Friday, 15:45 - 16:10 h, Room: H 3003A

 

Annick Sartenaer
Derivative-free optimization for large-scale nonlinear data assimilation problems

Coauthors: Serge Gratton, Patrick Laloyaux

 

Abstract:
Data assimilation consists in techniques to combine observations with a numerical prediction model. The goal is to produce the best estimate of the current state of the system. Two different approaches are used in data assimilation algorithms: 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 nonlinear weighted least-squares problem called 4D-Var (four-dimensional variational problem). In both approaches, evaluating derivatives is challenging as one needs to compute the Jacobian of the model operator. The Ensemble Kalman Filter (EnKF) provides a suitable derivative-free alternative for the first
approach by using a Monte-Carlo implementation on the Kalman filter equations. However, no derivative-free variant of the variational approach has been proposed so far. In this talk, we present such a variant, based on a technique to build and explore a sequence of appropriate low dimensional subspaces. Numerical illustration is shown on a shallow water data assimilation problem, including a comparison with the Ensemble Kalman Filter approach.

 

Talk 2 of the invited session Fri.3.H 3003A
"Novel applications of derivative-free and simulation-based optimization" [...]
Cluster 6
"Derivative-free & simulation-based optimization" [...]

 

  There are three major facts that should be watched out for in all payday loans in the United States. Of course, the choice is not that easy, as there exist great number of different preparations. Notwithstanding, Cialis is the one that definitely differs from all other products.