FN Archimer Export Format
PT C
TI Data-driven and learning-based interpolations of along-track Nadir and wide-swath SWOT altimetry observations
BT 
AF BEAUCHAMP, Maxime
   FABLET, Ronan
   UBELMANN, Clement
   BALLAROTTA, Maxime
   CHAPRON, Bertrand
AS 1:1;2:1;3:2;4:3;5:4;
FF 1:;2:;3:;4:;5:PDG-ODE-LOPS-SIAM;
C1 IMT Atlantique Bretagne Pays Loire, Brest, France.
   Ocean Next, Grenoble, France.
   Collecte Localisat Satellites CLS, Ramonville St Agne, France.
   IFREMER, Plouzane, France.
C2 IMT ATLANTIQUE, FRANCE
   OCEAN NEXT, FRANCE
   CLS, FRANCE
   IFREMER, FRANCE
SI BREST
SE PDG-ODE-LOPS-SIAM
UM LOPS
IN WOS Ifremer UMR
   copubli-france
UR https://archimer.ifremer.fr/doc/00739/85150/90134.pdf
   https://archimer.ifremer.fr/doc/00739/85150/90135.pdf
LA English
DT Proceedings paper
AB 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 a small region, part of the GULFSTREAM and mainly driven by energetic mesoscale dynamics. Based on an Observation System Simulation Experiment (OSSE), we will use the NATL60 high resolution deterministic ocean simulation of the North Atlantic to generate two types of pseudo altimetric observational dataset: along-track nadir data for the current capabilities of the observation system and wide-swath SWOT data in the context of the upcoming SWOT mission. We briefly introduce the analog data assimilation (AnDA), an up-to-date version of the DINEOF algorithm, and a new NN-based end-to-end learning framework for the representation of spatio-temporal irregulary-sampled data. We evaluate how some of these methods are a significant improvements, particularly by catching up the small scales ranging up to 30-40km, inaccessible by the conventional methods so far. A clear gain is also demonstrated when assimilating jointly wide-swath SWOT and (agreggated) along-track nadir observations.
PY 2020
CT CI2020: Proceedings of the 10th International Conference on Climate InformaticsSeptember 2020. ISBN: 978-1-4503-8848-1. pp. 22–29
DI 10.1145/3429309.3429313
ID 85150
ER

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