Variational assimilation of Lagrangian Data in Oceanography
Abstract
Within the framework of the Global Ocean Data Assimilation Experiment, an increasing amount of data is available. A crucial issue for oceanographers is to exploit at best these observations, in order to improve models, climatology, forecasts, etc. 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. I will present methods and results about variational assimilation of Lagrangian data.