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| Titel |
Ensemble Kalman filter assimilation of temperature and altimeter data with bias correction and application to seasonal prediction |
| VerfasserIn |
C. L. Keppenne, M. M. Rienecker, N. P. Kurkowski, D. A. Adamec |
| 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 ; 12, no. 4 ; Nr. 12, no. 4 (2005-05-17), S.491-503 |
| Datensatznummer |
250010674
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| Publikation (Nr.) |
 copernicus.org/npg-12-491-2005.pdf |
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| Zusammenfassung |
| To compensate for a poorly known geoid, satellite altimeter data is usually
analyzed in terms of anomalies from the time mean record. When such
anomalies are assimilated into an ocean model, the bias between the
climatologies of the model and data is problematic. An ensemble Kalman
filter (EnKF) is modified to account for the presence of a forecast-model
bias and applied to the assimilation of TOPEX/Poseidon (T/P) altimeter data.
The online bias correction (OBC) algorithm uses the same ensemble of model
state vectors to estimate biased-error and unbiased-error covariance
matrices. Covariance localization is used but the bias covariances have
different localization scales from the unbiased-error covariances, thereby
accounting for the fact that the bias in a global ocean model could have
much larger spatial scales than the random error.The method is applied to a 27-layer version of the Poseidon global ocean general circulation model with about 30-million state variables. Experiments
in which T/P altimeter anomalies are assimilated show that the OBC reduces
the RMS observation minus forecast difference for sea-surface height (SSH)
over a similar EnKF run in which OBC is not used. Independent in situ temperature
observations show that the temperature field is also improved. When the T/P
data and in situ temperature data are assimilated in the same run and the
configuration of the ensemble at the end of the run is used to initialize
the ocean component of the GMAO coupled forecast model, seasonal SSH
hindcasts made with the coupled model are generally better than those
initialized with optimal interpolation of temperature observations without
altimeter data. The analysis of the corresponding sea-surface temperature
hindcasts is not as conclusive. |
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