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Titel |
Mediterranean Forecasting System: forecast and analysis assessment through skill scores |
VerfasserIn |
M. Tonani, N. Pinardi, C. Fratianni, J. Pistoia, S. Dobricic, S. Pensieri, M. Alfonso, K. Nittis |
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 ; 5, no. 4 ; Nr. 5, no. 4 (2009-12-07), S.649-660 |
Datensatznummer |
250002738
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Publikation (Nr.) |
copernicus.org/os-5-649-2009.pdf |
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Zusammenfassung |
This paper describes the first evaluation of the quality of the forecast and
analyses produced at the basin scale by the Mediterranean ocean Forecasting
System (MFS) (http://gnoo.bo.ingv.it/mfs). The system produces
short-term ocean forecasts for the following ten days. Analyses are produced
weekly using a daily assimilation cycle. The analyses are compared with
independent data from buoys, where available, and with the assimilated data
before the data are inserted. In this work we have considered 53 ten days
forecasts produced from 16 August 2005 to 15
August 2006.
The forecast skill is evaluated by means of root mean square error (rmse)
differences, bias and anomaly correlations at different depths for
temperature and salinity, computing differences between forecast and
analysis, analysis and persistence and forecast and persistence. The Skill
Score (SS) is defined as the ratio of the rmse of the difference between
analysis and forecast and the rmse of the difference between analysis and
persistence. The SS shows that at 5 and 30 m the forecast is always better
than the persistence, but at 300 m it can be worse than persistence for the
first days of the forecast. This result may be related to flow adjustments
introduced by the data assimilation scheme. The monthly variability of SS
shows that when the system variability is high, the values of SS are higher,
therefore the forecast has higher skill than persistence.
We give evidence that the error growth in the surface layers is controlled
by the atmospheric forcing inaccuracies, while at depth the forecast error
can be interpreted as due to the data insertion procedure. The data, both in
situ and satellite, are not homogeneously distributed in the basin;
therefore, the quality of the analyses may be different in different areas
of the basin. |
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