Evaluation of the wind influence in modeling the black sea wave conditions
01 Feb 2014-Environmental Engineering and Management Journal (OAIMDD - EcoZone Publishing House)-Vol. 13, Iss: 2, pp 305-314
TL;DR: In this article, the authors focused on the importance of the resolution and accuracy of the wind fields in modeling waves in the Black Sea and the impact of increasing the wind resolution is even greater in the wave modeling than in the wind modeling.
Abstract: The present work is focused on the importance of the resolution and accuracy of the wind fields in modeling waves in the Black Sea. Two different wind fields are considered for forcing the third generation spectral wave model SWAN. The wind data wave model results are compared against in situ measurements performed at the Gloria drilling unit and also against satellite data for a two-month period of wintertime at the beginning of 2002. Subsequently, the model simulations were extended with other four months, time interval that corresponds to moderated wave conditions. Both direct comparisons and statistical results show that in such enclosed seas, as the Black Sea is, the wind resolution is a crucial factor in modeling waves. Moreover, the impact of increasing the wind resolution is even greater in the wave modeling than in the wind modeling. The underestimation of the extreme significant wave heights, a typical feature of the spectral models, is in general corrected when the high-resolution wind data is used but it still persists in high wind and wave conditions as well as in highly non stationary cases.
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University of Oldenburg1, National Research Council2, Plymouth Marine Laboratory3, National Institute of Oceanography, India4, University of Bologna5, Scripps Institution of Oceanography6, IFREMER7, Centre national de la recherche scientifique8, Sofia University9, University of Toulouse10, Food and Agriculture Organization11, University of Reading12, Parthenope University of Naples13, Met Office14, Polytechnic University of Catalonia15, University of Aveiro16, University of Haifa17, Spanish National Research Council18, European Environment Agency19, Tallinn University of Technology20, Bulgarian Academy of Sciences21, Danish Meteorological Institute22, University of Otago23, German Research Centre for Artificial Intelligence24, University of Copenhagen25
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