL and FRP-GRID products, providing example analyses for both individual fires and multi-year regional-scale fire activity; the companion paper (Roberts et al., 2015) provides a full product performance evaluation and a demonstration of product use within components of the Copernicus Atmosphere Monitoring Service (CAMS). more
Climate Data Records LSA-SAF Land Method

LSA SAF Meteosat FRP products – Part 2: Evaluation and demonstration for use in the Copernicus Atmosphere Monitoring Service (CAMS)

Author(s):
Roberts, G.; Wooster, M. J.; Xu, W.; Freeborn, P. H.; Morcrette, J.-J.; Jones, L.; Benedetti, A.; Jiangping, H.; Fisher, D.; Kaiser, J. W.
Publication title: Atmospheric Chemistry and Physics
2015
 | Volume: 15 | Issue: 22
2015
DOI: 10.5194/acp-15-13241-2015
Abstract:
Characterising the dynamics of landscape-scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation … Characterising the dynamics of landscape-scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation (EO) sensors mounted onboard geostationary satellites. As a result, a number of operational active fire products have been developed from the data of such sensors. An example of which are the Fire Radiative Power (FRP) products, the FRP-PIXEL and FRP-GRID products, generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from imagery collected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) series of geostationary EO satellites. The processing chain developed to deliver these FRP products detects SEVIRI pixels containing actively burning fires and characterises their FRP output across four geographic regions covering Europe, part of South America and Northern and Southern Africa. The FRP-PIXEL product contains the highest spatial and temporal resolution FRP data set, whilst the FRP-GRID product contains a spatio-temporal summary that includes bias adjustments for cloud cover and the non-detection of low FRP fire pixels. Here we evaluate these two products against active fire data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and compare the results to those for three alternative active fire products derived from SEVIRI imagery. The FRP-PIXEL product is shown to detect a substantially greater number of active fire pixels than do alternative SEVIRI-based products, and comparison to MODIS on a per-fire basis indicates a strong agreement and low bias in terms of FRP values. However, low FRP fire pixels remain undetected by SEVIRI, with errors of active fire pixel detection commission and omission compared to MODIS ranging between 9–13 % and 65–77 % respectively in Africa. Higher errors of omission result in greater underestimation of regional FRP totals relative to those derived from simultaneously collected MODIS data, ranging from 35 % over the Northern Africa region to 89 % over the European region. High errors of active fire omission and FRP underestimation are found over Europe and South America and result from SEVIRI's larger pixel area over these regions. An advantage of using FRP for characterising wildfire emissions is the ability to do so very frequently and in near-real time (NRT). To illustrate the potential of this approach, wildfire fuel consumption rates derived from the SEVIRI FRP-PIXEL product are used to characterise smoke emissions of the 2007 "mega-fire" event focused on Peloponnese (Greece) and used within the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS) as a demonstration of what can be achieved when using geostationary active fire data within the Copernicus Atmosphere Monitoring Service (CAMS). Qualitative comparison of the modelled smoke plumes with MODIS optical imagery illustrates that the model captures the temporal and spatial dynamics of the plume very well, and that high temporal resolution emissions estimates such as those available from a geostationary orbit are important for capturing the sub-daily variability in smoke plume parameters such as aerosol optical depth (AOD), which are increasingly less well resolved using daily or coarser temporal resolution emissions data sets. Quantitative comparison of modelled AOD with coincident MODIS and AERONET (Aerosol Robotic Network) AOD indicates that the former is overestimated by ~ 20–30 %, but captures the observed AOD dynamics with a high degree of fidelity. The case study highlights the potential of using geostationary FRP data to drive fire emissions estimates for use within atmospheric transport models such as those implemented in the Monitoring Atmospheric Composition and Climate (MACC) series of projects for the CAMS. more
Climate Data Records LSA-SAF Land Validation

Analysis of current validation practices in Europe for space-based climate data records of essential climate variables

Author(s):
Zeng, Y.; Su, Z.; Calvet, J.-C.; Manninen, T.; Swinnen, E.; Schulz, J.; Roebeling, R.; Poli, P.; Tan, D.; Riihelä, A.; Tanis, C.-M.; Arslan, A.-N.; Obregon, A.; Kaiser-Weiss, A.; John, V.O.; Timmermans, W.; Timmermans, J.; Kaspar, F.; Gregow, H.; Barbu, A.-L.; Fairbairn, D.; Gelati, E.; Meurey, C.
Publication title: International Journal of Applied Earth Observation and Geoinformation
2015
 | Volume: 42
2015
DOI: 10.1016/j.jag.2015.06.006
Abstract:
The Climate Data Records (CDRs) of Essential Climate Variables (ECVs) that are based on satellite observations need to be precisely described. In part… The Climate Data Records (CDRs) of Essential Climate Variables (ECVs) that are based on satellite observations need to be precisely described. In particular, when these products are delivered to end-users, the error characteristics information and how this information is obtained (e.g., through a validation process) need to be documented. Such validation information is intended to help end-users understanding to what extent the product is suitable for their specific applications. Based on how different European initiatives approached the validation of CDR and ECV products, we reviewed several aspects of the current validation practices. Based on the analysis of current practices, essentials of validation are discussed. A generic validation process is subsequently proposed, together with a quality indicator. more
EUM-Secr International cooperation Validation

Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

Author(s):
Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; Le Gléau, H.; Lockhoff, M.; Lutz, H.-J.; Meirink, J. F.; Minnis, P.; Palikonda, R.; Roebeling, R.; Thoss, A.; Platnick, S.; Watts, P.; Wind, G.
Publication title: Atmospheric Measurement Techniques
2014
 | Volume: 7 | Issue: 9
2014
DOI: 10.5194/amt-7-2839-2014
Abstract:
Abstract. The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth… Abstract. The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 km to 0.6 km. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed. more
Atmosphere CM-SAF Climate Data Records Validation

Extraction des vecteurs vents à partir d'images satellite

Author(s):
Borde, Régis; Doutriaux-Boucher, Marie
Publication title: La Météorologie
2014
 | Volume: 8 | Issue: 87
2014
DOI: 10.4267/2042/54333
Abstract:
Les vecteurs vents extraits à partir des images satellite sont utilisés quotidiennement dans les modèles de prévision numérique du temps afin d'amélio… Les vecteurs vents extraits à partir des images satellite sont utilisés quotidiennement dans les modèles de prévision numérique du temps afin d'améliorer la qualité des prévisions météorologiques. Ils constituent en fait la seule observation du déplacement des masses d'air disponible aux hautes latitudes et au-dessus des océans. Cet article présente une vue d'ensemble de l'extraction des vecteurs vents à partir des images satellite à Eumetsat. La première partie décrit l'algorithme utilisé pour extraire des vents à partir des satellites géostationnaires Météosat, la seconde partie décrit l'extraction de ces vecteurs vents à partir des satellites polaires en orbite basse. more
Climate Data Records EUM-Secr Method

Comparison of profile total ozone from SBUV (v8.6) with GOME-type and ground-based total ozone for a 16-year period (1996 to 2011)

Author(s):
Chiou, E. W.; Bhartia, P. K.; McPeters, R. D.; Loyola, D. G.; Coldewey-Egbers, M.; Fioletov, V. E.; Van Roozendael, M.; Spurr, R.; Lerot, C.; Frith, S. M.
Publication title: Atmospheric Measurement Techniques
2014
 | Volume: 7 | Issue: 6
2014
DOI: 10.5194/amt-7-1681-2014
Abstract:
Abstract. This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, na… Abstract. This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile total ozone, (ii) GTO (GOME-type total ozone), and (iii) ground-based total ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0–30° S, 0–30° N, 50–30° S, and 30–60° N. It has been found that, on average, the differences in monthly zonal mean total ozone vary between −0.3 and 0.8 % and are well within 1%. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean total ozone vary between 0.6–0.7% and 2.8–3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4–0.6% and 2.2–3.5%. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4–2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between −0.04 and 0.1% yr−1 (−0.1 and 0.3 DU yr−1). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multi-year total ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30–60° N from −5% in 1996 to −2% in 2010. In contrast, at 50–30° S and 30° S–30° N there has been a levelling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1%, but a slight increase has been found in the differences during the period 1996–2010. more
AC-SAF Atmosphere Climate Data Records Validation

Comparison of decadal global water vapor changes derived from independent satellite time series

Author(s):
Mieruch, S.; Schröder, M.; Noël, S.; Schulz, J.
Publication title: Journal of Geophysical Research: Atmospheres
2014
 | Volume: 119 | Issue: 22
2014
DOI: 10.1002/2014JD021588
Abstract:
We analyze trends in total column water vapor (TCWV) retrieved from independent satellite observations and retrieval schemes. GOME-SCIAMACHY (Global O… We analyze trends in total column water vapor (TCWV) retrieved from independent satellite observations and retrieval schemes. GOME-SCIAMACHY (Global Ozone Monitoring Experiment-SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) measurements are carried out in the visible part of the solar spectrum and present a partly cloud-corrected climatology that is available over land and ocean. The HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) product, provided by EUMETSAT's Satellite Application Facility on Climate Monitoring is based on passive microwave observations from the Special Sensor Microwave/Imager. It also includes the TCWV from cloudy pixels but is only available over oceans. The common observation time period is between 1996 and 2005. Due to the relatively short length of the period, the strong interannual variability with strong contributions from El Niño and La Niña events and the strong anomaly at the start of the common period, caused by the 1997/1998 El Niño, the observed trends should not be interpreted as long-term climate trends. After subtraction of average seasonality from monthly gridded data, a linear model and a level shift model have been fitted to the HOAPS and GOME-SCIAMACHY data, respectively. Autocorrelation and cross correlation of fit residuals are accounted for in assessing uncertainties in trends. The trends observed in both time series agree within uncertainty margins. This agreement holds true for spatial patterns, magnitudes, and global averages. The consistency increases confidence in the reliability of the trends because the methods, spectral range, and observation technique as well as the satellites and their orbits are completely independent of each other. The similarity of the trends in both data sets is an indication of sufficient stability in the observations for the time period of ≈ 10 years. more
Atmosphere CM-SAF Climate Data Records Validation

