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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

Abstract/Summary

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
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
ID Code:33549
Publisher:Springer

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