Climate downscaling for regional models with a neural network: A Hawaiian example

Global ocean/atmosphere circulation models (GCMs) allow us to better understand and predict the behavior of the ocean and atmosphere at large spatial and temporal scales; however, they may be unsuited for regional studies due to their low spatial resolution. We have developed a method for downscaling GCMs data using an artificial neural network to reconstruct […]

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