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A dynamical systems framework for intermittent data assimilation

Reich, S. (2011) A dynamical systems framework for intermittent data assimilation. BIT Numerical Mathematics, 51 (1). pp. 235-249. ISSN 1572-9125

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To link to this item DOI: 10.1007/s10543-010-0302-4


We consider the problem of discrete time filtering (intermittent data assimilation) for differential equation models and discuss methods for its numerical approximation. The focus is on methods based on ensemble/particle techniques and on the ensemble Kalman filter technique in particular. We summarize as well as extend recent work on continuous ensemble Kalman filter formulations, which provide a concise dynamical systems formulation of the combined dynamics-assimilation problem. Possible extensions to fully nonlinear ensemble/particle based filters are also outlined using the framework of optimal transportation theory.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
ID Code:33549

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