Results 21 to 30 of about 109,140 (374)
On the modern deep learning approaches for precipitation downscaling [PDF]
Earth Science Informatics, 2022 Deep Learning (DL) based downscaling has recently become a popular tool in earth sciences. Multiple DL methods are routinely used to downscale coarse-scale precipitation data to produce more accurate and reliable estimates at local scales.
B. Kumar +7 more
semanticscholar +1 more source
Deep Learning Regional Climate Model Emulators: A Comparison of Two Downscaling Training Frameworks
Journal of Advances in Modeling Earth Systems, 2023 Regional climate models (RCMs) have a high computational cost due to their higher spatial resolution compared to global climate models (GCMs). Therefore, various downscaling approaches have been developed as a surrogate for the dynamical downscaling of ...
Marijn van der Meer +2 more
semanticscholar +1 more source
Regional climate downscaling over Europe: perspectives from the EURO-CORDEX community
Regional Environmental Change, 2020 The European CORDEX (EURO-CORDEX) initiative is a large voluntary effort that seeks to advance regional climate and Earth system science in Europe. As part of the World Climate Research Programme (WCRP) - Coordinated Regional Downscaling Experiment ...
D. Jacob +66 more
semanticscholar +1 more source
Earth's Future, 2022 Global climate models (GCMs) are essential for investigating climate change, but their coarse scale limits their efficacy for climate adaptation planning at the regional scales where climate impacts manifest.
G. Di Virgilio +10 more
semanticscholar +1 more source
Review on spatial downscaling of satellite derived precipitation estimates
Environmental Earth Sciences, 2023 The present work aims at reviewing and identifying gaps in knowledge and future perspectives of satellite-derived precipitation downscaling algorithms. Here, various aspects related to statistical and dynamical downscaling approaches of the precipitation
Maria Kofidou +2 more
semanticscholar +1 more source
Evaluating Downscaling Factors of Microwave Satellite Soil Moisture Based on Machine Learning Method
Remote Sensing, 2021 Downscaling microwave remotely sensed soil moisture (SM) is an effective way to obtain spatial continuous SM with fine resolution for hydrological and agricultural applications on a regional scale.
Hao Sun, Yajing Cui
doaj +1 more source
Journal of Climate, 2021 Global models comprising the sixth-generation Coupled Climate Model Intercomparison Project (CMIP6) are downscaled using a very high-resolution but simplified coupled atmosphere–ocean tropical cyclone model, as a means of estimating the response of ...
K. Emanuel
semanticscholar +1 more source
Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields With a Generative Adversarial Network [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2020 Generative adversarial networks (GANs) have been recently adopted for super-resolution, an application closely related to what is referred to as “downscaling” in the atmospheric sciences: improving the spatial resolution of low-resolution images.
J. Leinonen, D. Nerini, A. Berne
semanticscholar +1 more source
PreciPatch: A Dictionary-based Precipitation Downscaling Method
Remote Sensing, 2020 Climate and weather data such as precipitation derived from Global Climate Models (GCMs) and satellite observations are essential for the global and local hydrological assessment.
Mengchao Xu +8 more
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Towards an Accurate and Reliable Downscaling Scheme for High-Spatial-Resolution Precipitation Data
Remote Sensing, 2023 Accurate high-spatial-resolution precipitation is significantly important in hydrological and meteorological modelling, especially in rain-gauge-sparse areas.
Honglin Zhu +3 more
doaj +1 more source