Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6747-2022
https://doi.org/10.5194/gmd-15-6747-2022
Model evaluation paper
 | 
06 Sep 2022
Model evaluation paper |  | 06 Sep 2022

Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44

Jorge Baño-Medina, Rodrigo Manzanas, Ezequiel Cimadevilla, Jesús Fernández, Jose González-Abad, Antonio S. Cofiño, and José Manuel Gutiérrez

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Latest update: 24 Jun 2024
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Short summary
Deep neural networks are used to produce downscaled regional climate change projections over Europe for temperature and precipitation for the first time. The resulting dataset, DeepESD, is analyzed against state-of-the-art downscaling methodologies, reproducing more accurately the observed climate in the historical period and showing plausible future climate change signals with low computational requirements.