A Posteriori Learning for Quasi‐Geostrophic Turbulence Parametrization-Reference-Cited by-同舟云学术

A Posteriori Learning for Quasi‐Geostrophic Turbulence Parametrization

Author:

Frezat Hugo¹²³^ORCID,Le Sommer Julien²^ORCID,Fablet Ronan³^ORCID,Balarac Guillaume¹⁴,Lguensat Redouane⁵^ORCID

Affiliation:

1. University Grenoble Alpes CNRS UMR LEGI Grenoble France

2. University Grenoble Alpes CNRS UMR IGE Grenoble France

3. IMT Atlantique CNRS UMR Lab‐STICC INRIA Team Odyssey Brest France

4. Institut Universitaire de France (IUF) Paris France

5. Institut Pierre Simon Laplace IRD Sorbonne Université Paris France

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Chemistry,Global and Planetary Change

Link

Reference112 articles.

1. Noether networks: Meta‐learning useful conserved quantities;Alet F.;Advances in Neural Information Processing Systems,2021

3. Barkmeijer J.(2009).Adjoint diagnostics for the atmosphere and ocean. Retrieved fromhttps://www.ecmwf.int/node/15243

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