Deep learning subgrid-scale parametrisations for short-term forecasting of sea-ice dynamics with a Maxwell elasto-brittle rheology
<p>We introduce a proof of concept to parametrise the unresolved subgrid scale of sea-ice dynamics with deep learning techniques. Instead of parametrising single processes, a single neural network is trained to correct all model variables at the same time. This data-driven approach is applied...
Main Authors: | T. S. Finn, C. Durand, A. Farchi, M. Bocquet, Y. Chen, A. Carrassi, V. Dansereau |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2023-07-01
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Series: | The Cryosphere |
Online Access: | https://tc.copernicus.org/articles/17/2965/2023/tc-17-2965-2023.pdf |
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