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| Titel |
Evaluation of numerical models by FerryBox and fixed platform in situ data in the southern North Sea |
| VerfasserIn |
M. Haller, F. Janssen, J. Siddorn, W. Petersen, S. Dick |
| 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 ; 11, no. 6 ; Nr. 11, no. 6 (2015-11-16), S.879-896 |
| Datensatznummer |
250117326
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| Publikation (Nr.) |
 copernicus.org/os-11-879-2015.pdf |
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| Zusammenfassung |
| For
understanding and forecasting of hydrodynamics in coastal regions, numerical
models have served as an important tool for many years. In order to assess
the model performance, we compared simulations to observational data of water
temperature and salinity. Observations were available from FerryBox transects
in the southern North Sea and, additionally, from a fixed platform of the
MARNET network. More detailed analyses have been made at three different
stations, located off the English eastern coast, at the Oyster Ground and in
the German Bight.
FerryBoxes installed on ships of opportunity (SoO) provide high-frequency
surface measurements along selected tracks on a regular basis.
The results of two operational hydrodynamic models have been evaluated for
two different time periods: BSHcmod v4 (January 2009 to April 2012) and FOAM
AMM7 NEMO (April 2011 to April 2012). While they adequately simulate
temperature, both models underestimate salinity, especially near the coast in
the southern North Sea. Statistical errors differ between the two models and
between the measured parameters. The root mean square error
(RMSE) of water temperatures amounts to 0.72 °C (BSHcmod
v4) and 0.44 °C (AMM7), while for salinity the performance of
BSHcmod is slightly better (0.68 compared to 1.1).
The study results reveal weaknesses in both models, in terms of variability,
absolute levels and limited spatial resolution. Simulation of the transition
zone between the coasts and the open sea is still a demanding task for
operational modelling. Thus, FerryBox data, combined with other observations
with differing temporal and spatial scales, can serve as an invaluable tool
not only for model evaluation, but also for model optimization by
assimilation of such high-frequency observations. |
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