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Less is more: error-distance scaling relation for data-efficient kilometer-scale downscaling of extreme heat

Ahmed Marey et al.
arXiv CS · Papers
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machine-learningneural-networks
Extreme heat is where urban adaptation needs kilometer-scale data the most, but the simulations training a downscaler can cost more than they save, and how much is needed has not been identified. We measured it with CASPER, a U-Net with a structure-preserving loss downscaling 32 km reanalysis to 1 k
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