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