CLAAS: the CM SAF cloud property data set using SEVIRI

Author(s):
Stengel, M.; Kniffka, A.; Meirink, J. F.; Lockhoff, M.; Tan, J.; Hollmann, R.
Publication title: Atmospheric Chemistry and Physics
2014
 | Volume: 14 | Issue: 8
2014
DOI: 10.5194/acp-14-4297-2014
Abstract:
Abstract. An 8-year record of satellite-based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived withi… Abstract. An 8-year record of satellite-based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived within the EUMETSAT Satellite Application Facility on Climate Monitoring. The data set is based on SEVIRI measurements of the Meteosat Second Generation satellites, of which the visible and near-infrared channels were intercalibrated with MODIS. Applying two state-of-the-art retrieval schemes ensures high accuracy in cloud detection, cloud vertical placement and microphysical cloud properties. These properties were further processed to provide daily to monthly averaged quantities, mean diurnal cycles and monthly histograms. In particular, the per-month histogram information enhances the insight in spatio-temporal variability of clouds and their properties. Due to the underlying intercalibrated measurement record, the stability of the derived cloud properties is ensured, which is exemplarily demonstrated for three selected cloud variables for the entire SEVIRI disc and a European subregion. All data products and processing levels are introduced and validation results indicated. The sampling uncertainty of the averaged products in CLAAS is minimized due to the high temporal resolution of SEVIRI. This is emphasized by studying the impact of reduced temporal sampling rates taken at typical overpass times of polar-orbiting instruments. In particular, cloud optical thickness and cloud water path are very sensitive to the sampling rate, which in our study amounted to systematic deviations of over 10% if only sampled once a day. The CLAAS data set facilitates many cloud related applications at small spatial scales of a few kilometres and short temporal scales of a~few hours. Beyond this, the spatiotemporal characteristics of clouds on diurnal to seasonal, but also on multi-annual scales, can be studied. more
Atmosphere CM-SAF Climate Data Records Validation

A New Database of Global and Direct Solar Radiation Using the Eastern Meteosat Satellite, Models and Validation

Author(s):
Amillo, Ana; Huld, Thomas; Müller, Richard
Publication title: Remote Sensing
2014
 | Volume: 6 | Issue: 9
2014
DOI: 10.3390/rs6098165
Abstract:
We present a new database of solar radiation at ground level for Eastern Europe and Africa, the Middle East and Asia, estimated using satellite images… We present a new database of solar radiation at ground level for Eastern Europe and Africa, the Middle East and Asia, estimated using satellite images from the Meteosat East geostationary satellites. The method presented calculates global horizontal (G) and direct normal irradiance (DNI) at hourly intervals, using the full Meteosat archive from 1998 to present. Validation of the estimated global horizontal and direct normal irradiance values has been performed by comparison with high-quality ground station measurements. Due to the low number of ground measurements in the viewing area of the Meteosat Eastern satellites, the validation of the calculation method has been extended by a comparison of the estimated values derived from the same class of satellites but positioned at 0°E, where more ground stations are available. Results show a low overall mean bias deviation (MBD) of +1.63 Wm−2 or +0.73% for global horizontal irradiance. The mean absolute bias of the individual station MBD is 2.36%, while the root mean square deviation of the individual MBD values is 3.18%. For direct normal irradiance the corresponding values are overall MBD of +0.61 Wm−2 or +0.62%, while the mean absolute bias of the individual station MBD is 5.03% and the root mean square deviation of the individual MBD values is 6.30%. The resulting database of hourly solar radiation values will be made freely available. These data will also be integrated into the PVGIS web application to allow users to estimate the energy output of photovoltaic (PV) systems not only in Europe and Africa, but now also in Asia. more
Application Atmosphere CM-SAF Climate Data Records

Validation and stability assessment of the monthly mean CM SAF surface solar radiation dataset over Europe against a homogenized surface dataset (1983–2005)

Author(s):
Sanchez-Lorenzo, A.; Wild, M.; Trentmann, J.
Publication title: Remote Sensing of Environment
2013
 | Volume: 134
2013
DOI: 10.1016/j.rse.2013.03.012
Abstract:
This work presents a validation of the downwelling surface shortwave radiation, or surface solar radiation (SSR), derived from the Satellite Applicati… This work presents a validation of the downwelling surface shortwave radiation, or surface solar radiation (SSR), derived from the Satellite Application Facility on Climate Monitoring (CM SAF) over Europe for a 23-year period of records on a monthly basis. This SSR product has been recently derived based on the visible channel of the Meteosat First Generation satellites, providing a dataset with a high spatial resolution (0.03° × 0.03°) covering the 1983–2005 period. The CM SAF SSR product is compared against a homogeneous dataset of surface observations from the Global Energy Balance Archive (GEBA) over Europe, which has been homogenized by means of the Standard Normal Homogeneity Test (SNHT). The results show a good agreement between both datasets (r2 = 0.86, p < 0.01), with a slight overestimation (bias of + 5.20 W m− 2) of the CM SAF records as compared to the surface observations on a monthly mean basis. Equally, there is a monthly mean absolute bias difference (MABD) of 8.19 W m− 2 that is below the accuracy threshold defined by the CM SAF. There is a clear maximum and minimum MABD during summer and winter, respectively, with an opposite cycle if the relative MABD values are considered. Moreover, the temporal stability of the CM SAF SSR is checked against the GEBA stations for the mean time series over Europe, as well as for each individual series. The results point to possible inhomogeneities in the CM SAF records around 1987 and 1994, possibly due to changes in the satellite instruments, although other factors such as the lack of aerosol retrievals in the CM SAF SSR are also discussed. Consequently, the study of the means and trends in the SSR derived from CM SAF is only recommended for the records after 1994. more
Atmosphere CM-SAF Climate Data Records Validation

The CM SAF SSM/I-based total column water vapour climate data record: methods and evaluation against re-analyses and satellite

Author(s):
Schröder, M.; Jonas, M.; Lindau, R.; Schulz, J.; Fennig, K.
Publication title: Atmospheric Measurement Techniques
2013
 | Volume: 6 | Issue: 3
2013
DOI: 10.5194/amt-6-765-2013
Abstract:
Abstract. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring … Abstract. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring (CM SAF) aims at the provision and sound validation of well documented Climate Data Records (CDRs) in sustained and operational environments. In this study, a total column water vapour path (WVPA) climatology from CM SAF is presented and inter-compared to water vapour data records from various data sources. Based on homogenised brightness temperatures from the Special Sensor Microwave Imager (SSM/I), a climatology of WVPA has been generated within the Hamburg Ocean–Atmosphere Fluxes and Parameters from Satellite (HOAPS) framework. Within a research and operation transition activity the HOAPS data and operation capabilities have been successfully transferred to the CM SAF where the complete HOAPS data and processing schemes are hosted in an operational environment. An objective analysis for interpolation, namely kriging, has been applied to the swath-based WVPA retrievals from the HOAPS data set. The resulting climatology consists of daily and monthly mean fields of WVPA over the global ice-free ocean. The temporal coverage ranges from July 1987 to August 2006. After a comparison to the precursor product the CM SAF SSM/I-based climatology has been comprehensively compared to different types of meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF-ERA40, ERA INTERIM and operational analyses) and from the Japan Meteorological Agency (JMA–JRA). This inter-comparison shows an overall good agreement between the climatology and the analyses, with daily absolute biases generally smaller than 2 kg m−2. The absolute value of the bias to JRA and ERA INTERIM is typically smaller than 0.5 kg m−2. For the period 1991–2006, the root mean square error (RMSE) for both reanalyses is approximately 2 kg m−2. As SSM/I WVPA and radiances are assimilated into JMA and all ECMWF analyses and to assess consistency with existing WVPA climatologies, the SSM/I-based climatology is also compared to the time series of SSM/I and TMI (Tropical Rainfall Measuring Mission Microwave Imager) WVPA from Remote Sensing Systems (RSS), leading to results consistent with the reanalyses results. This evaluation study gives confidence in consistency, accurateness and stability of the total water vapour climatology produced. more
Atmosphere CM-SAF Climate Data Records Validation

On the optimal method for evaluating cloud products from passive satellite imagery using CALIPSO-CALIOP data: example investigating the CM SAF CLARA-A1 dataset

