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Interpretable Multiscale Machine Learning‐Based Parameterizations of Convection for ICON

Abstract Machine learning (ML)‐based parameterizations have been developed for Earth System Models (ESMs) with the goal to better represent subgrid‐scale processes or to accelerate computations. ML‐based parameterizations within hybrid ESMs have successfully learned subgrid‐scale processes from shor...

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Detalles Bibliográficos
Principais autores: Helge Heuer, Mierk Schwabe, Pierre Gentine, Marco A. Giorgetta, Veronika Eyring
Formato: Artigo
Idioma:Inglês
Publicado: American Geophysical Union (AGU) 2024-08-01
Series:Journal of Advances in Modeling Earth Systems
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Acceso en liña:https://doi.org/10.1029/2024MS004398
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