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 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 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

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

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

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

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

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

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

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
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