Author(s):
Karlsson, K.-G.; Johansson, E.
Publication title: Atmospheric Measurement Techniques
2013
 | Volume: 6 | Issue: 5
2013
DOI: 10.5194/amt-6-1271-2013
Abstract:
Abstract. A method for detailed evaluation of a new satellite-derived global 28 yr cloud and radiation climatology (Climate Monitoring SAF Clouds, Alb… Abstract. A method for detailed evaluation of a new satellite-derived global 28 yr cloud and radiation climatology (Climate Monitoring SAF Clouds, Albedo and Radiation from AVHRR data, named CLARA-A1) from polar-orbiting NOAA and Metop satellites is presented. The method combines 1 km and 5 km resolution cloud datasets from the CALIPSO-CALIOP (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation – Cloud-Aerosol Lidar with Orthogonal Polarization) cloud lidar for estimating cloud detection limitations and the accuracy of cloud top height estimations. Cloud detection is shown to work efficiently for clouds with optical thicknesses above 0.30 except for at twilight conditions when this value increases to 0.45. Some misclassifications of cloud-free surfaces during daytime were revealed for semi-arid land areas in the sub-tropical and tropical regions leading to up to 20% overestimated cloud amounts. In addition, a substantial fraction (at least 20–30%) of all clouds remains undetected in the polar regions during the polar winter season due to the lack of or an inverted temperature contrast between Earth surfaces and clouds. Subsequent cloud top height evaluation took into account the derived information about the cloud detection limits. It was shown that this has fundamental importance for the achieved results. An overall bias of −274 m was achieved compared to a bias of −2762 m when no measures were taken to compensate for cloud detection limitations. Despite this improvement it was concluded that high-level clouds still suffer from substantial height underestimations, while the opposite is true for low-level (boundary layer) clouds. The validation method and the specifically collected satellite dataset with optimal matching in time and space are suggested for a wider use in the future for evaluation of other cloud retrieval methods based on passive satellite imagery. more
Atmosphere CM-SAF Climate Data Records Validation

Land Surface Albedo from Geostationary Satelites: A Multiagency Collaboration within SCOPE-CM

Author(s):
Lattanzio, Alessio; Schulz, Jörg; Matthews, Jessica; Okuyama, Arata; Theodore, Bertrand; Bates, John J.; Knapp, Kenneth R.; Kosaka, Yuki; Schüller, Lothar
Publication title: Bulletin of the American Meteorological Society
2013
 | Volume: 94 | Issue: 2
2013
DOI: 10.1175/BAMS-D-11-00230.1
Abstract:
Climate has been recognized to have direct and indirect impact on society and economy, both in the long term and daily life. The challenge of understa… Climate has been recognized to have direct and indirect impact on society and economy, both in the long term and daily life. The challenge of understanding the climate system, with its variability and changes, is enormous and requires a joint long-term international commitment from research and governmental institutions. An important international body to coordinate worldwide climate monitoring efforts is the World Meteorological Organization (WMO). The Global Climate Observing System (GCOS) has the mission to provide coordination and the requirements for global observations and essential climate variables (ECVs) to monitor climate changes. The WMO-led activity on Sustained, Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) is responding to these requirements by ensuring a continuous and sustained generation of climate data records (CDRs) from satellite data in compliance with the principles and guidelines of GCOS. SCOPE-CM represents a new partnership between operational space agencies to coordinate the generation of CDRs. To this end, pilot projects for different ECVs, such as surface albedo, cloud properties, water vapor, atmospheric motion winds, and upper-tropospheric humidity, have been initiated. The coordinated activity on land surface albedo involves the operational meteorological satellite agencies in Europe [European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)], in Japan [the Japan Meteorological Agency (JMA)], and in the United States [National Oceanic and Atmospheric Administration (NOAA)]. This paper presents the first results toward the generation of a unique land surface albedo CDR, involving five different geostationary satellite positions and approximately three decades of data starting in the 1980s, and combining close to 30 different satellite instruments. more
Climate Data Records EUM-Secr Land Validation

Intercalibrating Microwave Satellite Observations for Monitoring Long-Term Variations in Upper- and Midtropospheric Water Vapor*

Author(s):
Chung, Eui-Seok; Soden, Brian J.; John, Viju O.
Publication title: Journal of Atmospheric and Oceanic Technology
2013
 | Volume: 30 | Issue: 10
2013
DOI: 10.1175/JTECH-D-13-00001.1
Abstract:
Abstract This paper analyzes the growing archive of 183-GHz water vapor absorption band measurements from the Advanced Microwave Sounding … Abstract This paper analyzes the growing archive of 183-GHz water vapor absorption band measurements from the Advanced Microwave Sounding Unit B (AMSU-B) and Microwave Humidity Sounder (MHS) on board polar-orbiting satellites and document adjustments necessary to use the data for long-term climate monitoring. The water vapor channels located at 183.31 ± 1 GHz and 183.31 ± 3 GHz are sensitive to upper- and midtropospheric relative humidity and less prone to the clear-sky sampling bias than infrared measurements, making them a valuable but underutilized source of information on free-tropospheric water vapor. A method for the limb correction of the satellite viewing angle based upon a simplified model of radiative transfer is introduced to remove the scan angle dependence of the radiances. Biases due to the difference in local observation time between satellites and spurious trends associated with satellite orbital drift are then diagnosed and adjusted for using synthetic radiative simulations based on the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim). The adjusted, cloud-filtered, and limb-corrected brightness temperatures are then intercalibrated using zonal-mean brightness temperature differences. It is found that these correction procedures significantly improve consistency and quantitative agreement between microwave radiometric satellite observations that can be used to monitor upper- and midtropospheric water vapor. The resulting radiances are converted to estimates of the deep-layer-mean upper- and midtropospheric relative humidity, and can be used to evaluate trends in upper-tropospheric relative humidity from reanalysis datasets and coupled ocean–atmosphere models. more
Climate Data Records EUM-Secr Validation

Triple Collocation of Summer Precipitation Retrievals from SEVIRI over Europe with Gridded Rain Gauge and Weather Radar Data

Author(s):
Roebeling, R. A.; Wolters, E. L. A.; Meirink, J. F.; Leijnse, H.
Publication title: Journal of Hydrometeorology
2012
 | Volume: 13 | Issue: 5
2012
DOI: 10.1175/JHM-D-11-089.1
Abstract:
Abstract Quantitative information on the spatial and temporal error structures in large-scale (regional or global) precipitation datasets … Abstract Quantitative information on the spatial and temporal error structures in large-scale (regional or global) precipitation datasets is essential for hydrologic and climatic studies. A powerful tool to quantify error structures in large-scale datasets is triple collocation. In this paper, triple collocation is used to determine the spatial and temporal error characteristics of three precipitation datasets over Europe—that is, the precipitation-properties visible/near infrared (PP-VNIR) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board Meteosat Second Generation (MSG), weather radar observations from the European integrated weather radar system, and gridded rain gauge observations from the datasets of the Global Precipitation Climatology Centre (GPCC) and the European Climate Assessment and Dataset (ECA&D) project. For these datasets the spatial and temporal error characteristics are evaluated and their performance is discussed. Finally, weather radar and PP-VNIR retrievals are used to evaluate the diurnal cycles of precipitation occurrence and intensity during daylight hours for different European climate regions. The results suggest that the triple collocation method provides realistic error estimates. The spatial and temporal error structures agree with the findings of earlier studies and reveal the strengths and weaknesses of the datasets, such as inhomogeneity of weather radar practices across Europe, the effect of sampling density in the gridded rain gauge dataset, and the sensitivity to retrieval assumptions in the PP-VNIR dataset. This study can help us in developing satisfactory strategies for combining various precipitation datasets—for example, for improved monitoring of diurnal variations or for detecting temporal trends in precipitation. more
Application Atmosphere CM-SAF Climate Data Records

Multi-sensor data merging with stacked neural networks for the creation of satellite long-term climate data records

Author(s):
Loyola, Diego G; Coldewey-Egbers, Melanie
Publication title: EURASIP Journal on Advances in Signal Processing
2012
 | Volume: 2012 | Issue: 1
2012
DOI: 10.1186/1687-6180-2012-91
Abstract:
This article presents a novel artificial neural network technique for merging multi-sensor satellite data. Stacked neural networks (NNs) are used to l… This article presents a novel artificial neural network technique for merging multi-sensor satellite data. Stacked neural networks (NNs) are used to learn the temporal and spatial drifts between data from different satellite sensors. The resulting NNs are then used to sequentially adjust the satellite data for the creation of a global homogeneous long-term climate data record. The proposed technique has successfully been applied to the merging of ozone data from three European satellite sensors covering together a time period of more than 16 years. The resulting long-term ozone data record has an excellent long-term stability of 0.2 ± 0.2% per decade and can therefore be used for ozone and climate studies. more
AC-SAF Atmosphere Climate Data Records Validation

