Regression Forest Approaches to Gravity Wave Parameterization for Climate Projection
Abstract We train random and boosted forests, two machine learning architectures based on regression trees, to emulate a physics‐based parameterization of atmospheric gravity wave momentum transport. We compare the forests to a neural network benchmark, evaluating both offline errors and online perf...
| Main Authors: | , |
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| 格式: | 文件 |
| 语言: | English |
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American Geophysical Union (AGU)
2024-07-01
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| 丛编: | Journal of Advances in Modeling Earth Systems |
| 主题: | |
| 在线阅读: | https://doi.org/10.1029/2023MS004184 |