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| Titel |
The impact of nonlinearity in Lagrangian data assimilation |
| VerfasserIn |
A. Apte, C. K. R. T. Jones |
| 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 ; 20, no. 3 ; Nr. 20, no. 3 (2013-05-23), S.329-341 |
| Datensatznummer |
250018971
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| Publikation (Nr.) |
 copernicus.org/npg-20-329-2013.pdf |
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| Zusammenfassung |
| The focus of this paper is on how two main manifestations of
nonlinearity in low-dimensional systems – shear around a center fixed
point (nonlinear center) and the differential divergence of
trajectories passing by a saddle (nonlinear saddle) – strongly affect
data assimilation. The impact is felt through their leading to
non-Gaussian distribution functions. The major factors that control
the strength of these effects is time between observations, and
covariance of the prior relative to covariance of the observational
noise. Both these factors – less frequent observations and larger prior
covariance – allow the nonlinearity to take hold. To expose these
nonlinear effects, we use the comparison between exact posterior
distributions conditioned on observations and the ensemble Kalman
filter (EnKF) approximation of these posteriors. We discuss the
serious limitations of the EnKF in handling these effects. |
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