Deep learning can correct model errors from the subgrid-scale for sea-ice dynamics

Poster contribution tothe "11th Sea Ice data assimilation workshop in Oslo". This poster summarizes the work currently under discussion for" The Cryosphere ". This work is a contribution to the project SASIP (grant no. 353), funded by Schmidt Futures – a philanthropic initiative...

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Bibliographic Details
Main Authors: Finn, Tobias, Durand, Charlotte, Farchi, Alban, Bocquet, Marc, Chen, Yumeng, Carrassi, Alberto, Dansereau, Véronique
Format: Conference Object
Language:English
Published: Zenodo 2023
Subjects:
machine learning
sea-ice modelling
Sea ice
Online Access:https://doi.org/10.5281/zenodo.7788085
Description
Summary:Poster contribution tothe "11th Sea Ice data assimilation workshop in Oslo". This poster summarizes the work currently under discussion for" The Cryosphere ". This work is a contribution to the project SASIP (grant no. 353), funded by Schmidt Futures – a philanthropic initiative that seeks to improve societal outcomes through the development of emerging science and technologies.

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