Articles | Volume 5, issue 1
Wind Energ. Sci., 5, 285–308, 2020
Wind Energ. Sci., 5, 285–308, 2020

Research article 28 Feb 2020

Research article | 28 Feb 2020

How to improve the state of the art in metocean measurement datasets

Erik Quaeghebeur and Michiel B. Zaaijer

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Cited articles

Aggarwal, C. C.: Outlier analysis, 2 edn., Springer, Cham, Switzerland,, 2017. a
Beeken, A., Neumann, T., and Westerhellweg, A.: Five years of operation of the first offshore wind research platform in the German Bight – FINO1, Tech. rep., DEWI GmbH, available at:, last access: 25 November 2009. a
Brower, M. C., ed.: Data validation, chap. 9, pp. 117–129, John Wiley & Sons, Inc., Hoboken, New Jersey,, 2012. a
BSH: FINO – Plot und Download, available at: (last access: 15 October 2019), 2019a. a, b
BSH: FINO, available at: (last access: 15 October 2019), 2019b. a
Short summary
Meteorological and oceanic datasets are fundamental to the modeling of offshore wind farms. Data quality issues in one such dataset led us to conduct a study to establish whether such issues are more generally present in these datasets. The answer is yes and users should be aware of this. We therefore also investigated how such issues can be avoided. The result is a set of techniques and recommendations for dataset producers, leading to substantial quality improvements with limited extra effort.