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| Titel |
Improving the ensemble transform Kalman filter using a second-order Taylor approximation of the nonlinear observation operator |
| VerfasserIn |
G. Wu, X. Zheng, L. Wang, X. Liang, S. Zhang, X. Zhang |
| 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 ; 1, no. 1 ; Nr. 1, no. 1 (2014-04-11), S.543-582 |
| Datensatznummer |
250115085
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| Publikation (Nr.) |
 copernicus.org/npgd-1-543-2014.pdf |
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| Zusammenfassung |
The Ensemble Transform Kalman Filter (ETKF) assimilation scheme has
recently seen rapid development and wide application. As a specific
implementation of the Ensemble Kalman Filter (EnKF), the ETKF is
computationally more efficient than the conventional EnKF. However,
the current implementation of the ETKF still has some limitations
when the observation operator is strongly nonlinear. One problem is
that the nonlinear operator and its tangent-linear operator are
iteratively calculated in the minimization of a nonlinear objective
function similar to 4DVAR, which may be computationally
expensive. Another problem is that it uses the tangent-linear
approximation of the observation operator to estimate the
multiplicative inflation factor of the forecast errors, which may
not be sufficiently accurate.
This study seeks a way to avoid these problems. First, we apply the
second-order Taylor approximation of the nonlinear observation
operator to avoid iteratively calculating the operator and its
tangent-linear operator. The related computational cost is also
discussed. Second, we propose a scheme to estimate the inflation
factor when the observation operator is strongly
nonlinear. Experimentation with the Lorenz-96 model shows that using
the second-order Taylor approximation of the nonlinear observation
operator leads to a reduction of the analysis error compared with
the traditional linear approximation. Similarly, the proposed
inflation scheme leads to a reduction of the analysis error compared
with the procedure using the traditional inflation scheme. |
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