How to improve the state of the art in metocean measurement datasets
<p>We present an analysis of three datasets of 10 min metocean measurement statistics and our resulting recommendations to both producers and users of such datasets. Many of our recommendations are more generally of interest to all numerical measurement data producers. The dataset...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-02-01
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| Series: | Wind Energy Science |
| Online Access: | https://www.wind-energ-sci.net/5/285/2020/wes-5-285-2020.pdf |
| Summary: | <p>We present an analysis of three datasets of 10 min metocean measurement statistics and our resulting recommendations to both producers and users of
such datasets. Many of our recommendations are more generally of interest to all numerical measurement data producers. The datasets analyzed
originate from offshore meteorological masts installed to support offshore wind farm planning and design: the Dutch OWEZ and MMIJ and the German
FINO1. Our analysis shows that such datasets contain issues that users should look out for and whose prevalence can be reduced by producers. We
also present expressions to derive uncertainty and bias values for the statistics from information typically available about sample uncertainty. We
also observe that the format in which the data are disseminated is sub-optimal from the users' perspective and discuss how producers can create more
immediately useful dataset files. Effectively, we advocate using an established binary format (HDF5 or netCDF4) instead of the typical text-based
one (comma-separated values), as this allows for the inclusion of relevant metadata and the creation of significantly smaller directly accessible
dataset files. Next to informing producers of the advantages of these formats, we also provide concrete pointers to their effective use. Our
conclusion is that datasets such as the ones we analyzed can be improved substantially in usefulness and convenience with limited effort.</p> |
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| ISSN: | 2366-7443 2366-7451 |