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physics.ao-ph2025
Neural ocean forecasting from sparse satellite-derived observations: a case-study for SSH dynamics and altimetry data
Daria Botvynko, Pierre Haslée, Lucile Gaultier +5
We present an end-to-end deep learning framework for short-term forecasting of global sea surface dynamics based on sparse satellite altimetry data. Building on two state-of-the-ar…
physics.ao-ph2024
Adjoint-based online learning of two-layer quasi-geostrophic baroclinic turbulence
Fei Er Yan, Hugo Frezat, Julien Le Sommer +2
For reasons of computational constraint, most global ocean circulation models used for Earth System Modeling still rely on parameterizations of sub-grid processes, and limitations…