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| Titel |
Assimilating NOAA SST data into BSH operational circulation model for the North and Baltic Seas: What can we learn about the model and data |
| VerfasserIn |
Svetlana Losa, Jens Schröter, Sergey Danilov, Lars Nerger, Tijana Janjic, Frank Janssen |
| Konferenz |
EGU General Assembly 2011
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250056440
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| Zusammenfassung |
| Within the DeMarine-Environment project- as a part of the European Global Monitoring for
Environment and Security (GMES) initiative,- a data assimilation (DA) system has
been developed for the operational circulation model of the German Maritime and
Hydrographic Agency(BSH). In order to improve forecast of hydrographic characteristics in
the North and Baltic Seas, Singular Evolutive Interpolated Kalman (SEIK) filter
algorithm has been locally implemented for assimilating NOAA sea surface temperature
(SST) over the period 01.10.2007 - 30.09.2008. Significant error reduction has
been achieved for SST forecast (will be shown here) and, since 01.10.2010, the
data assimilation system has been running at BSH in pre-operational phase. Some
aspects of the system implementation however remain a challenge. The forecast
quality is found to be dependent on the assumption about model and data error
statistics which are not always if ever a priori known. However such a combination of
the information from two different sources- the model and the data,- which one
gets with a data assimilation, might itself improve our understanding of both these
sources and help to optimize the system. Here we discuss SST data assimilation
results obtained with several different (with respect to timing, period, frequency)
forecasting schemes and initial error statistics. The Maximum Entropy Approach
(Kivman et al, 2001) is considered as an additional criterion of the analysis performed. |
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