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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 |
2198-5634
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 2, no. 1 ; Nr. 2, no. 1 (2015-01-27), S.115-143 |
| Datensatznummer |
250115145
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| Publikation (Nr.) |
 copernicus.org/npgd-2-115-2015.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
aproximation 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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