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Journal of Climate
AbstractDownward surface solar radiation (SSR) is a crucial component of the Global Energy Balance, affecting temperature and the hydrological cycle profoundly, and it provides crucial information about climate change. Many studies have examined SSR trends, however they are often concentrated on specific regions due to limited spatial coverage of ground based observation stations. To overcome this spatial limitation, this study performs a spatial interpolation based on a machine learningdoi:10.1175/jcli-d-21-0165.1 fatcat:pvm4o7q5irazzavl7rxvhu7ikm