TY - JOUR
T1 - Evaluation of the climate change impact on wind resources in Taiwan Strait
AU - Chang, Tsang Jung
AU - Chen, Chun Lung
AU - Tu, Yi Long
AU - Yeh, Hung Te
AU - Wu, Yu Ting
N1 - Funding Information:
The authors would like to acknowledge the data of WRF for this work provided by Taiwan Climate Change Projection & Information Platform. The authors are grateful for the financial support of this work provided by Ministry of Science and Technology, R.O.C. , under Grant Nos. 102-2625-M-002-006 and 103-2111-M-006-007 . Computing resources were provided by the Taiwan National Center for High-performance Computing (NCHC) and the Swiss National Supercomputing Center (CSCS) under project ID d32. We thank the editor and the three anonymous reviewers for their constructive comments.
Publisher Copyright:
© 2015 Elsevier Ltd. All rights reserved.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - 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.
AB - 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.
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U2 - 10.1016/j.enconman.2015.02.033
DO - 10.1016/j.enconman.2015.02.033
M3 - Article
AN - SCOPUS:84924809124
VL - 95
SP - 435
EP - 445
JO - Energy Conversion and Management
JF - Energy Conversion and Management
SN - 0196-8904
ER -