Process‐Based Machine Learning Observationally Constrains Future Regional Warming Projections
Abstract We present the results of a novel process‐based machine learning method to constrain climate model uncertainty in future regional temperature projections. Ridge‐ERA5—a ridge regression model—learns coefficients to represent observed relationships between daily near‐surface temperature anoma...
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| Hlavní autoři: | , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Wiley
2025-06-01
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| Edice: | Journal of Geophysical Research: Machine Learning and Computation |
| On-line přístup: | https://doi.org/10.1029/2025JH000698 |
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