IASI on Metop-A: Operational Level 2 retrievals after five years in orbit

Author(s):
August, Thomas; Klaes, Dieter; Schlüssel, Peter; Hultberg, Tim; Crapeau, Marc; Arriaga, Arlindo; O'Carroll, Anne; Coppens, Dorothée; Munro, Rose; Calbet, Xavier
Publication title: Journal of Quantitative Spectroscopy and Radiative Transfer
2012
 | Volume: 113 | Issue: 11
2012
DOI: 10.1016/j.jqsrt.2012.02.028
Abstract:
Geophysical parameters from the IASI instrument on Metop-A are essential products provided from EUMETSAT's Central Facility in near real time. They in… Geophysical parameters from the IASI instrument on Metop-A are essential products provided from EUMETSAT's Central Facility in near real time. They include vertical profiles of temperature and humidity, related cloud information, surface emissivity and temperature, and atmospheric composition parameters (CO, ozone and several other trace gases). As compared to previous operational processor versions, the latest processor version 5 delivers significant improvements in retrieval performance for most major products. These include improvements to cloud properties products, cloud detection (with a positive impact on the knowledge of the sea surface temperature, SST), the temperature profile (especially in the mid and upper troposphere), and ozone and carbon monoxide total columns. This paper provides a comprehensive summary of the processing algorithms, the latest scientific developments, and the related validation studies and activities. It concludes with a discussion of the future outlook. more
Climate Data Records EUM-Secr Method

HOAPS precipitation validation with ship-borne rain gauge measurements over the Baltic Sea

Author(s):
Bumke, Karl; Fennig, Karsten; Strehz, Alexander; Mecking, Rebekka; Schröder, Marc
Publication title: Tellus A: Dynamic Meteorology and Oceanography
2012
 | Volume: 64 | Issue: 1
2012
DOI: 10.3402/tellusa.v64i0.18486
Abstract:
Global ocean precipitation is an important part of the water cycle in the climate system. A number of efforts have been undertaken to acquire reliable… Global ocean precipitation is an important part of the water cycle in the climate system. A number of efforts have been undertaken to acquire reliable estimates of precipitation over the oceans based on remote sensing and reanalysis modelling. However, validation of these data is still a challenging task, mainly due to a lack of suitable in situ measurements of precipitation over the oceans. In this study, validation of the satellite-based Hamburg Ocean Atmosphere Parameters and fluxes from Satellite data (HOAPS) climatology was conducted with in situ measurements by ship rain gauges over the Baltic Sea from 1995 to 1997. The ship rain gauge data are point-to-area collocated against the HOAPS data. By choosing suitable collocation parameters, a detection rate of up to about 70% is achieved. Investigation of the influence of the synoptic situation on the detectability shows that HOAPS performs better for stratiform than for convective precipitation. The number of collocated data is not sufficient to validate precipitation rates. Thus, precipitation rates were analysed by applying an interpolation scheme based on the Kriging method to both data sets. It was found that HOAPS underestimates precipitation by about 10%, taking into account that precipitation rates below 0.3 mm h−1 cannot be detected from satellite information. more
Atmosphere CM-SAF Climate Data Records Validation

A New Algorithm for the Satellite-Based Retrieval of Solar Surface Irradiance in Spectral Bands

Author(s):
Mueller, Richard; Behrendt, Tanja; Hammer, Annette; Kemper, Axel
Publication title: Remote Sensing
2012
 | Volume: 4 | Issue: 3
2012
DOI: 10.3390/rs4030622
Abstract:
Accurate solar surface irradiance data is a prerequisite for an efficient planning and operation of solar energy systems. Further, it is essential for… Accurate solar surface irradiance data is a prerequisite for an efficient planning and operation of solar energy systems. Further, it is essential for climate monitoring and analysis. Recently, the demand on information about spectrally resolved solar surface irradiance has grown. As surface measurements are rare, satellite derived information with high accuracy might fill this gap. This paper describes a new approach for the retrieval of spectrally resolved solar surface irradiance from satellite data. The method combines a eigenvector-hybrid look-up table approach for the clear sky case with satellite derived cloud transmission (Heliosat method). The eigenvector LUT approach is already used to retrieve the broadband solar surface irradiance of data sets provided by the Climate Monitoring Satellite Application Facility (CM-SAF). This paper describes the extension of this approach to wavelength bands and the combination with spectrally resolved cloud transmission values derived with radiative transfer corrections of the broadband cloud transmission. Thus, the new approach is based on radiative transfer modeling and enables the use of extended information about the atmospheric state, among others, to resolve the effect of water vapor and ozone absorption bands. The method is validated with spectrally resolved measurements from two sites in Europe and by comparison with radiative transfer calculations. The validation results demonstrate the ability of the method to retrieve accurate spectrally resolved irradiance from satellites. The accuracy is in the range of the uncertainty of surface measurements, with exception of the UV and NIR (≥ 1200 nm) part of the spectrum, where higher deviations occur. more
Atmosphere CM-SAF Climate Data Records Method

A fast SEVIRI simulator for quantifying retrieval uncertainties in the CM SAF cloud physical property algorithm

Author(s):
Jonkheid, B. J.; Roebeling, R. A.; van Meijgaard, E.
Publication title: Atmospheric Chemistry and Physics
2012
 | Volume: 12 | Issue: 22
2012
DOI: 10.5194/acp-12-10957-2012
Abstract:
Abstract. The uncertainties in the cloud physical properties derived from satellite observations make it difficult to interpret model evaluation studi… Abstract. The uncertainties in the cloud physical properties derived from satellite observations make it difficult to interpret model evaluation studies. In this paper, the uncertainties in the cloud water path (CWP) retrievals derived with the cloud physical properties retrieval algorithm (CPP) of the climate monitoring satellite application facility (CM SAF) are investigated. To this end, a numerical simulator of MSG-SEVIRI observations has been developed that calculates the reflectances at 0.64 and 1.63 μm for a wide range of cloud parameter values, satellite viewing geometries and surface albedos using a plane-parallel radiative transfer model. The reflectances thus obtained are used as input to CPP, and the retrieved values of CWP are compared to the original input of the simulator. Cloud parameters considered in this paper refer to e.g. sub-pixel broken clouds and the simultaneous occurrence of ice and liquid water clouds within one pixel. These configurations are not represented in the CPP algorithm and as such the associated retrieval uncertainties are potentially substantial. It is shown that the CWP retrievals are very sensitive to the assumptions made in the CPP code. The CWP retrieval errors are generally small for unbroken single-layer clouds with COT > 10, with retrieval errors of ~3% for liquid water clouds to ~10% for ice clouds. In a multi-layer cloud, when both liquid water and ice clouds are present in a pixel, the CWP retrieval errors increase dramatically; depending on the cloud, this can lead to uncertainties of 40–80%. CWP retrievals also become more uncertain when the cloud does not cover the entire pixel, leading to errors of ~50% for cloud fractions of 0.75 and even larger errors for smaller cloud fractions. Thus, the satellite retrieval of cloud physical properties of broken clouds as well as multi-layer clouds is complicated by inherent difficulties, and the proper interpretation of such retrievals requires extra care. more
Atmosphere CM-SAF Climate Data Records Validation

Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI

Author(s):
Bugliaro, L.; Zinner, T.; Keil, C.; Mayer, B.; Hollmann, R.; Reuter, M.; Thomas, W.
Publication title: Atmospheric Chemistry and Physics
2011
 | Volume: 11 | Issue: 12
2011
DOI: 10.5194/acp-11-5603-2011
Abstract:
Abstract. Validation of cloud properties retrieved from passive spaceborne imagers is essential for cloud and climate applications but complicated due… Abstract. Validation of cloud properties retrieved from passive spaceborne imagers is essential for cloud and climate applications but complicated due to the large differences in scale and observation geometry between the satellite footprint and the independent ground based or airborne observations. Here we illustrate and demonstrate an alternative approach: starting from the output of the COSMO-EU weather model of the German Weather Service realistic three-dimensional cloud structures at a spatial scale of 2.33 km are produced by statistical downscaling and microphysical properties are associated to them. The resulting data sets are used as input to the one-dimensional radiative transfer model libRadtran to simulate radiance observations for all eleven low resolution channels of MET-8/SEVIRI. At this point, both cloud properties and satellite radiances are known such that cloud property retrieval results can be tested and tuned against the objective input "truth". As an example, we validate a cloud property retrieval of the Institute of Atmospheric Physics of DLR and that of EUMETSAT's Climate Monitoring Science Application Facility CMSAF. Cloud detection and cloud phase assignment perform well. By both retrievals 88% of the pixels are correctly classified as clear or cloudy. The DLR algorithm assigns the correct thermodynamic phase to 95% of the cloudy pixels and the CMSAF retrieval to 84%. Cloud top temperature is slightly overestimated by the DLR code (+3.1 K mean difference with a standard deviation of 10.6 K) and to a very low extent by the CMSAF code (−0.12 K with a standard deviation of 7.6 K). Both retrievals account reasonably well for the distribution of optical thickness for both water and ice clouds, with a tendency to underestimation. Cloud effective radii are most difficult to evaluate but the APICS algorithm shows that realistic histograms of occurrences can be derived (CMSAF was not evaluated in this context). Cloud water path, which is a combination of the last two quantities, is slightly underestimated by APICS, while CMSAF shows a larger scattering. more
Atmosphere CM-SAF Climate Data Records Validation

Validation of Backscatter Measurements from the Advanced Scatterometer on MetOp-A

