COMPARISON OF FIELD AND FORECAST METOCEAN DATA IN THE GERMAN BIGHT
ICCE 2022
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How to Cite

COMPARISON OF FIELD AND FORECAST METOCEAN DATA IN THE GERMAN BIGHT. (2023). Coastal Engineering Proceedings, 37, management.87. https://doi.org/10.9753/icce.v37.management.87

Abstract

Offshore wind energy can contribute significantly to achieve greenhouse gas neutrality in the near future. But the planning, construction and operation of offshore wind parks is associated with high costs. In particular, the operation and maintenance (OandM) costs account for a major fraction and in turn are also dependent on appropriate weather windows in which working vessels can operate. A precise knowledge of how wind, sea state and currents affect each other, as well as the most accurate possible prediction of the development, is essential to maximize these periods and reduce the resulting costs. For the German Bight, the high-resolution coastal wave model (CWAM) is often used for this purpose. The CWAM is based on WAM (Hasselmann et al. 1988) and was developed by the German Meteorological Service (DWD) and German Maritime and Hydrographic Agency (BSH) in cooperation with the Helmholtz-Zentrum Hereon. Compared to other WAM models it offers the advantages of higher resolution, as well as the consideration of current speeds and tide-dependent water depths. The BSH also operates multiple measuring stations in the German Bight, which enable real-time investigation of sea state parameters. The general objective of this study is to compare historical data sets from in situ measurements in the German Bight with numerical forecast data and to identify which factors influence the accuracy of the CWAM and why deviations occur.
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References

Amidror (2002): Scattered data interpolation methods for electronic imaging systems: a survey. Journal of Electronic Imaging, vol. 11, Issue 2, pp. 157-176

Hasselmann et al. (1988): The WAM model – a third generation ocean wave prediction model, Journal of Physical Oceanography, vol. 18, Issue 12, pp. 1775–1810

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Copyright (c) 2023 Lukas Froehling, Thilo Grotebrune, Arndt Hildebrandt