61 citations · 133 across the 11 of their papers we have counts for
11 papers
OceanBench: The Sea Surface Height Edition
J. Emmanuel Johnson, Quentin Febvre, Anastasia Gorbunova +4
The ocean profoundly influences human activities and plays a critical role in climate regulation. Our understanding has improved over the last decades with the advent of satellite…
Training neural mapping schemes for satellite altimetry with simulation data
Quentin Febvre, Julien Le Sommer, Clément Ubelmann +1
Satellite altimetry combined with data assimilation and optimal interpolation schemes have deeply renewed our ability to monitor sea surface dynamics. Recently, deep learning (DL)…
Scale-aware neural calibration for wide swath altimetry observations
Quentin Febvre, Clément Ubelmann, Julien Le Sommer +1
Sea surface height (SSH) is a key geophysical parameter for monitoring and studying meso-scale surface ocean dynamics. For several decades, the mapping of SSH products at regional…
Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables
J. Emmanuel Johnson, Redouane Lguensat, Ronan Fablet +2
Optimal Interpolation (OI) is a widely used, highly trusted algorithm for interpolation and reconstruction problems in geosciences. With the influx of more satellite missions, we h…
Inversion of sea surface currents from satellite-derived SST-SSH synergies with 4DVarNets
Ronan Fablet, Bertrand Chapron, Julien Le Sommer +1
Satellite altimetry is a unique way for direct observations of sea surface dynamics. This is however limited to the surface-constrained geostrophic component of sea surface velocit…
A posteriori learning for quasi-geostrophic turbulence parametrization
Hugo Frezat, Julien Le Sommer, Ronan Fablet +2
The use of machine learning to build subgrid parametrizations for climate models is receiving growing attention. State-of-the-art strategies address the problem as a supervised lea…