### Annick Sartenaer (Namur Center of Complex Systems (naXys) and Department of Mathematics, Université de Namur, Belgium)

#### Data assimilation in oceanography and weather forecasting

*Wednesday 12 June 2013 at 15.30, JCMB 6206*

##### Abstract

Data assimilation is a methodology for estimating the initial state of a
dynamical system by combining the information from observational data and from
a numerical prediction model that describes the evolution of the system. The
most important fields of application of data assimilation are the ocean and
weather forecasts. In this talk, we briefly survey the two main approaches
used in data assimilation: the sequential one, based on the statistical
estimation theory (Kalman filter) and the variational one, based on the
optimal control theory. This last approach amounts to solve a very large
weighted nonlinear least-squares problem called 4D-Var (four-dimensional
variational problem).

Focussing on the solution of the 4D-Var problem, we discuss two challenging
issues in the context of large-scale operational data assimilation:
preconditioning techniques, for accelerating the convergence, and
derivative-free techniques, to avoid the computation of derivatives.

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