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About this paper
Daria Botvynko, Pierre Haslée, Lucile Gaultier, Bertrand Chapron, Clement de Boyer Montégut, Anass El Aouni, Julien Le Sommer, Ronan Fablet
The authors adapt 4DVarNet to forecast seven days of complete sea-level fields directly from 14 days of sparse satellite observations. Trained on reanalysis with synthetic sampling masks, it is evaluated against real observations. It outperforms GLO12 on global nRMSE, a score where higher is better; this supports feasibility in this case study, not universal superiority or operational readiness.
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