A dynamical systems framework for intermittent data assimilation
- 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.
| Author details: | Sebastian ReichORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1007/s10543-010-0302-4 |
| ISSN: | 0006-3835 |
| Title of parent work (English): | BIT : numerical mathematics ; the leading applied mathematics journal for all computational mathematicians |
| Publisher: | Springer |
| Place of publishing: | Dordrecht |
| Publication type: | Article |
| Language: | English |
| Year of first publication: | 2011 |
| Publication year: | 2011 |
| Release date: | 2017/03/26 |
| Tag: | Data assimilation; Dynamical systems; Ensemble Kalman filter; Nonlinear filters; Optimal transportation |
| Volume: | 51 |
| Issue: | 1 |
| Number of pages: | 15 |
| First page: | 235 |
| Last Page: | 249 |
| Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
| Peer review: | Referiert |
