Articles | Volume 31, issue 1
Research article
13 Feb 2024
Research article |  | 13 Feb 2024

A two-fold deep-learning strategy to correct and downscale winds over mountains

Louis Le Toumelin, Isabelle Gouttevin, Clovis Galiez, and Nora Helbig

Model code and software

louisletoumelin/neural_network_and_devine: le_toumelin_et_al_2024 (le_toumelin_2024) Louis Le Toumelin

Short summary
Forecasting wind fields over mountains is of high importance for several applications and particularly for understanding how wind erodes and disperses snow. Forecasters rely on operational wind forecasts over mountains, which are currently only available on kilometric scales. These forecasts can also be affected by errors of diverse origins. Here we introduce a new strategy based on artificial intelligence to correct large-scale wind forecasts in mountains and increase their spatial resolution.