Welkom op het expertplatform!
Dit platform verschaft informatie en kennis omtrent de WL expertisedomeinen 'hydraulica en sediment', 'havens en waterwegen', 'waterbouwkundige constructies', 'waterbeheer' en 'kustbescherming' - gaande van WL medewerkers met hun expertise, het curriculum van deze instelling, tot publicaties, projecten, data (op termijn) en evenementen waarin het WL betrokken is.
Het WL onderschrijft het belang van "open access" voor de ontsluiting van haar onderzoeksresultaten. Lees er meer over in ons openaccessbeleid.
| one publication added to basket [199479] |
Super-ensemble techniques applied to wave forecast: performance and limitations
Lenartz, F.; Beckers, J.-M.; Chiggiato, J.; Mourre, B.; Troupin, C.; Vandenbulcke, L.; Rixen, M. (2010). Super-ensemble techniques applied to wave forecast: performance and limitations. Ocean Sci. 6(2): 595-604. dx.doi.org/10.5194/os-6-595-2010
In: Ocean Science. Copernicus: Göttingen. ISSN 1812-0784; e-ISSN 1812-0792
|   |
| Auteurs | | Top |
- Lenartz, F.
- Beckers, J.-M.
- Chiggiato, J.
- Mourre, B.
|
- Troupin, C.
- Vandenbulcke, L.
- Rixen, M.
|
|
| 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. |
IMIS is ontwikkeld en wordt gehost door het VLIZ.
