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Chaotic Systems: Theory and Applications - Selected Papers from the 2nd Chaotic Modeling and Simulation International Conference (CHAOS2009)

DOI: 10.1142/9789814299725_0004

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Some Issues and Results on the EnKF and Particle Filters for Meteorological Models

Journal article published in 2010 by Christophe Baehr, Olivier Pannekoucke ORCID
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This paper is available in a repository.

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Abstract

In this paper we examine the links between Ensemble Kalman Filters (EnKF) and Particle Filters (PF). EnKF can be seen as a Mean-Field process with a PF approximation. We explore the problem of dimensionality on a toy model. To by-pass this difficulty, we suggest using Local Particle Filters (LPF) to catch non-lineartity and feed larger scale EnKF. To go one step forward we conclude with a real application and present the filtering of perturbed measurements of atmospheric wind in the domain of turbulence. This example is the cornerstone of the LPF for the assimilation of atmospheric turbulent wind. These local representation tech-niques will be use in further works to assimilate singular data of turbulence linked parameters in non-hydrostatic models.