188 citations · 762 across the 33 of their papers we have counts for
6 papers · 1 filter
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)…
A VAE Approach to Sample Multivariate Extremes
Nicolas Lafon, Philippe Naveau, Ronan Fablet
Generating accurate extremes from an observational data set is crucial when seeking to estimate risks associated with the occurrence of future extremes which could be larger than t…
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Sibo Cheng, Cesar Quilodran-Casas, Said Ouala +14
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical a…
Reduction of rain-induced errors for wind speed estimation on SAR observations using convolutional neural networks
Aurélien Colin, Pierre Tandeo, Charles Peureux +2
Synthetic Aperture Radar is known to be able to provide high-resolution estimates of surface wind speed. These estimates usually rely on a Geophysical Model Function (GMF) that has…
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…