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Accuracy assessment of temperature trends from ERA5 and ERA5-Land
Science of the Total Environment, 2023Many environmental processes and ecological systems are being affected by the warming temperatures as a result of climate change. To correctly identify and attribute the uncertainty estimates in these systems, an investigation of temperature trend signal existing in the datasets that are used to study such systems is necessary. In this study, the trend
Meric Yilmaz
exaly +3 more sources
Consistency of spatiotemporal variability of MODIS and ERA5-Land surface warming trends over complex topography [PDF]
Environmental Science and Pollution Research, 2023 Yilmaz, Meric/0000-0001-6921-7687In this study, the trend of widely used MODIS MxD11 and MxD21 Land Surface Temperature (LST) and ERA5-Land Skin Temperature (SKT) and 2 m air temperature products were validated using 2 m air temperature trends obtained ...
Meric Yilmaz
exaly +2 more sources
ERA5-Land Reanalysis Temperature Data Addressing Heatwaves in Portugal
2023Abstract: In this research, heatwaves in Portugal were analysed using high-resolution daily minimum and maximum temperature data (Tmin and Tmax) from the European Reanalysis of Global Climate Observations (ERA5-Land) for the period from 1 October 1980 to 30 September 2021 (41 hydrological years) at four differentiated climatological locations in the ...
Espinosa, Luis Angel +2 more
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Evaluating the performance of key ERA-Interim, ERA5 and ERA5-Land climate variables across Siberia [PDF]
International Journal of ClimatologyReanalysis datasets provide a continuous picture of the past climate for every point on Earth. They are especially useful in areas with few direct observations, such as Siberia.
Gareth J Marshall +2 more
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Monthly surface energy fluxes in ERA5-Land reanalysis: a comparison with FLUXNET observations.
2022<p>We compare Earth's surface energy balance components (monthly mean radiation and energy fluxes) from the ERA5-Land reanalysis with their measured equivalents from FLUXNET stations in the period 2001-2018. The comparison (FLUXNET station vs.
Petr Skalak +3 more
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Spatio-temporal AI downscaling of ERA5-land precipitation estimates
Generative deep learning models have been proven to have great potential for precipitation nowcasting and downscaling applications. spateGAN [1] is a conditional generative neural network that we initially developed for spatio-temporal superresolution of radar-rainfall in Germany.Luca Glawion +4 more
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Meteorological drought variability in Poland by means of the ERA5-Land dataset
In this work, meteorological drought in Poland has been characterized considering the Standardized Precipitation Index (SPI) evaluated at different timescales (3, 6, 12 and 24 months) from the ERA5-Land monthly dataset provided by ECMWF under the framework of Copernicus Climate Change Service Programme.Antonio Romio +6 more
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