Author(s):
Anderson, C.; Figa, J.; Bonekamp, H.; Wilson, J. J. W.; Verspeek, J.; Stoffelen, A.; Portabella, M.
Publication title: Journal of Atmospheric and Oceanic Technology
2011
 | Volume: 29 | Issue: 1
2011
DOI: 10.1175/JTECH-D-11-00020.1
Abstract:
Abstract The Advanced Scatterometer (ASCAT) on the Meteorological Operational (MetOp) series of satellites is designed to provide data for… Abstract The Advanced Scatterometer (ASCAT) on the Meteorological Operational (MetOp) series of satellites is designed to provide data for the retrieval of ocean wind fields. Three transponders were used to give an absolute calibration and the worst-case calibration error is estimated to be 0.15–0.25 dB. In this paper the calibrated data are validated by comparing the backscatter from a range of naturally distributed targets against models developed from European Remote Sensing Satellite (ERS) scatterometer data. For the Amazon rainforest it is found that the isotropic backscatter decreases from −6.2 to −6.8 dB over the incidence angle range. The ERS value is around −6.5 dB. All ASCAT beams are within 0.1 dB of each other. Rainforest backscatter over a 3-yr period is found to be very stable with annual changes of approximately 0.02 dB. ASCAT ocean backscatter is compared against values from the C-band geophysical model function (CMOD-5) using ECMWF wind fields. A difference of approximately 0.2 dB below 55° incidence is found. Differences of over 1 dB above 55° are likely due to inaccuracies in CMOD-5, which has not been fully validated at large incidence angles. All beams are within 0.1 dB of each other. Backscatter from regions of stable Antarctic sea ice is found to be consistent with model backscatter except at large incidence angles where the model has not been validated. The noise in the ice backscatter indicates that the normalized standard deviation of the backscatter values Kp is around 4.5%, which is consistent with the expected value. These results agree well with the expected calibration accuracy and give confidence that the calibration has been successful and that ASCAT products are of high quality. more
Climate Data Records EUM-Secr Validation

A New Method for the Comparison of Trend Data with an Application to Water Vapor

Author(s):
Mieruch, Sebastian; Noël, Stefan; Reuter, Maximilian; Bovensmann, Heinrich; Burrows, John P.; Schröder, Marc; Schulz, Jörg
Publication title: Journal of Climate
2011
 | Volume: 24 | Issue: 12
2011
DOI: 10.1175/2011JCLI3669.1
Abstract:
Abstract Global total column water vapor trends have been derived from both the Global Ozone Monitoring Experiment (GOME) and the Scanning… Abstract Global total column water vapor trends have been derived from both the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite data and from globally distributed radiosonde measurements, archived and quality controlled by the Deutscher Wetterdienst (DWD). The control of atmospheric water vapor amount by the hydrological cycle plays an important role in determining surface temperature and its response to the increase in man-made greenhouse effect. As a result of its strong infrared absorption, water vapor is the most important naturally occurring greenhouse gas. Without water vapor, the earth surface temperature would be about 20 K lower, making the evolution of life, as we know it, impossible. The monitoring of water vapor and its evolution in time is therefore of utmost importance for our understanding of global climate change. Comparisons of trends derived from independent water vapor measurements from satellite and radiosondes facilitate the assessment of the significance of the observed changes in water vapor. In this manuscript, the authors have compared observed water vapor change and trends, derived from independent instruments, and assessed the statistical significance of their differences. This study deals with an example of the Behrens–Fisher problem, namely, the comparison of samples with different means and different standard deviations, applied to trends from time series. Initially the Behrens–Fisher problem for the derivation of the consolidated change and trends is solved using standard (frequentist) hypothesis testing by performing the Welch test. Second, a Bayesian model selection is applied to solve the Behrens–Fisher problem by integrating the posterior probabilities numerically by using the algorithm Differential Evolution Markov Chain (DEMC). Additionally, an analytical approximative solution of the Bayesian posterior probabilities is derived by means of a quadratic Taylor series expansion applied in a computationally efficient manner to large datasets. The two statistical methods used in the study yield similar results for the comparison of the water vapor changes and trends from the different measurements, yielding a consolidated and consistent behavior. more
Application Atmosphere CM-SAF Climate Data Records

Towards Multidecadal Consistent Meteosat Surface Albedo Time Series

Author(s):
Loew, Alexander; Govaerts, Yves
Publication title: Remote Sensing
2010
 | Volume: 2 | Issue: 4
2010
DOI: 10.3390/rs2040957
Abstract:
Monitoring of land surface albedo dynamics is important for the understanding of observed climate trends. Recently developed multidecadal surface albe… Monitoring of land surface albedo dynamics is important for the understanding of observed climate trends. Recently developed multidecadal surface albedo data products, derived from a series of geostationary satellite data, provide the opportunity to study long term surface albedo dynamics at the regional to global scale. Reliable estimates of temporal trends in surface albedo require carefully calibrated and homogenized long term satellite data records and derived products. The present paper investigates the long term consistency of a new surface albedo product derived from Meteosat First Generation (MFG) geostationary satellites for the time period 1982–2006. The temporal consistency of the data set is characterized. The analysis of the long term homogeneity reveals some discrepancies in the time series related to uncertainties in the characterization of the sensor spectral response of some of the MFG satellites. A method to compensate for uncertainties in the current data product is proposed and evaluated. more
Climate Data Records EUM-Secr Land Method

The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS-3

Author(s):
Andersson, A.; Fennig, K.; Klepp, C.; Bakan, S.; Graßl, H.; Schulz, J.
Publication title: Earth System Science Data
2010
 | Volume: 2 | Issue: 2
2010
DOI: 10.5194/essd-2-215-2010
Abstract:
The availability of microwave instruments on satellite platforms allows the retrieval of essential water cycle components at high quality for improved… The availability of microwave instruments on satellite platforms allows the retrieval of essential water cycle components at high quality for improved understanding and evaluation of water processes in climate modelling. HOAPS-3, the latest version of the satellite climatology "Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data" provides fields of turbulent heat fluxes, evaporation, precipitation, freshwater flux and related atmospheric variables over the global ice-free ocean. This paper describes the content, methodology and retrievals of the HOAPS climatology. A sophisticated processing chain, including all available Special Sensor Microwave Imager (SSM/I) instruments aboard the satellites of the Defense Meteorological Satellites Program (DMSP) and careful inter-sensor calibration, ensures a homogeneous time-series with dense data sampling and hence detailed information of the underlying weather situations. The completely reprocessed data set with a continuous time series from 1987 to 2005 contains neural network based algorithms for precipitation and wind speed and Advanced Very High Resolution Radiometer (AVHRR) based SST fields. Additionally, a new 85 GHz synthesis procedure for the defective SSM/I channels on DMSP F08 from 1988 on has been implemented. Freely available monthly and pentad means, twice daily composites and scan-based data make HOAPS-3 a versatile data set for studying ocean-atmosphere interaction on different temporal and spatial scales. HOAPS-3 data products are available via http://www.hoaps.org. more
Atmosphere CM-SAF Climate Data Records Method

Radiometric Calibration of the Advanced Wind Scatterometer Radar ASCAT Carried Onboard the METOP-A Satellite

Author(s):
Wilson, J J W; Anderson, C; Baker, M A; Bonekamp, H; Saldaña, J Figa; Dyer, R G; Lerch, J A; Kayal, G; Gelsthorpe, R V; Brown, M A; Schied, E; Schutz-Munz, S; Rostan, F; Pritchard, E W; Wright, N G; King, D; Onel, Ü
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2010
 | Volume: 48 | Issue: 8
2010
DOI: 10.1109/TGRS.2010.2045763
Abstract:
The Advanced Wind Scatterometer (ASCAT) is a six-beam spaceborne radar instrument designed to measure wind fields over the oceans. An ASCAT instrument… The Advanced Wind Scatterometer (ASCAT) is a six-beam spaceborne radar instrument designed to measure wind fields over the oceans. An ASCAT instrument is carried by each of the three METOP satellites. The ASCAT calibration strategy is described and detailed results are presented concerning the radiometric calibration achieved. more
Climate Data Records EUM-Secr Validation

Multi sensor reanalysis of total ozone

Author(s):
van der A, R. J.; Allaart, M. A. F.; Eskes, H. J.
Publication title: Atmospheric Chemistry and Physics
2010
 | Volume: 10 | Issue: 22
2010
DOI: 10.5194/acp-10-11277-2010
Abstract:
Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measu… Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based on independent ground-based total ozone data from the World Ozone and Ultraviolet Data Center. The correction is a function of solar zenith angle, viewing angle, time (trend), and effective ozone temperature. As second step data assimilation was applied to create a global dataset of total ozone analyses. The data assimilation method is a sub-optimal implementation of the Kalman filter technique, and is based on a chemical transport model driven by ECMWF meteorological fields. The chemical transport model provides a detailed description of (stratospheric) transport and uses parameterisations for gas-phase and ozone hole chemistry. The MSR dataset results from a 30-year data assimilation run with the 14 corrected satellite datasets as input, and is available on a grid of 1× 1 1/2° with a sample frequency of 6 h for the complete time period (1978–2008). The Observation-minus-Analysis (OmA) statistics show that the bias of the MSR analyses is less than 1% with an RMS standard deviation of about 2% as compared to the corrected satellite observations used. more
AC-SAF Atmosphere Climate Data Records Validation

A Method for Estimating the Sampling Error Applied to CM-SAF Monthly Mean Cloud Fractional Cover Data Retrieved From MSG SEVIRI

