On ensemble representation of the observation-error covariance in the Ensemble Kalman Filter |
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| Authors: | Email author" target="_blank">J D?KepertEmail author |
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| Institution: | (1) Bureau of Meteorology Research Centre, GPO Box 1289K, Melbourne, Vic, 3001, Australia |
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| Abstract: | Evensen (2003) presents a modification of the Ensemble Kalman Filter (EnKF), in which the observation-error and background-error covariance matrices are both represented by ensembles, in contrast to the usual practice, where only the background error is so represented. It is shown that this modification can cause the ensemble to collapse to a single member, in the common situation where the number of observations is more than twice the number of ensemble members, and to be rank-deficient when the number of observations is greater than or equal to the ensemble size. It is also shown that some further modifications to the scheme, presented by Evensen as offering numerical efficiencies, can prevent this collapse. However, these latter modifications are shown in some simple numerical examples to require tuning to produce acceptable results, which are nevertheless inferior to those of the standard EnKF.Acknowledgements The author acknowledges useful discussions with Peter Steinle, and other participants at the EnKF workshop held in BMRC in November, 2003. |
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| Keywords: | Data assimilation Ensemble Kalman Filter Observation-error covariance |
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