Articles | Volume 16, issue 8
https://doi.org/10.5194/gmd-16-2119-2023
https://doi.org/10.5194/gmd-16-2119-2023
Development and technical paper
 | 
19 Apr 2023
Development and technical paper |  | 19 Apr 2023

4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry

Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet

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Cited articles

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Short summary
4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.