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| Titel |
Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM – perfect model experiments |
| VerfasserIn |
J. Liu, E. J. Fertig, H. Li, E. Kalnay, B. R. Hunt, E. J. Kostelich, I. Szunyogh, R. Todling |
| 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 ; 15, no. 4 ; Nr. 15, no. 4 (2008-08-05), S.645-659 |
| Datensatznummer |
250012717
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| Publikation (Nr.) |
 copernicus.org/npg-15-645-2008.pdf |
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| Zusammenfassung |
| This paper compares the performance of the Local Ensemble Transform Kalman
Filter (LETKF) with the Physical-Space Statistical Analysis System (PSAS)
under a perfect model scenario. PSAS is a 3D-Var assimilation system used
operationally in the Goddard Earth Observing System Data Assimilation System
(GEOS-4 DAS). The comparison is carried out using simulated winds and
geopotential height observations and the finite volume Global Circulation
Model with 72 grid points zonally, 46 grid points meridionally and 55
vertical levels. With forty ensemble members, the LETKF obtains analyses and
forecasts with significantly lower RMS errors than those from PSAS,
especially over the Southern Hemisphere and oceans. This observed advantage
of the LETKF over PSAS is due to the ability of the 40-member ensemble LETKF
to capture flow-dependent errors and thus create a good estimate of the
evolving background uncertainty. An initial decrease of the forecast errors
in the Northern Hemisphere observed in the PSAS but not in the LETKF suggests that the LETKF
analysis is more balanced. |
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