CR 29:183-198 (2005)  -  doi:10.3354/cr029183

Climate change impacts on wind speeds and wind energy density in northern Europe: empirical downscaling of multiple AOGCMs

S. C. Pryor1,*, J. T. Schoof1,3, R. J. Barthelmie2,1

1Atmospheric Science Program, Department of Geography, Indiana University, Bloomington, Indiana 47405, USA
2Department of Wind Energy and Atmospheric Physics, Risø National Laboratory, 4000 Roskilde, Denmark
3Present address: Center for Ocean-Atmospheric Prediction Studies, The Florida State University, Tallahassee, Florida 32310, USA

ABSTRACT: We present empirical downscaling of 5 state-of-the-art AOGCMs (Atmosphere-Ocean General Circulation Models) to investigate potential changes in wind speeds and energy density in northern Europe. The approach is based on downscaling the Weibull parameters of wind speed probability distributions from AOGCM-derived 500 hPa relative vorticity and sea-level pressure gradients, and is demonstrated to generate accurate depictions of the wind climate during the transfer function conditioning period. Bootstrapping is used to develop 100 realizations for each downscaling period and these are used to assess the uncertainty in the results due to stochastic effects in the AOGCM-derived downscaling predictors. Projected changes in the wind speed probability distribution vary with the AOGCMs from which the predictors are derived, but generally it is shown that mean wind speeds, 90th percentile wind speeds and energy density are slightly lower in the 2081–2100 climate projection period than during 1961–1990 at the majority of the 46 stations studied. Conversely it is found that there is no significant difference between conditions during 2046–2065 and 1961–1990 based on the ensemble of downscaling results. Equally, the winter time of 2046–2065 is largely indistinguishable from 1961–1990 for the majority of stations, while the winters of 2081–2100 appear to be associated with lower mean and 90th percentile wind speeds and energy density.

KEY WORDS: Wind speeds · AOGCM · Climate projections · Empirical downscaling

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