A new statistical downscaling framework is proposed to evaluate the climate change impact on wind resources in Taiwan Strait. In this framework, a two-parameter Weibull distribution function is used to estimate the wind energy density distribution in the strait. An empirically statistical downscaling model that relates the Weibull parameters to output of a General Circulation Model (GCM) and regression coefficients is adopted. The regression coefficients are calculated using wind speed results obtained from a past climate (1981-2000) simulation reconstructed by a Weather Research and Forecasting (WRF) model. These WRF-reconstructed wind speed results are validated with data collected at a weather station on an islet inside the strait. The comparison shows that the probability distributions of the monthly wind speeds obtained from WRF-reconstructed and measured wind speed data are in acceptable agreement, with small discrepancies of 10.3% and 7.9% for the shape and scale parameters of the Weibull distribution, respectively. The statistical downscaling framework with output from three chosen GCMs (i.e., ECHAM5, CM2.1 and CGCM2.3.2) is applied to evaluate the wind energy density distribution in Taiwan Strait for three future climate periods of 2011-2040, 2041-2070, and 2071-2100. The results show that the wind energy density distributions in the future climate periods are higher in the eastern half of Taiwan Strait, but reduce slightly by 3% compared with that in the past climate period.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Nuclear Energy and Engineering
- Fuel Technology
- Energy Engineering and Power Technology