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.Published by Copernicus Publications on behalf of the European Academy of Wind Energy e.V.
286E. Quaeghebeur and M. B. Zaaijer: How to improve the state of the art in metocean measurement datasets dressed? This paper reports the results of that study. In brief, (i) yes, there are shared issues, but, not unexpectedly, not all of them in all datasets, and (ii) dataset producers can address the issues with a few non-burdensome additions to their creation practice. Next to providing arguments for and detailing these conclusions, this paper is meant to raise awareness of the issues mentioned by giving concrete examples. Furthermore, it provides dataset producers with concrete ideas about how to achieve substantial improvements with reasonable effort.The users of the produced datasets are of course the farm developers, but also the academic world, whose usage is not necessarily restricted to wind energy applications. The context of our academic research is offshore wind energy, but the work we present here is relevant outside that area as well. Therefore, we treat all measured quantities on equal footing and do not focus on wind and wave data. When our discussion goes beyond the analysis of the specific datasets we considered, it is also mostly independent of their metocean nature but generally applies to any numerical time series data.We structure the paper into two main sections. We start with an essentially descriptive Sect. 2, to give an overview of the datasets we considered and to identify the issues we encountered. The original contributions here are our thorough description, in-depth analysis, ...