Robustness of neural network emulations of radiative transfer parameterizations in a state-of-the-art general circulation model
<p>The ability of machine-learning-based (ML-based) model components to generalize to the previously unseen inputs and its impact on the stability of the models that use these components have been receiving a lot of recent attention, especially in the context of ML-based parameterizations. At...
Main Authors: | A. Belochitski, V. Krasnopolsky |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2021-12-01
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Series: | Geoscientific Model Development |
Online Access: | https://gmd.copernicus.org/articles/14/7425/2021/gmd-14-7425-2021.pdf |
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