Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 14
Articles | Volume 17, issue 14
https://doi.org/10.5194/gmd-17-5459-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-5459-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 14
Model description paper
 | 
22 Jul 2024
Model description paper |  | 22 Jul 2024

TorchClim v1.0: a deep-learning plugin for climate model physics

David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett

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Latest update: 13 Dec 2024
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Short summary
Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
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