Author(s):
Reuter, Maximilian; Thomas, Werner; Mieruch, Sebastian; Hollmann, Rainer
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2010
 | Volume: 48 | Issue: 6
2010
DOI: 10.1109/TGRS.2010.2041240
Abstract:
Averaging a set of individual measurements can reduce the stochastic error but can introduce a sampling error particularly for irregularly sampled dat… Averaging a set of individual measurements can reduce the stochastic error but can introduce a sampling error particularly for irregularly sampled data. We present a general method to estimate the total error of an averaged quantity as a combination of the measurement error and the sampling error without knowledge about the true average value of the distribution. Our approach requires covariance matrices connecting the retrieved measurement values to an independent reference data set. These covariance matrices can be obtained from a representative validation data set. We confirm the validity of the method by estimating the temporal sampling error of monthly mean cloud fractional cover (CFC) data derived from the Spinning-Enhanced Visible and Infrared Imager radiometer onboard the METEOSAT Second Generation (MSG) spacecraft, operated by the European Organization for the Exploitation of Meteorological Satellites. The estimated sampling errors are then compared with the true sampling errors calculated from an hourly sampled complete data set. For this purpose, we use ten sampling scenarios. Some of them address typical sampling problems like systematic over- and undersampling as well as hourly, daily, and random data gaps. Two additional sampling scenarios are directly related to the satellite application facility on climate monitoring monthly mean CFC data record. These are used to estimate the worst case sampling errors of this data record. The estimated total and sampling errors agree well with corresponding calculated values. We derive the needed covariance matrices by analyzing synoptic observations of the cloud fraction which are MSG diskwide available, the majority of them over European land surfaces. The method is not limited to temporal averaging cloud fraction data. Moreover, it is a general method that is also applicable to temporal and spatial averaging of other parameters as long as appropriate covariance matrices are available. more
Atmosphere CM-SAF Climate Data Records Validation

The CM-SAF and FUB Cloud Detection Schemes for SEVIRI: Validation with Synoptic Data and Initial Comparison with MODIS and CALIPSO

Author(s):
Reuter, M.; Thomas, W.; Albert, P.; Lockhoff, M.; Weber, R.; Karlsson, K-G.; Fischer, J.
Publication title: Journal of Applied Meteorology and Climatology
2009
 | Volume: 48 | Issue: 2
2009
DOI: 10.1175/2008JAMC1982.1
Abstract:
Abstract The Satellite Application Facility on Climate Monitoring (CM-SAF) is aiming to retrieve satellite-derived geophysical parameters … Abstract The Satellite Application Facility on Climate Monitoring (CM-SAF) is aiming to retrieve satellite-derived geophysical parameters suitable for climate monitoring. CM-SAF started routine operations in early 2007 and provides a climatology of parameters describing the global energy and water cycle on a regional scale and partially on a global scale. Here, the authors focus on the performance of cloud detection methods applied to measurements of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the first Meteosat Second Generation geostationary spacecraft. The retrieved cloud mask is the basis for calculating the cloud fractional coverage (CFC) but is also mandatory for retrieving other geophysical parameters. Therefore, the quality of the cloud detection directly influences climate monitoring of many other parameters derived from spaceborne sensors. CM-SAF products and results of an alternative cloud coverage retrieval provided by the Institut für Weltraumwissenschaften of the Freie Universität in Berlin, Germany (FUB), were validated against synoptic measurements. Furthermore, and on the basis of case studies, an initial comparison was performed of CM-SAF results with results derived from the Moderate Resolution Imaging Spectrometer (MODIS) and from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP). Results show that the CFC from CM-SAF and FUB agrees well with synoptic data and MODIS data over midlatitudes but is underestimated over the tropics and overestimated toward the edges of the visible Earth disk. more
Atmosphere CM-SAF Climate Data Records Validation

Surface radiation at sea validation of satellite-derived data with shipboard measurements

Author(s):
Behr, Hein Dieter; Hollmann, Rainer; Müller, Richard W.
Publication title: Meteorologische Zeitschrift
2009
 | Volume: 18 | Issue: 1
2009
DOI: 10.1127/0941-2948/2009/356
Abstract:
Quality-controlled and validated radiation products are the basis for their ability to serve the climate and solar energy community. Satellite-derived… Quality-controlled and validated radiation products are the basis for their ability to serve the climate and solar energy community. Satellite-derived radiation fluxes are well preferred for this task as they cover the whole research area in time and space. In order to monitor the accuracy of these data, validation with well maintained and calibrated ground based measurements is necessary. Over sea, however, long-term accurate reference data sets from calibrated instruments recording radiation are scarce. Therefore data from research vessels operating at sea are used to perform a reasonable validation. A prerequisite is that the instruments on board are maintained as well as land borne stations. This paper focuses on the comparison of radiation data recorded on board of the German Research Vessel "Meteor" during her 13 months cruise across the Mediterranean and the Black Sea with CM-SAF products using NOAA- and MSG-data (August 2006-August 2007): surface incoming short-wave radiation (SIS) and surface downward long-wave radiation (SDL). Measuring radiation fluxes at sea causes inevitable errors, e.g.shadowing of fields of view of the radiometers by parts of the ship. These ship-inherent difficulties are discussed at first. A comparison of pairs of ship-recorded and satellite-derived mean fluxes for the complete measuring period delivers a good agreement: the mean bias deviation (MBD) for SIS daily means is −7.6 W/m2 with a median bias of −4 W/m2 and consistently the MBD for monthly means is −7.3 W/m2, for SDL daily means the MBD is 8.1 and 6 W/m2 median bias respectively. The MBD for monthly means is 8.2 W/m2. The variances of the daily means (ship and satellite) have the same annual courses for both fluxes. No significant dependence of the bias on the total cloud cover recorded according to WMO (1969) has been found. The results of the comparison between ship-based observations and satellite retrieved surface radiation reveal the good accuracy of the satellite-based CM-SAF products over sea. more
Atmosphere CM-SAF Climate Data Records Validation

Satellite Application Facilities irradiance products: hourly time step comparison and validation over Europe

Author(s):
Ineichen, Pierre; Barroso, Carla Sofia; Geiger, Bernhard; Hollmann, Rainer; Marsouin, Anne; Mueller, Richard
Publication title: International Journal of Remote Sensing
2009
 | Volume: 30 | Issue: 21
2009
DOI: 10.1080/01431160802680560
Abstract:
Downward short- and longwave incoming irradiances play a key role in the radiation budget at the Earth's surface. Monitoring these parameters is essen… Downward short- and longwave incoming irradiances play a key role in the radiation budget at the Earth's surface. Monitoring these parameters is essential for understanding the basic mechanisms involved in climate change, such as the greenhouse effect, global dimming, and changes in cloud cover and precipitation. Geostationary satellite observations are important in the retrieval of irradiance at the surface, providing excellent spatial and temporal coverage. Three decentralized Satellite Application Facilities (SAFs) are currently operational in the European Organisation for the Exploitation of Meteorological Satellites (Eumetsat), involved in retrieving surface solar irradiance (SSI) and downward longwave irradiance (DLI) from Meteosat images. This study presents a common validation of these radiation products against ground data from eight stations covering four months representative of the annual declination variation. The overall conclusion is that the products of the different SAFs are comparable in terms of bias and standard deviation. The SSI is retrieved with a standard deviation of 80–100 W m−2 and negligible bias, and the DLI with a standard deviation of 25 W m−2 with a slight site-dependent bias. more
Atmosphere CM-SAF Climate Data Records Validation

Global long-term monitoring of the ozone layer – a prerequisite for predictions

Author(s):
Loyola, D. G.; Coldewey-Egbers, R. M.; Dameris, M.; Garny, H.; Stenke, A.; Van Roozendael, M.; Lerot, C.; Balis, D.; Koukouli, M.
Publication title: International Journal of Remote Sensing
2009
 | Volume: 30 | Issue: 15-16
2009
DOI: 10.1080/01431160902825016
Abstract:
Although the Montreal Protocol now controls the production and emission of ozone depleting substances, the timing of ozone recovery is unclear. There … Although the Montreal Protocol now controls the production and emission of ozone depleting substances, the timing of ozone recovery is unclear. There are many other factors affecting the ozone layer, in particular climate change is expected to modify the speed of re-creation of the ozone layer. Therefore, long-term observations are needed to monitor the further evolution of the stratospheric ozone layer. Measurements from satellite instruments provide global coverage and are supplementary to selective ground-based observations. The combination of data derived from different space-borne instruments is needed to produce homogeneous and consistent long-term data records. They are required for robust investigations including trend analysis. For the first time global total ozone columns from three European satellite sensors GOME (ERS-2), SCIAMACHY (ENVISAT), and GOME-2 (METOP-A) are combined and added up to a continuous time series starting in June 1995. On the one hand it is important to monitor the consequences of the Montreal Protocol and its amendments; on the other hand multi-year observations provide the basis for the evaluation of numerical models describing atmospheric processes, which are also used for prognostic studies to assess the future development. This paper gives some examples of how to use satellite data products to evaluate model results with respective data derived from observations, and to disclose the abilities and deficiencies of atmospheric models. In particular, multi-year mean values derived from the Chemistry-Climate Model E39C-A are used to check climatological values and the respective standard deviations. more
AC-SAF Atmosphere Climate Data Records Validation

Validation of Cloud Liquid Water Path Retrievals from SEVIRI Using One Year of CloudNET Observations

