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| Titel |
Spectral diagonal ensemble Kalman filters |
| VerfasserIn |
I. Kasanický, J. Mandel, M. Vejmelka |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 22, no. 4 ; Nr. 22, no. 4 (2015-08-18), S.485-497 |
| Datensatznummer |
250120995
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| Publikation (Nr.) |
 copernicus.org/npg-22-485-2015.pdf |
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| Zusammenfassung |
| A new type of ensemble Kalman filter is developed, which is based on
replacing the sample covariance in the analysis step by its diagonal in a
spectral basis. It is proved that this technique improves the approximation
of the covariance when the covariance itself is diagonal in the spectral
basis, as is the case, e.g., for a second-order stationary random field and
the Fourier basis. The method is extended by wavelets to the case when the
state variables are random fields which are not spatially homogeneous.
Efficient implementations by the fast Fourier transform (FFT) and discrete
wavelet transform (DWT) are presented for several types of observations,
including high-dimensional data given on a part of the domain, such as radar
and satellite images. Computational experiments confirm that the method
performs well on the Lorenz 96 problem and the shallow water equations with
very small ensembles and over multiple analysis cycles. |
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