Sensitivities in Wind Driven Spectral Wave Modelling for the Belgian Coast
This paper presents the analysis of spectral wind-wave modelling (using SWAN) of the North Sea focusing on the modelled wave parameters along the Belgian coast. Two wind databases were used to drive the model: ECMWF-ERA5 reanalysis and the Dutch Offshore Wind Atlas. The models were calibrated with measured data at various stations along the Belgian coastline. The accuracy in terms of wave parameter statistics was compared for the calibrated and uncalibrated models. It was found that a calibrated SWAN model does, in general, produce more accurate results when compared to measured data for stati... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2022 |
Reihe/Periodikum: | Journal of Marine Science and Engineering, Vol 10, Iss 1138, p 1138 (2022) |
Verlag/Hrsg.: |
MDPI AG
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Schlagwörter: | SWAN / Belgium / wave modelling / wind-waves / ECMWF-ERA5 / DOWA / Naval architecture. Shipbuilding. Marine engineering / VM1-989 / Oceanography / GC1-1581 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26974243 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.3390/jmse10081138 |
This paper presents the analysis of spectral wind-wave modelling (using SWAN) of the North Sea focusing on the modelled wave parameters along the Belgian coast. Two wind databases were used to drive the model: ECMWF-ERA5 reanalysis and the Dutch Offshore Wind Atlas. The models were calibrated with measured data at various stations along the Belgian coastline. The accuracy in terms of wave parameter statistics was compared for the calibrated and uncalibrated models. It was found that a calibrated SWAN model does, in general, produce more accurate results when compared to measured data for stations along the Belgian coastline even though not by any significant margin. Comparing the two wind databases, on the modelling scale conducted in this study, there is no advantage observed in using a spatially finer scale wind database over a coarser database to force the model. The grid sizes were varied in the models and marginal differences were observed in the modelled data. The long-term extreme value statistics were calculated for various grid sizes and compared to published values. It is shown that the extreme value statistics are relatively insensitive to the grid density and thus much time can be saved on long-term modelling on this model scale. In addition, a benefit to the practise of grid nesting is demonstrated when considering complex bathymetric effects that have an influence on wave transformation in the shallower areas of the coast, especially along the Belgian coastline demarcated with its numerous sandbanks.