Non-negative Decomposition of Sea Surface Dynamics from Multi-source Ocean Remote Sensing Data

Manuel Lopez Radcenco 1, 2 Abdeldjalil Aïssa-El-Bey 3, 2 Pierre Ailliot 1, 4 Pierre Tandeo 1, 2 Ronan Fablet 1, 2
1 Lab-STICC_TB_CID_TOMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Lab-STICC_TB_CACS_COM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : The growing availability of multi-source ocean remote sensing data is a key factor for improving our understanding of upper ocean dynamics, ocean circulation and atmospheric-ocean interactions. Following an ongoing body of work that investigates mesoscale upper ocean dynamics from linear couplings between SST (sea surface temperature) and SSH (sea surface height), we propose a novel observation-driven framework for the identification and characterization of sea surface dynamical modes. It relies on a multi-modal decomposition of SST-SSH relationships. Our findings suggest that upper ocean dynamics may be decomposed as the superimposition of several dynamical modes, rather than mutually exclusive ones as investigated in previous work. Our study stresses the relevance of a non-negative bi-modal additive decomposition to capture the complex space-time variability of mesoscale upper ocean dynamics.
Type de document :
Poster
ACO 2016 : A connected ocean: new approaches, new technologies, new challenges for knowledge of ocean processes, Oct 2016, Brest, France
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https://hal.archives-ouvertes.fr/hal-01611018
Contributeur : Bibliothèque Télécom Bretagne <>
Soumis le : jeudi 5 octobre 2017 - 12:29:03
Dernière modification le : mercredi 11 juillet 2018 - 07:50:11

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  • HAL Id : hal-01611018, version 1

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Manuel Lopez Radcenco, Abdeldjalil Aïssa-El-Bey, Pierre Ailliot, Pierre Tandeo, Ronan Fablet. Non-negative Decomposition of Sea Surface Dynamics from Multi-source Ocean Remote Sensing Data. ACO 2016 : A connected ocean: new approaches, new technologies, new challenges for knowledge of ocean processes, Oct 2016, Brest, France. 〈hal-01611018〉

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