Author(s):
Roebeling, R. A.; Deneke, H. M.; Feijt, A. J.
Publication title: Journal of Applied Meteorology and Climatology
2008
 | Volume: 47 | Issue: 1
2008
DOI: 10.1175/2007JAMC1661.1
Abstract:
Abstract The accuracy and precision are determined of cloud liquid water path (LWP) retrievals from the Spinning Enhanced Visible and Infr… Abstract The accuracy and precision are determined of cloud liquid water path (LWP) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat-8 using 1 yr of LWP retrievals from microwave radiometer (MWR) measurements of two CloudNET stations in northern Europe. The MWR retrievals of LWP have a precision that is superior to current satellite remote sensing techniques, which justifies their use as validation data. The Cloud Physical Properties (CPP) algorithm of the Satellite Application Facility on Climate Monitoring (CM-SAF) is used to retrieve LWP from SEVIRI reflectances at 0.6 and 1.6 μm. The results show large differences in the accuracy and precision of LWP retrievals from SEVIRI between summer and winter. During summer, the instantaneous LWP retrievals from SEVIRI agree well with those from the MWRs. The accuracy is better than 5 g m−2 and the precision is better than 30 g m−2, which is similar to the precision of LWP retrievals from MWR. The added value of the 15-min sampling frequency of Meteosat-8 becomes evident in the validation of the daily median and diurnal variations in LWP retrievals from SEVIRI. The daily median LWP values from SEVIRI and MWR are highly correlated (correlation &gt; 0.95) and have a precision better than 15 g m−2. In addition, SEVIRI and MWR reveal similar diurnal variations in retrieved LWP values. The peak LWP values occur around noon. During winter, SEVIRI generally overestimates the instantaneous LWP values from MWR, the accuracy drops to about 10 g m2, and the precision to about 30 g m−2. The most likely reason for these lower accuracies is the shortcoming of CPP, and similar one-dimensional retrieval algorithms, to model inhomogeneous clouds. It is suggested that neglecting cloud inhomogeneities leads to a significant overestimation of LWP retrievals from SEVIRI over northern Europe during winter. more
Atmosphere CM-SAF Climate Data Records Validation

Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data

Author(s):
Wolters, Erwin L. A.; Roebeling, Robert A.; Feijt, Arnout J.
Publication title: Journal of Applied Meteorology and Climatology
2008
 | Volume: 47 | Issue: 6
2008
DOI: 10.1175/2007JAMC1591.1
Abstract:
Abstract Three cloud-phase determination algorithms from passive satellite imagers are explored to assess their suitability for climate mo… Abstract Three cloud-phase determination algorithms from passive satellite imagers are explored to assess their suitability for climate monitoring purposes in midlatitude coastal climate zones. The algorithms are the Moderate Resolution Imaging Spectroradiometer (MODIS)-like thermal infrared cloud-phase method, the Satellite Application Facility on Climate Monitoring (CM-SAF) method, and an International Satellite Cloud Climatology Project (ISCCP)-like method. Using one year (May 2004–April 2005) of data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the first Meteosat Second Generation satellite (Meteosat-8), retrievals of the methods are compared with collocated and synchronized ground-based cloud-phase retrievals obtained from cloud radar and lidar observations at Cabauw, Netherlands. Three aspects of the satellite retrievals are evaluated: 1) instantaneous cloud-phase retrievals, 2) monthly-averaged water and ice cloud occurrence frequency, and 3) diurnal cycle of cloud phase for May–August 2004. For the instantaneous cases, all methods have a very small bias for thick water and ice cloud retrievals (∼5%). The ISCCP-like method has a larger bias for pure water clouds (∼10%), which is likely due to the 260-K threshold leading to misdetection of water clouds existing at lower temperatures. For the monthly-averaged water and ice cloud occurrence, the CM-SAF method is best capable of reproducing the annual cycle, mainly for the water cloud occurrence frequency, for which an almost constant positive bias of ∼8% was found. The ISCCP- and MODIS-like methods have more problems in detecting the annual cycle, especially during the winter months. The difference in annual cycle detection among the three methods is most probably related to the use of visible/near-infrared reflectances that enable a more direct observation of cloud phase. The diurnal cycle in cloud phase is reproduced well by all methods. The MODIS-like method reproduces the diurnal cycle best, with correlations of 0.89 and 0.86 for water and ice cloud occurrence frequency, respectively. more
Atmosphere CM-SAF Climate Data Records Validation

Estimation of surface albedo increase during the eighties Sahel drought from Meteosat observations

Author(s):
Govaerts, Y.; Lattanzio, A.
Publication title: Global and Planetary Change
2008
 | Volume: 64 | Issue: 3-4
2008
DOI: 10.1016/j.gloplacha.2008.04.004
Abstract:
The devastating drought in the Sahel during the 70s and the 80s is among the most undisputed and largest recent climate event recognized by the resear… The devastating drought in the Sahel during the 70s and the 80s is among the most undisputed and largest recent climate event recognized by the research community. This dramatic climate event has generated numerous sensitivity analyses on land-atmosphere feedback mechanisms with contradicting conclusions on surface albedo response to precipitation changes. Recent improvements in the calibration and quantitative exploitation of archived Meteosat data for the retrieval of surface albedo have permitted to compare surface albedo of 1884, the driest year of the 80s, with year 2003 which had similar precipitation rate than conditions prevailing prior to the 80s drought. This analysis reveals detailed information on the geographical extension and magnitude of the surface albedo increase during from the 80s drought. A mean zonal increase in broadband surface albedo of about 0.06 between 1984 and 2003 has been estimated from the analysis of Meteosat observations. Regions particularly affected by the 1980s drought are essentially located into a narrow band of about 2° width along 16°N running from 18°W up to 20°E. Within this geographical area, surface albedo changes are not homogeneous and largest differences might locally exceed 0.15 whereas other places remained almost unaffected. The variety of previously published results might be explained by these important spatial variations observed around 16°N. more
Climate Data Records EUM-Secr Land Validation

Retrieval error estimation of surface albedo derived from geostationary large band satellite observations: Application to Meteosat-2 and Meteosat-7 data

Author(s):
Govaerts, Y. M.; Lattanzio, A.
Publication title: Journal of Geophysical Research
2007
 | Volume: 112 | Issue: D5
2007
DOI: 10.1029/2006JD007313
Abstract:
The extraction of critical geophysical variables from multidecade archived satellite observations, such as those acquired by the European Meteosat Fir… The extraction of critical geophysical variables from multidecade archived satellite observations, such as those acquired by the European Meteosat First Generation satellite series, for the generation of climate data records is recognized as a pressing challenge by international environmental organizations. This paper presents a statistical method for the estimation of the surface albedo retrieval error that explicitly accounts for the measurement uncertainties and differences in the Meteosat radiometer characteristics. The benefit of this approach is illustrated with a simple case study consisting of a meaningful comparison of surface albedo derived from observations acquired at a 20 year interval by sensors with different radiometric performances. In particular, it is shown how it is possible to assess the magnitude of minimum detectable significant surface albedo change. more
Climate Data Records EUM-Secr Land Method

Consistency of surface anisotropy characterization with meteosat observations

Author(s):
Lattanzio, A.; Govaerts, Y.M.; Pinty, B.
Publication title: Advances in Space Research
2007
 | Volume: 39 | Issue: 1
2007
DOI: 10.1016/j.asr.2006.02.049
Abstract:
The purpose of this paper is to present the results of the evaluation of the Meteosat Surface Albedo (MSA) product, including the effects due to instr… The purpose of this paper is to present the results of the evaluation of the Meteosat Surface Albedo (MSA) product, including the effects due to instrument changes and associated calibration uncertainties. To this end, observations acquired by two adjacent geostationary spacecrafts, Meteosat-7 and Meteosat-5 have been processed with the MSA algorithm. These satellites are located, respectively, at 0° and 63° East. Data acquired by these two instruments overlap over a large area encompassing most of Africa and the Arabian peninsula. The consistency of the surface anisotropy retrieval is evaluated through a reconstruction of the Meteosat-5 (-7) observations with the Meteosat-7 (-5) surface anisotropy characterization. Some differences slightly higher than the calibration accuracy have been found. This effect has no significant impact on the albedo retrieval which indicates that MSA is a reliable algorithm to produce albedo datasets. more
Climate Data Records EUM-Secr Method

Spectral Conversion of Surface Albedo Derived From Meteosat First Generation Observations

Author(s):
Govaerts, Y.M.; Pinty, B.; Taberner, M.; Lattanzio, A.
Publication title: IEEE Geoscience and Remote Sensing Letters
2006
 | Volume: 3 | Issue: 1
2006
DOI: 10.1109/LGRS.2005.854202
Abstract:
Comparison of surface albedos derived from spaceborne radiometers with different spectral bands requires, first of all, the conversion of these quanti… Comparison of surface albedos derived from spaceborne radiometers with different spectral bands requires, first of all, the conversion of these quantities into common spectral intervals. This letter proposes a spectral conversion method specifically dedicated to surface albedo derived in a large-band instrument such as the solar channel onboard the Meteosat first-generation radiometer. This new method accounts for the retrieval algorithm assumptions and radiometer spectral limitations that might have an impact on the retrieved surface albedo in such a large band. It is also shown that the proposed approach has no impact when surface albedo is derived in narrow bands and confirms the results of previously published spectral conversion methods. more
Climate Data Records EUM-Secr Land Method

Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17

Author(s):
Roebeling, R. A.; Feijt, A. J.; Stammes, P.
Publication title: Journal of Geophysical Research
2006
 | Volume: 111 | Issue: D20
2006
DOI: 10.1029/2005JD006990
Abstract:
In the framework of the Satellite Application Facility on Climate Monitoring (CM-SAF) an algorithm was developed to retrieve Cloud Physical Properties… In the framework of the Satellite Application Facility on Climate Monitoring (CM-SAF) an algorithm was developed to retrieve Cloud Physical Properties (CPP) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation (METEOSAT−8) and the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) satellites. This paper presents the CPP algorithm and determines if SEVIRI can be used together with AVHRR to build a consistent and accurate data set of cloud optical thickness (COT) and cloud liquid water path (CLWP) over Europe for climate research purposes. After quantifying the differences in 0.6 and 1.6 μm operational calibrated reflectances of SEVIRI and AVHRR, a recalibration procedure is proposed to normalize and absolutely calibrate these reflectances. The effects of recalibration, spatial resolution, and viewing geometry differences on the SEVIRI and AVHRR cloud property retrievals are evaluated. The intercomparison of 0.6 and 1.6 μm operationally calibrated reflectances indicates ∼6 and ∼26% higher reflectances for SEVIRI than for AVHRR. These discrepancies result in retrieval differences between AVHRR and SEVIRI of ∼8% for COT and ∼60% for CLWP. Owing to recalibration these differences reduce to ∼5%, while the magnitude of the median COT and CLWP values of AVHRR decrease ∼2 and ∼60% and the SEVIRI values increase ∼10 and ∼55%, respectively. The differences in spatial resolution and viewing geometry slightly influence the retrieval precision. Thus the CPP algorithm can be used to build a consistent and high-quality data set of SEVIRI and AVHRR retrieved cloud properties for climate research purposes, provided the instrument reflectances are recalibrated, preferably guided by the satellite operators. more
Atmosphere CM-SAF Climate Data Records Method

NWCSAF AVHRR Cloud Detection and Analysis Using Dynamic Thresholds and Radiative Transfer Modeling. Part I: Algorithm Description

Author(s):
Dybbroe, Adam; Karlsson, Karl-Göran; Thoss, Anke
Publication title: Journal of Applied Meteorology
2005
 | Volume: 44 | Issue: 1
2005
DOI: 10.1175/JAM-2188.1
Abstract:
Abstract New methods and software for cloud detection and classification at high and midlatitudes using Advanced Very High Resolution Radi… Abstract New methods and software for cloud detection and classification at high and midlatitudes using Advanced Very High Resolution Radiometer (AVHRR) data are developed for use in a wide range of meteorological, climatological, land surface, and oceanic applications within the Satellite Application Facilities (SAFs) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), including the SAF for Nowcasting and Very Short Range Forecasting Applications (NWCSAF) project. The cloud mask employs smoothly varying (dynamic) thresholds that separate fully cloudy or cloud-contaminated fields of view from cloud-free conditions. Thresholds are adapted to the actual state of the atmosphere and surface and the sun–satellite viewing geometry using cloud-free radiative transfer model simulations. Both the cloud masking and the cloud-type classification are done using sequences of grouped threshold tests that employ both spectral and textural features. The cloud-type classification divides the cloudy pixels into 10 different categories: 5 opaque cloud types, 4 semitransparent clouds, and 1 subpixel cloud category. The threshold method is fuzzy in the sense that the distances in feature space to the thresholds are stored and are used to determine whether to stop or to continue testing. They are also used as a quality indicator of the final output. The atmospheric state should preferably be taken from a short-range NWP model, but the algorithms can also run with climatological fields as input. more
Atmosphere Method NWC-SAF Software for CDR development Validation

Coupling Diffuse Sky Radiation and Surface Albedo

Author(s):
Pinty, Bernard; Lattanzio, Alessio; Martonchik, John V.; Verstraete, Michel M.; Gobron, Nadine; Taberner, Malcolm; Widlowski, Jean-Luc; Dickinson, Robert E.; Govaerts, Yves
Publication title: Journal of the Atmospheric Sciences
2005
 | Volume: 62 | Issue: 7
2005
DOI: 10.1175/JAS3479.1
Abstract:
Abstract New satellite instruments have been delivering a wealth of information regarding land surface albedo. This basic quantity describ… Abstract New satellite instruments have been delivering a wealth of information regarding land surface albedo. This basic quantity describes what fraction of solar radiation is reflected from the earth’s surface. However, its concept and measurements have some ambiguity resulting from its dependence on the incidence angles of both the direct and diffuse solar radiation. At any time of day, a surface receives direct radiation in the direction of the sun, and diffuse radiation from the various other directions in which it may have been scattered by air molecules, aerosols, and cloud droplets. This contribution proposes a complete description of the distribution of incident radiation with angles, and the implications in terms of surface albedo are given in a mathematical form, which is suitable for climate models that require evaluating surface albedo many times. The different definitions of observed albedos are explained in terms of the coupling between surface and atmospheric scattering properties. The analytical development in this paper relates the various quantities that are retrieved from orbiting platforms to what is needed by an atmospheric model. It provides a physically simple and practical approach to evaluation of land surface albedo values at any condition of sun illumination irrespective of the current range of surface anisotropic conditions and atmospheric aerosol load. The numerical differences between the various definitions of albedo for a set of typical atmospheric and surface scattering conditions are illustrated through numerical computation. more
Climate Data Records EUM-Secr Land Method

Surface albedo retrieval from Meteosat: 2. Applications

Author(s):
Pinty, Bernard; Roveda, Fausto; Verstraete, Michel M.; Gobron, Nadine; Govaerts, Yves; Martonchik, John V.; Diner, David J.; Kahn, Ralph A.
Publication title: Journal of Geophysical Research: Atmospheres
2000
 | Volume: 105 | Issue: D14
2000
DOI: 10.1029/2000JD900114
Abstract:
An advanced algorithm to retrieve the radiative properties of terrestrial surfaces sampled by the Meteosat visible instrument was derived in a compani… An advanced algorithm to retrieve the radiative properties of terrestrial surfaces sampled by the Meteosat visible instrument was derived in a companion paper [Pinty et al., this issue]. Preliminary applications of this algorithm against a limited set of Meteosat data is performed and the required procedures to screen “clear-sky” conditions only and to retrieve the “likely” solution of the inverse problem are presented and evaluated. The accumulation of results over two periods of 20 days each during the Northern Hemisphere summer and winter permits establishing sample geophysical maps of the algorithm products, including the surface albedo (i.e., directional hemispherical reflectance factors) over the entire African continent. The seasonal albedo changes occurring at a continental scale are interpreted on the basis of the most prominent environmental factors, namely the atmospheric circulation controlling the seasonal monsoon events and the biomass burning activities. The results of this study, supported by additional radiation transfer simulations, suggest that anthropogenic fire activities induce significant perturbations of the surface albedo values in the intertropical zones at the continental scale. more
Climate Data Records EUM-Secr Land Method

Surface albedo retrieval from Meteosat: 1. Theory

Author(s):
Pinty, Bernard; Roveda, Fausto; Verstraete, Michel M.; Gobron, Nadine; Govaerts, Yves; Martonchik, John V.; Diner, David J.; Kahn, Ralph A.
Publication title: Journal of Geophysical Research: Atmospheres
2000
 | Volume: 105 | Issue: D14
2000
DOI: 10.1029/2000JD900113
Abstract:
Land surface albedo constitutes a critical climatic variable, since it largely controls the actual amount of solar energy available to the Earth syste… Land surface albedo constitutes a critical climatic variable, since it largely controls the actual amount of solar energy available to the Earth system. The purpose of this paper is to establish a theory for the exploitation of space observations to solve the atmosphere/surface radiation transfer problem on an operational basis and to generate surface albedo, aerosol load, and possibly land cover change products. Surface albedo is rather variable in space and time and depends both on the structure and on the radiative characteristics of the surface, as well as on the angular and spectral distribution of radiation at the bottom of the atmosphere. Weather and climate models often use preset distributions or simple parameterizations of this environment variable, even though such approaches do not accurately account for the actual effect of the underlying surface. From a mathematical point of view, the determination of the surface albedo corresponds to the estimation of a boundary condition for the radiation transfer problem in the coupled surface-atmosphere system. A relatively large database of 10 years or more of Meteosat data has been accumulated by EUMETSAT. These data, collected at half-hour intervals over the entire Earth disk visible from longitude 0°, constitute a unique resource to describe the anisotropy of the coupled surface-atmosphere system and provide the opportunity to document changes in surface albedo which may have occurred in these regions over that period. In addition, since the coupled surface-atmosphere radiation transfer problem must be solved, the proposed procedure also yields an estimate of the spatial and temporal distribution of aerosols. The proposed inversion procedure yields a characterization of surface radiative properties that may also be used to document and monitor land surface dynamics over the portion of the globe observed by Meteosat. Results from preliminary applications and an error budget analysis are discussed in a companion paper [Pinty et al., this issue]. more
Climate Data Records EUM-Secr Land Method