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Titel |
Four-dimensional ensemble variational (4D-En-Var) data assimilation for the HIgh Resolution Limited Area Model (HIRLAM) |
VerfasserIn |
N. Gustafsson, J. Bojarova |
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 ; 21, no. 4 ; Nr. 21, no. 4 (2014-07-14), S.745-762 |
Datensatznummer |
250120927
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Publikation (Nr.) |
copernicus.org/npg-21-745-2014.pdf |
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Zusammenfassung |
A four-dimensional ensemble variational (4D-En-Var) data assimilation has been
developed for a limited area model. The integration of tangent linear and
adjoint models, as applied in standard 4D-Var, is replaced with the use of an
ensemble of non-linear model states to estimate four-dimensional background
error covariances over the assimilation time window. The computational costs
for 4D-En-Var are therefore significantly reduced in comparison with standard
4D-Var and the scalability of the algorithm is improved.
The flow dependency of 4D-En-Var assimilation increments is demonstrated in
single simulated observation experiments and compared with corresponding
increments from standard 4D-Var and Hybrid 4D-Var ensemble assimilation
experiments. Real observation data assimilation experiments carried out over
a 6-week period show that 4D-En-Var outperforms standard 4D-Var as well as
Hybrid 4D-Var ensemble data assimilation with regard to forecast quality
measured by forecast verification scores. |
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