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
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
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
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