Assimilation of Lagrangian Data into an ocean model
Abstract
Within the framework of Global Ocean Data Assimilation Experiment (GODAE), an increasing amount of data are available. A crucial issue for oceanographers is to exploit at best these observations, in order to improve models, climatology, forecasts, etc. Thanks to the international program Argo and to more localized experiments, a new type of data is now available: positions of floats drifting at depth in the ocean. Unlike other data, mainly Eulerian, these ones are Lagrangian: the measuring instrument move in the flow. I will briefly described methods about 4D-Var assimilation of Lagrangian data in the OPAVAR ocean model, and show some results assessing the complementarity with temperature data.
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