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...
Main Authors: | Yuval, Janni (Author), O'Gorman, Paul (Author) |
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Other Authors: | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences (Contributor) |
Format: | Article |
Language: | English |
Published: |
Springer Science and Business Media LLC,
2020-08-13T20:41:19Z.
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Subjects: | |
Online Access: | Get fulltext |
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