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• W2889883989 abstract "The mitigation of climate change demands a fundamental conversion of our energy system, from a mainly fossil fuel-driven system to one with a higher share of renewable sources. For Europe, wind has emerged as an important renewable energy source with high potential. However, wind energy production is strongly influenced by weather and climate conditions, and hence subject to day-to-day, seasonal and long-term climate change. The analysis and estimation of the impact of these changes on the future wind energy production is of high importance for the development of an energy system with higher renewable energy content. The overall objective of this thesis is to investigate regional scale wind speeds and wind energy potentials over Europe at different timescales, focussing on the near-term and long-term future. With this aim, three studies are performed. The first study estimates future changes of wind energy output (Eout) of an exemplary wind turbine over Europe in a large multi-model ensemble. For this purpose, model output from 22 global climate models (GCMs) from CMIP5 is regionalised using a statistical-dynamical downscaling (SDD) approach. This method is based on a combination of circulation weather type (CWT) analysis and regional climate modelling with COSMO-CLM. Mean annual Eout is projected to increase over Northern and Central Europe and decrease over Southern Europe in the ensemble mean. However, the individual ensemble members can differ both in terms of magnitude and sign of change. Simulated future changes are more robust in seasonal terms, in which Eout generally increases for winter and decreases in summer. These changes lead to an enhancement of the intra-annual variability of Eout for most parts of Europe, which in turn results in a higher volatility of wind energy production under future climate conditions. Regarding changes in the inter-annual variability, results for the individual models vary strongly and the spatial patterns are not coherent between future periods and scenarios. The study clearly reveals an impact of climate change on wind energy potentials over Europe, but in some aspects results depend strongly on the choice of GCM. This highlights the large uncertainties between different GCMs and the importance to analyse multi-model ensembles. The second study evaluates future changes of regional wind speed and wind energy output over Europe, this time in a dynamically downscaled ensemble. The high resolution EURO-CORDEX ensemble is based on nine GCM-RCM chains at 12 km spatial and three-hourly temporal resolution. The ensemble mean projects a weak decrease of mean annual Eout for most parts of Europe and a small but robust increase for the Baltic and the Aegean Sea. Differences to the previous study are primarily based on the model choice. Regarding variability, small robust changes are simulated for inter-daily variability, while changes are larger but more uncertain for inter- and intra-annual variability of Eout. Both inter-daily and intra-annual variability are projected to increase for Northern, Central and Eastern Europe. In terms of wind speed characteristics relevant for wind energy production, an increased occurrence of low wind speeds is detected. The study reveals that regions like the Baltic and the Aegean Sea could profit from climate change due to a combination of increasing mean annual Eout and decreasing intra-annual variability. On the other hand, negative impacts are projected for regions like Germany, France and Iberia with decreasing mean Eout and a higher intra-annual variability. The third study examines the decadal predictability of wind speed and wind energy potentials over Central Europe in three generations of the decadal prediction system developed within the German MiKlip (‘Mittelfristige Klimaprognosen’) project. The prediction system is based on the global Max-Planck-Institute Earth System Model (MPI-ESM). Uninitialised historical and yearly-initialised hindcast experiments are downscaled applying the same SDD approach as used in the first study to assess the decadal forecast skill. The three ensemble generations show some decadal forecast skill for both mean annual wind speed and Eout. This skill is mainly limited to the first years (1-4) after initialisation. In seasonal terms, skill scores are generally lower than for annual means with lowest values in summer and highest values in autumn. In general, differences between the individual ensemble generations are small. The regionalisation is able to preserve and sometimes increase the forecast skill from the global model, and it often improves the ensemble spread. The study identifies a dominant westerly weather type with strong pressure gradients over Central Europe as potential source for the forecast skill, showing similar MSE-based skill scores as Eout. Overall, results are encouraging for the installation of a decadal prediction system for Central Europe and for the utilization of such a system for wind energy applications. This thesis extends the current knowledge on wind speed and wind energy potentials over Europe. The outcomes show that climate change affects future wind energy generation at different timescales. Future responses depend on the analysed ensembles, which consider different models and downscaling approaches. Differences arise mainly from the model choice, while the different downscaling methods provide similar climate change signals. The results proved to be important for an advanced impact study, which analysed climate change impacts on a European renewable energy system. The results on decadal predictability are encouraging for the establishment of a decadal prediction system for wind energy applications. Overall, outcomes of this thesis may be relevant for the successful integration of wind energy into our electric power system." @default.
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• W2889883989 date "2018-07-01" @default.
• W2889883989 modified "2023-09-24" @default.
• W2889883989 title "Wind speed and wind energy potentials over Europe: Regionalisation, decadal predictability, and long-term future changes" @default.
• W2889883989 hasPublicationYear "2018" @default.
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