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

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 (>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

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

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

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

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

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

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

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
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