dc.description.abstract
This work examines the projected impacts of climate change on wind energy generation across Europe and explores how these impacts can be integrated into longterm energy system planning to enhance system resilience. Using an ensemble of 15 CMIP6 global climate and Earth system models under the highemission SSP58.5 scenario, this study quantifies changes in annual and seasonal Capacity Factor (CF), and the frequency and duration of wind droughts across six climatologically diverse European regions. A rigorous twostage bias correction with a constant scalling factor approach, leveraging ERA5 re analysis data and the Global Wind Atlas (GWA), ensures alignment with observational cli matology. Wind speeds are extrapolated using logarithmic vertical interpolation to turbine specific hub heights, followed by regionally differentiated power output modelling using established turbine performance curves. The analysis reveals a spatially heterogeneous but robust seasonal signal, with a signif icant decline in summer wind capacity factors across Central and Northern Europe, as well as Southern Europe in autumn, and high intermodel agreement on these trends. In contrast, winter and spring exhibit greater model disagreement and statistical variability, reflecting a more uncertain climate response. Wind droughts, defined using seasonal, modelspecific fifthpercentile CF thresholds, are projected to increase in frequency and duration in several regions, particularly during summer, although their emergence is less consistent than the CF signal. To assess the operational relevance of these projected changes, the Time of Emergence (ToE) of climate signals is estimated using signaltonoise ratios and statistical tests, pro viding insight into when changes in wind generation become distinguishable from histori cal variability. While some regions exhibit early emergence of declining CF signals, such as the British Isles by midcentury, ToE estimates remain sensitive to methodological as sumptions and interannual variability. By aligning the temporal scope of the projections with typical wind project development cy cles, this work addresses a key gap in current literature, namely the lack of mediumterm, operationally relevant projections for wind energy. The methodological framework, en compassing bias correction, spatial standardisation, seasonal and extremeevent charac terisation, and ensemblebased robustness assessments, is designed to be reproducible and applicable to other regions or technologies. Findings from this study underscore the importance of incorporating climateaware wind generation estimates into energy mod els to ensure robust planning, particularly as Europe accelerates its transition towards renewabledominated power systems under increasingly nonstationary climate condi tions.
