Articles | Volume 5, issue 1
Wind Energ. Sci., 5, 285–308, 2020
https://doi.org/10.5194/wes-5-285-2020
Wind Energ. Sci., 5, 285–308, 2020
https://doi.org/10.5194/wes-5-285-2020

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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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Erik Quaeghebeur on behalf of the Authors (30 Nov 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (17 Dec 2019) by Andrea Hahmann
RR by Rémi Gandoin (05 Jan 2020)
ED: Publish subject to minor revisions (review by editor) (10 Jan 2020) by Andrea Hahmann
AR by Erik Quaeghebeur on behalf of the Authors (17 Jan 2020)  Author's response    Manuscript
ED: Publish as is (28 Jan 2020) by Andrea Hahmann
ED: Publish as is (29 Jan 2020) by Jakob Mann(Chief Editor)
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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.