The role of model dynamics in ensemble Kalman filter performance for chaotic systems

Tellus, Series A: Dynamic Meteorology and Oceanography
By: , and 

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Abstract

The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or 'diverging', when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter's update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as non-linearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics. ?? 2011 The Authors Tellus A ?? 2011 John Wiley & Sons A/S.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title The role of model dynamics in ensemble Kalman filter performance for chaotic systems
Series title Tellus, Series A: Dynamic Meteorology and Oceanography
DOI 10.1111/j.1600-0870.2011.00539.x
Volume 63
Issue 5
Year Published 2011
Language English
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Tellus, Series A: Dynamic Meteorology and Oceanography
First page 958
Last page 977