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Aspects of particle filtering in high-dimensional spaces

Van Leeuwen, P. (2015) Aspects of particle filtering in high-dimensional spaces. In: Ravela, S. and Sandu, A. (eds.) Dynamic data-driven environmental systems science. Lecture notes in computer science, 8964. Springer, Heidelberg, pp. 251-262. ISBN 9783319251370

[img] Text - Accepted Version
· Restricted to Repository staff only until 27 November 2016.


To link to this article DOI: 10.1007/978-3-319-25138-7


Nonlinear data assimilation is high on the agenda in all fields of the geosciences as with ever increasing model resolution and inclusion of more physical (biological etc.) processes, and more complex observation operators the data-assimilation problem becomes more and more nonlinear. The suitability of particle filters to solve the nonlinear data assimilation problem in high-dimensional geophysical problems will be discussed. Several existing and new schemes will be presented and it is shown that at least one of them, the Equivalent-Weights Particle Filter, does indeed beat the curse of dimensionality and provides a way forward to solve the problem of nonlinear data assimilation in high-dimensional systems.

Item Type:Book or Report Section
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > National Centre for Earth Observation (NCEO)
Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:50238

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