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| Titel |
Assimilation of ocean colour data into a Biogeochemical Flux Model of the Eastern Mediterranean Sea |
| VerfasserIn |
G. Triantafyllou, G. Korres, I. Hoteit, G. Petihakis, A. C. Banks |
| 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 ; 3, no. 3 ; Nr. 3, no. 3 (2007-08-21), S.397-410 |
| Datensatznummer |
250001098
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| Publikation (Nr.) |
 copernicus.org/os-3-397-2007.pdf |
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| Zusammenfassung |
| An advanced multivariate sequential data assimilation system has been
implemented within the framework of the European MFSTEP project to fit
a three-dimensional biogeochemical model of the Eastern Mediterranean
to satellite chlorophyll data from the Sea-viewing Wide
Field-of-view Sensor (SeaWiFS). The physics are described by the
Princeton Ocean Model (POM) while the biochemistry of the ecosystem is
tackled with the Biogeochemical Flux Model (BFM). The assimilation
scheme is based on the Singular Evolutive Extended Kalman (SEEK)
filter, in which the error statistics were parameterized by means of a
suitable set of Empirical Orthogonal Functions (EOFs). To avoid
spurious long-range correlations associated with the limited number of
EOFs, the filter covariance matrix was given compact support through
a radius of influence around every data point location. Hindcast
experiments were performed for one year over 1999 and forced with
ECMWF 6 h atmospheric fields. The solution of the assimilation
system was evaluated against the assimilated data and the MedAtlas
climatology, and by assessing the impact of the assimilation on
non-observed biogeochemical processes. It is found that the
assimilation of SeaWiFS data improves the overall behavior of
the BFM model and efficiently removes long term biases from the
model despite some difficulties during the spring bloom
period. Results, however, suggest the need of subsurface data to
enhance the estimation of the ecosystem variables in the deep
layers. |
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