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Intercomparison of data-driven and learning-based interpolations of along-track Nadir and wide-swath Swot altimetry observations ArchiMer
Beauchamp, Maxime; Fablet, Ronan; Ubelmann, Clément; Ballarotta, Maxime; Chapron, Bertrand.
Over the last years, a very active field of research aims at exploring new data-driven and  learning-based methodologies to propose computationally efficient strategies able to benefit from  the large amount of observational remote sensing and numerical simulations for the reconstruction,  interpolation and prediction of high-resolution derived products of geophysical fields. In this paper,  we investigate how they might help to solve for the oversmoothing of the state-of-the-art optimal  interpolation (OI) techniques in the reconstruction of sea surface height (SSH) spatio-temporal  fields. We focus on two small 10° x 10° GULFSTREAM and 8° x 10° OSMOSIS regions, part  of the North-Atlantic basin: the GULFSTREAM area is mainly driven by energetic...
Tipo: Text Palavras-chave: Data-driven and learning-based approaches; Interpolation; Benchmarking; Nadir and SWOT altimetric satellite data; Sea surface height (SSH).
Ano: 2020 URL: https://archimer.ifremer.fr/doc/00648/76052/76996.pdf
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