Deep learning for surrogate modelling of neXtSIM

Contribution tothe "11th Sea Ice data assimilation workshop in Oslo". This presentation describes the advance in the work from my PhD. This work is a contribution to the project SASIP (grant no. 353), funded by Schmidt Futures – a philanthropic initiative that seeks to improve societal out...

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Bibliographic Details
Main Authors: Durand, Charlotte, Finn, Tobias, Farchi, Alban, Bocquet, Marc, Òlason, Einar
Format: Lecture
Language:English
Published: Zenodo 2023
Subjects:
Deep learning
Sea-ice Physics
Sea-ice thickness
Surrogate modeling
Sea ice
Online Access:https://doi.org/10.5281/zenodo.7828175
Description
Summary:Contribution tothe "11th Sea Ice data assimilation workshop in Oslo". This presentation describes the advance in the work from my PhD. 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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