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<p>With higher penetration of renewable energies and the effort to decarbonize power production there is a strong interest in the objective characterization of wind resource. Over Europe, wind power accounts for around 17% of total power capacity and almost 30% of renewable capacity and is the overall second largest form of generation capacity after gas.&#160;</p>
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<p>In addition to the description of mean capacity factors, there is a need to characterize extremes. Low wind events and persistent low wind events (LWE) are of&#160;particular interest&#160;because during these the energy system needs to rely on &#8216;backup&#8217; sources such as gas, coal and nuclear. Over the United Kingdom and other parts of Europe, these are often linked to the occurrence of blocking (e.g.,&#160;Brayshaw&#160;et al. 2012,&#160;Cannon et al. 2015, Grams et al. 2017), which is the initial focus of this study. Additionally, blocking events have an impact on near-surface temperatures over Europe, which implies an effect in weather-dependent energy demand.&#160;</p>
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<p>This study focuses on the impacts of blocking conditions on low wind events and their persistence, and the representation of these effects on the high-resolution&#160;(around 25km) global&#160;PRIMAVERA models. Our results confirm that blocking events over Europe have a significant impact on the occurrence and duration of low wind speeds at the country level, which is of relevance to the energy sector. In addition to becoming more frequent, LWE are also more persistent under blocking conditions over large areas of Europe. Both effects are in general captured by most of the PRIMAVERA GCMs analysed here, revealing that when the models do get the blocking events, the basic dynamical connection with wind anomalies is present. Nonetheless, the fact that the simulated weather conditions have deficiencies introduces biases in the properties of the events and their joint occurrence.&#160;&#160;</p>
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<p>The errors in the models depend on the statistic, the country and the resolution, but some consistent bias patterns can be observed at times (e.g., North-South dipolar structures). No robust improvements in the representation of these effects were observed in the high-resolution versions of the PRIMAVERA models, nor where the highest resolution runs consistently outperforming coarser simulations.&#160;&#160;</p>
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<p>Blocking impacts to the energy systems are not only limited to wind power generation, since these large-scale anomalies also have an impact on near-surface temperature and therefore on electricity demand. These effects are also addressed here.</p>
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Identification of Extreme Wind Events Using a Weather Type Classification