SEIK - the unknown ensemble Kalman filter


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Lars.Nerger [ at ] awi.de

Abstract

The SEIK filter (Singular "Evolutive" Interpolated Kalman filter) hasbeen introduced in 1998 by D.T. Pham as a variant of the SEEK filter,which is a reduced-rank approximation of the Extended KalmanFilter. In recent years, it has been shown that the SEIK filter isan ensemble-based Kalman filter that uses a factorization rather thansquare-root of the state error covariance matrix. Unfortunately, theexistence of the SEIK filter as an ensemble-based Kalman filter withsimilar efficiency as the later introduced ensemble square-root Kalmanfilters, appears to be widely unknown and the SEIK filter is omittedin reviews about ensemble-based Kalman filters. To raise the attentionabout the SEIK filter as a very efficient ensemble-based Kalmanfilter, we review the filter algorithm and compare it with ensemblesquare-root Kalman filter algorithms. For a practical comparison theSEIK filter and the Ensemble Transformation Kalman filter (ETKF) areapplied in twin experiments assimilating sea level anomaly data intothe finite-element ocean model FEOM.



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Conference (Poster)
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Not peer-reviewed
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Published
Event Details
5th WMO Symposium on Data Assimilation, Melbourne, Australia, October 5 - 9.
Eprint ID
21131
Cite as
Nerger, L. , Janjic Pfander, T. , Hiller, W. and Schröter, J. (2009): SEIK - the unknown ensemble Kalman filter , 5th WMO Symposium on Data Assimilation, Melbourne, Australia, October 5 - 9 .


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