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Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions
Global climate models represent small-scale processes such as convection using subgrid models known as parameterizations, and these parameterizations contribute substantially to uncertainty in climate projections. Machine learning of new parameterizations from high-resolution model output is a promi...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335176/ https://www.ncbi.nlm.nih.gov/pubmed/32620769 http://dx.doi.org/10.1038/s41467-020-17142-3 |