Abstract
Abstract. A correct spatio-temporal representation of retrospective wind speed estimates is of large interest for the wind energy sector. In this respect, reanalyses provide an invaluable source of information. However, the quality of the various reanalysis estimates for wind speed are difficult to assess. Therefore, this study compares wind measurements at hub heights from 14 locations in Central Europe with two global (ERA5, MERRA-2) and one regional reanalysis (COSMO-REA6). Employing metrics such as bias, RMSE and correlation, we evaluate the performance of the reanalyses with respect to (a) the local surface characteristics (offshore, flat onshore, hilly onshore), (b) various height levels (60 to 200 m) and (c) the diurnal cycle. As expected, we find that the reanalyses show the smallest errors to observations at offshore sites. Over land, MERRA-2 generally overestimates wind speeds, while COSMO-REA6 and ERA5 represent the average wind speed more realistically. At sites with flat terrain, ERA5 correlates better with observations than COSMO-REA6. In contrast, COSMO-REA6 performs slightly better over hilly terrain, which can be explained by the higher horizontal resolution. In terms of diurnal variation, ERA5 outperforms both other reanalyses. While the overestimation of MERRA-2 is consistent throughout the day, COSMO-REA6 significantly underestimates wind speed at night over flat and hilly terrain due to a misrepresentation of nightly low level jets and mountain and valley breezes. Regarding the representation of downtime of wind turbines due to low/high wind speeds, we find that MERRA-2 is consistently underperforming with respect to the other reanalyses. Here COSMO-REA6 performs better over the ocean, while ERA5 shows the best results over land.
Highlights
A sound knowledge of relevant climatological parameters is essential in advancing the transition towards renewable energies
For the majority of observing sites used in this study, a Weibull distribution should not be used to evaluate wind speeds at hub heights
While this study presents results as deviations or differences from the observations due to the confidentially of some of the data, it provides a reasonable overview of the quality of wind speed reanalysis estimates at hub heights over Central Europe and the surrounding oceans
Summary
A sound knowledge of relevant climatological parameters is essential in advancing the transition towards renewable energies. Jourdier (2020) evaluate several reanalyses using wind mast data in France, Ramon et al (2019) compare the Tall Tower Dataset (Ramon et al, 2020) with global reanalyses All these studies show that reanalyses can be an important additional data source for the wind energy sector, but small-scale phenomena of the boundary layer such as the low level jet or local effects are not satisfyingly described by the reanalyses. We use measurements from the Tall Tower Dataset, the mast observations analysed in Frank et al (2020b), two lidar observations provided by the Danish company Orsted as well as five additional observation sites from BayWa r.e. Wind Gmbh made exclusively available to us.
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