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Carl von Ossietzky University Oldenburg, ForWind – Centre for Wind Energy Research

Carl von Ossietzky University Oldenburg, ForWind – Centre for Wind Energy Research. Climate Change of the Near Surface Wind Sped over Europe and North Atlantic in the IPCC A2 scenario. Kay Su šelj, Detlev Heinemann, Abha Sood. Outlook. Motivation Methodology Results – climate change of WS:

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Carl von Ossietzky University Oldenburg, ForWind – Centre for Wind Energy Research

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  1. Carl von Ossietzky University Oldenburg, ForWind – Centre for Wind Energy Research Climate Change of the Near Surface Wind Sped over Europe and North Atlantic in the IPCC A2 scenario Kay Sušelj, Detlev Heinemann, Abha Sood

  2. K. Sušelj et al / page 2 Outlook Motivation Methodology Results – climate change of WS: Winter Summer Outlook and conclusions

  3. K. Sušelj et al / page 3 Motivation Importance of Wind Speed (WS) climate change for wind energy High sensitivity of wind power on WS Inconsistent results of climate change of WS over Europe in recent literature (e.g. Räisänen et al., 2004; Pryor et al., 2005,2006)‏ Last IPCC report: Confidence in predicting future change of WS over Europe is low

  4. K. Sušelj et al / page 4 Methodology Statistically estimate climate change of WS over Europe and North Atlantic based on forcing parameter, i.e. Sea Level Pressure (SLP)‏ Find WS patterns optimized in explaining WS trend (past data) – Trend Empirical Orthogonal Functions Statistically relate the WS patterns to SLP patterns (past data)‏ Investigate change of SLP patterns in future climate Estimate climate change of WS SLP from ensemble of Global Circulation Models (GCMs) - estimation of the confidence of WS change GCM simulation based on SRES IPCC A2 scenario

  5. K. Sušelj et al / page 5 Assumptions: WS well defined by the large scale SLP forcing Statistical relationship between SLP and WS patterns describes physical coupling WS patterns from past climate remain significant in future climate Seasonally dependent WS patterns and relationship to SLP – independent analysis for four seasons of the year

  6. K. Sušelj et al / page 6 Trend WS pattern and related SLP patterns – Winter (Dec.-Feb.)‏ Sea Level Pressure Time Series WS – red; SLP - green

  7. K. Sušelj et al / page 7 Wind Speed change in Winter (Dec.-Feb.)‏ • SLP data from the GCM results used for 4th IPCC report • 17 GCMs with 1-5 runs • Estimation of reliability of results

  8. K. Sušelj et al / page 8 Wind speed change in Winter (Dec.-Feb.)‏ 90th percentile 10th percentile GCM mean

  9. K. Sušelj et al / page 9 Wind speed change in other seasons compared to Winter • Similar WS and SLP patterns, moved towards North to Northwest • Lower WS trend in past climate • SLP and WS relationship less clear • Contribution of local WS forcing more important

  10. K. Sušelj et al / page 10 Change of WS in Summer (Jun.-Aug.)‏ • 10m Wind Speed 10th percentile GCM mean 90th percentile

  11. K. Sušelj et al / page 11 Conclusions • Clear signal increase of WS over the North Atlantic and North Europe in Winter • The climate change of WS is small and not significant in other seasons • Analysis restricted to IPCC A2 scenario • Only the GCM resolved (synoptic scale) forcing • The GCMs cannot well represent the past variability of the SLP patterns • Further downscaling of wind can be done based on the selected GCMs

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