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| Titel |
Application of a hybrid EnKF-OI to ocean forecasting |
| VerfasserIn |
F. Counillon, P. Sakov, L. Bertino |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1812-0784
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| Digitales Dokument |
URL |
| Erschienen |
In: Ocean Science ; 5, no. 4 ; Nr. 5, no. 4 (2009-10-01), S.389-401 |
| Datensatznummer |
250002719
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| Publikation (Nr.) |
 copernicus.org/os-5-389-2009.pdf |
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| Zusammenfassung |
| Data assimilation methods often use an ensemble to represent the background
error covariance. Two approaches are commonly used; a simple one with a
static ensemble, or a more advanced one with a dynamic ensemble. The latter
is often non-practical due to its high computational requirements. Some
recent studies suggested using a hybrid covariance, which is a linear
combination of the covariances represented by a static and a dynamic
ensemble. Here, the use of the hybrid covariance is first extensively tested
with a quasi-geostrophic model and with different analysis schemes, namely
the Ensemble Kalman Filter (EnKF) and the Ensemble Square Root Filter (ESRF).
The hybrid covariance ESRF (ESRF-OI) is more accurate and more stable than
the hybrid covariance EnKF (EnKF-OI), but the overall conclusions are similar
regardless of the analysis scheme used. The benefits of using the hybrid
covariance are large compared to both the static and the dynamic methods with
a small dynamic ensemble. The benefits over the dynamic methods become
negligible, but remain, for large dynamic ensembles. The optimal value of the
hybrid blending coefficient appears to decrease exponentially with the size
of the dynamic ensemble. Finally, we consider a realistic application with
the assimilation of altimetry data in a hybrid coordinate ocean model (HYCOM)
for the Gulf of Mexico, during the shedding of Eddy Yankee (2006). A
10-member EnKF-OI is compared to a 10-member EnKF and a static method called
the Ensemble Optimal Interpolation (EnOI). While 10 members seem insufficient
for running the EnKF, the 10-member EnKF-OI reduces the forecast error
compared to the EnOI, and improves the positions of the fronts. |
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