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| Titel |
Coastal observing and forecasting system for the German Bight – estimates of hydrophysical states |
| VerfasserIn |
E. V. Stanev, J. Schulz-Stellenfleth, J. Staneva, S. Grayek, J. Seemann, W. Petersen |
| 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 ; 7, no. 5 ; Nr. 7, no. 5 (2011-09-14), S.569-583 |
| Datensatznummer |
250004799
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| Publikation (Nr.) |
 copernicus.org/os-7-569-2011.pdf |
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| Zusammenfassung |
| A coastal observing system for Northern and Arctic Seas (COSYNA) aims
at construction of a long-term observatory for the German part of the
North Sea, elements of which will be deployed as prototype modules in
Arctic coastal waters. At present a coastal prediction system
deployed in the area of the German Bight integrates near real-time
measurements with numerical models in a pre-operational way and
provides continuously state estimates and forecasts of coastal ocean
state. The measurement suite contributing to the pre-operational set
up includes in situ time series from stationary stations,
a High-Frequency (HF) radar system measuring surface currents,
a FerryBox system and remote sensing data from satellites. The
forecasting suite includes nested 3-D hydrodynamic models running in
a data-assimilation mode, which are forced with up-to-date
meteorological forecast data. This paper reviews the present status
of the system and its recent upgrades focusing on developments in the
field of coastal data assimilation. Model supported data analysis and
state estimates are illustrated using HF radar and FerryBox
observations as examples. A new method combining radial surface
current measurements from a single HF radar with a priori information
from a hydrodynamic model is presented, which optimally relates tidal
ellipses parameters of the 2-D current field and the M2 phase and
magnitude of the radials. The method presents a robust and helpful
first step towards the implementation of a more sophisticated
assimilation system and demonstrates that even using only radials from
one station can substantially benefit state estimates for surface
currents. Assimilation of FerryBox data based on an optimal
interpolation approach using a Kalman filter with a stationary background
covariance matrix derived from a preliminary model run which was
validated against remote sensing and in situ data demonstrated the
capabilities of the pre-operational system. Data assimilation
significantly improved the performance of the model with respect to
both SST and SSS and demonstrated a good skill not only in the
vicinity of the Ferry track, but also over larger model areas. The
examples provided in this study are considered as initial steps in
establishing new coastal ocean products enhanced by the integrated
COSYNA-observations and numerical modelling. |
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