Reference : Super-ensemble techniques applied to wave forecast: performance and limitations
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/2268/63289
Super-ensemble techniques applied to wave forecast: performance and limitations
English
Lenartz, Fabian mailto [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) > >]
Beckers, Jean-Marie mailto [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Chiggiato, Jacopo [NATO Undersea Research Centre (NURC) > Viale San Bartolomeo 400 > 19126 La Spezia, Italy > >]
Mourre, Baptiste [NATO Undersea Research Centre (NURC) > Viale San Bartolomeo 400 > 19126 La Spezia, Italy > >]
Troupin, Charles mailto [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) > >]
Vandenbulcke, Luc [Université de Liège - ULG > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) > >]
Rixen, Michel [NATO Undersea Research Centre (NURC) > Viale San Bartolomeo 400 > 19126 La Spezia, Italy > > >]
23-Jun-2010
Ocean Science
European Geosciences Union
6
2
595-604
Yes (verified by ORBi)
International
1812-0784
[en] Super-Ensemble ; Forecasts ; DART06 ; Adriatic Sea
[en] 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.
Centre Interfacultaire de Recherches en Océanologie - MARE
Researchers ; Professionals
http://hdl.handle.net/2268/63289
10.5194/os-6-595-2010
http://www.ocean-sci.net/6/595/2010/os-6-595-2010.html

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