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Ocean Science An interactive open-access journal of the European Geosciences Union
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Volume 6, issue 2
Ocean Sci., 6, 595–604, 2010
https://doi.org/10.5194/os-6-595-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Ocean Sci., 6, 595–604, 2010
https://doi.org/10.5194/os-6-595-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  23 Jun 2010

23 Jun 2010

Super-ensemble techniques applied to wave forecast: performance and limitations

F. Lenartz1,2, J.-M. Beckers2, J. Chiggiato1, B. Mourre1, C. Troupin2, L. Vandenbulcke2, and M. Rixen1 F. Lenartz et al.
  • 1NATO Undersea Research Centre (NURC), Viale San Bartolomeo 400, 19126 La Spezia, Italy
  • 2Université de Liège – GeoHydrodynamics and Environment Research (GHER), Allée du 6-Août 17, 4000 Liège, Belgium

Abstract. Nowadays, several operational ocean wave forecasts are available for a same region. These predictions may considerably differ, and to choose the best one is generally a difficult task. The super-ensemble approach, which consists in merging different forecasts and past observations into a single multi-model prediction system, is evaluated in this study. During the DART06 campaigns organized by the NATO Undersea Research Centre, four wave forecasting systems were simultaneously run in the Adriatic Sea, and significant wave height was measured at six stations as well as along the tracks of two remote sensors. This effort provided the necessary data set to compare the skills of various multi-model combination techniques. Our results indicate that a super-ensemble based on the Kalman Filter improves the forecast skills: The bias during both the hindcast and forecast periods is reduced, and the correlation coefficient is similar to that of the best individual model. The spatial extrapolation of local results is not straightforward and requires further investigation to be properly implemented.

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