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Ocean Surface Topography from Space
Advanced Altimeter Data Assimilation for Physical Ocean Prediction and Ecosystem Monitoring
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Jacques Verron

Joaquim Ballabrera
Eric Blayo, Laurent Debreu, Maelle Nodet, Arthur Vidard
Laurent Bertino, Geir Evensen
Jean Michel Brankart, Pierre Brasseur, Emmanuel Cosme, Achim Wirth, Bernard Barnier, Thierry Penduff
Lionel Gourdeau
Jens Schröter
Peter-Jan van Leeuwen


The general objectives of this project are to implement and validate innovative methodologies for the assimilation of altimeter data and other data into ocean and ecosystem models in order to contribute to the development of operational oceanography in the prospect of programmes such as GMES and to the development of scientific activities on the role of the ocean on climate (CLIVAR, IMBER) and the related observational components (GOOS).

Data assimilation methodological approaches will be multiple, taking advantages of the most recent advances in matters of statistical optimal estimation and optimal control theories. The comparisons of these various approaches and the joint use of their respective capabilities will be a central issue.

Altimetry from JASON-1, and from the forthcoming JASON-2/OSTM, will be the primary source of data for this project, in conjunction with ENVISAT and SARAL/AltiKa for altimetry, GRACE and GOCE for gravimetry and SMOS for salinity. But a particular attention will be brought to the use of multiple data of various nature including in-situ observations and to their optimal complementarity to altimetry.

The conjugate consideration of altimeter data and numerical models via data assimilation will allow to address several essential oceanographic questions:

  • improve our understanding of the role of the mesoscale variability on the general circulation and our capability for monitoring and forecasting the mesoscale/submesoscale variability,
  • improve the scientific understanding, monitoring and forecasting of seasonal to interannual climate anomalies such as El Nino and North Atlantic climate variability,
  • demonstrate the capability of coupled physico-biological systems with data assimilation to provide a rationale basis for the future management of living resources, especially in coastal regions and for the understanding of the carbon dioxide storage and fluxes.

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