Publications 2001

​A semi-evolutive partially local filter for data assimilation
I. Hoteit, D.T. Pham, and J. Blum
Marine Pollution Bulletin, 43, 164-174, 2001
I. Hoteit, D.T. Pham, and J. Blum
Data assimilation; EOF analysis; Reduced Kalman filtering; SEEK filter
2001
​he singular evolutive extended Kalman (SEEK) filter has been proposed recently by Pham et al. (1997) for data assimilation into numerical oceanic models. This filter has been applied in different realistic ocean frameworks and has provided satisfactory results (Pham et al., 1997; Verron et al., 1998). However, the SEEK filter remains expensive in real operational assimilation. To reduce cost and obtain a better representativity, we introduce the idea `local correction basis'. Such basis however cannot be made to evolve according to the model without destroying its locality property. Therefore we shall keep this basis fixed and we augment it by a few global basis vectors which evolve. The resulting semi-evolutive partially local filter is much less costly to implement than the SEEK filter and yet can yield better results. In the first application, validation twin experiments are conducted in a realistic setting of the OPA model over the tropical Pacific Ocean.
 
 
 DOI: 10.1016/S0025-326X(01)00079-0