Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions

Machine learning has been used to represent small-scale processes, such as clouds, in atmospheric models but this can lead to instability in simulations of climate. Here, the authors demonstrate a use of machine learning in an atmospheric model that leads to stable simulations of climate at a range...

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Autores principales: Janni Yuval, Paul A. O’Gorman
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/ecda3df6d70848f78f335430e31079e4
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