The role of model dynamics in ensemble Kalman filter performance for chaotic systems
Name
Ng-2011-The role model of dynamics.pdf
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1.26 MB
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Author(s)
NG, GENE-HUA CRYSTAL
MCLAUGHLIN, DENNIS
ENTEKHABI, DARA
AHANIN, ADEL
McLaughlin, Dennis
Entekhabi, Dara
Ahanin, Adel
Date Issued
October 2011
Journal
Tellus A
Publisher
Co-Action Publishing
Citation
NG, GENE-HUA CRYSTAL, DENNIS MCLAUGHLIN, DARA ENTEKHABI, and ADEL AHANIN. “The Role of Model Dynamics in Ensemble Kalman Filter Performance for Chaotic Systems.” Tellus A 63, no. 5 (September 15, 2011): 958–977.
Version
Final published version
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 nonlinearity 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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1111/j.1600-0870.2011.00539.x
