Improving Mesoscale Altimetric Data From a Multitracer Convolutional Processing of Standard Satellite-Derived Products

Type Article
Date 2018-05
Language English
Author(s) Fablet Ronan1, Verron Jacques2, Mourre Baptiste3, Chapron Bertrand4, Pascual Ananda5
Affiliation(s) 1 : Inst Mines Telecom Atlantique, UMR LabSTICC 6285, FR-29238 Brest, France.
2 : CNRS, Inst Geosci Environm, UMR 5183, Lab Glaciol & Geophys Environm, FR-38058 Grenoble, France.
3 : Sistema Observ & Prediccio Costaner Illes Balears, Balearic Isl Coastal & Forecasting Syst, E-07121 Palma De Mallorca, Spain.
4 : IFREMER, Lab Oceanog Phys & Spatiale, FR-29238 Brest, France.
5 : Mediterranean Inst Adv Studies CSIC UIB, E-07190 Esporles, Spain.
Source Ieee Transactions On Geoscience And Remote Sensing (0196-2892) (Ieee-inst Electrical Electronics Engineers Inc), 2018-05 , Vol. 56 , N. 5 , P. 2518-2525
DOI 10.1109/TGRS.2017.2750491
WOS© Times Cited 10
Keyword(s) Convolutional models, observing system simulation experiment (OSSE), sea surface height (SSH), sea surface temperature (SST), superresolution, Western Mediterranean Sea
Abstract Multisatellite measurements of altimeter-derived sea surface height (SSH) have provided a wealth of information on the ocean. Yet, horizontal scales below 100 km remain scarcely resolved. Especially, in the Mediterranean Sea, an important fraction of the mesoscale range, characterized by a small Rossby radius of deformation of 15-20 km, is not properly retrieved by altimeter-derived gridded products. Here, we investigate a novel processing of AVISO products with a view to resolving the horizontal scales sensed by current along-track altimeter data. The key feature of our framework is the use of linear convolutional operators to model the fine-scale SSH detail as a function of different sea surface fields, especially optimally interpolated SSH and sea surface temperature (SST). The proposed model embeds the surface quasi-geostrophic SST-SSH synergy as a special case. Using an observing system simulation experiment with simulated SSH data from model outputs in the Western Mediterranean Sea, we show that the proposed approach has the potential for improving current optimal interpolations of gridded altimeter-derived SSH fields by more than 20% in terms of relative SSH and kinetic energy mean square error, as well as in terms of spectral signatures for horizontal scales ranging from 30 to 100 km. Our results also suggest that SST-SSH relationship may only play a secondary role compared with the interscale SSH cascade. We further discuss the relevance of the proposed approach in the context of future altimetric satellite missions.
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Fablet Ronan, Verron Jacques, Mourre Baptiste, Chapron Bertrand, Pascual Ananda (2018). Improving Mesoscale Altimetric Data From a Multitracer Convolutional Processing of Standard Satellite-Derived Products. Ieee Transactions On Geoscience And Remote Sensing, 56(5), 2518-2525. Publisher's official version : , Open Access version :