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Projected near-surface wind speed and wind energy over Central Asia using dynamical downscaling with bias-corrected global climate models

文献类型：期刊论文

作者Zha, Jin-Lin8,9; Chuan, Ting9; Qiu, Yuan8; Wu, Jian9; Zhao, De-Ming9; Fan, Wen-Xuan9; Lyu, Yan-Jun7; Jiang, Hui-Ping5,6; Deng, Kai-Qiang3,4; Andres-Martin, Miguel2
刊名ADVANCES IN CLIMATE CHANGE RESEARCH
出版日期2024-08-01
卷号15期号:4页码:669-679
关键词Near-surface wind speed Wind power density Dynamical downscaling Central Asia WRF
ISSN号1674-9278
DOI10.1016/j.accre.2024.07.007
产权排序4
英文摘要Wind energy development in Central Asia can help alleviate drought and fragile ecosystems. Nevertheless, current studies mainly used the global climate models (GCMs) to project wind speed and energy. The simulated biases in GCMs remain prominent, which induce a large uncertainty in the projected results. To reduce the uncertainties of projected near-surface wind speed (NSW) and better serve the wind energy development in Central Asia, the Weather Research and Forecasting (WRF) model with bias-corrected GCMs was employed. Compared with the outputs of GCMs, dynamical downscaling acquired using the WRF model can better capture the high- and low-value centres of NSWS, especially those of Central Asia's mountains. Meanwhile, the simulated NSWS bias was also reduced. For future changes in wind speed and wind energy, under the Representative Concentration Pathway 4.5 (RCP4.5) scenario, NSWS during 2031-2050 is projected to decrease compared with that in 1986-2005. The magnitude of NSWS reduction during 2031-2050 will reach 0.1 m s(-1), and the maximum reduction is projected to occur over the central and western regions (>0.2 m s(-1)). Furthermore, future wind power density (WPD) can reveal nonstationarity and strong volatility, although a downward trend is expected during 2031-2050. In addition, the higher frequency of wind speeds at the turbine hub height exceeding 3.0 m s(-1) can render the plain regions more suitable for wind energy development than the mountains from 2031 to 2050. This study can serve as a guide in gaining insights into future changes in wind energy across Central Asia and provide a scientific basis for decision makers in the formulation of policies for addressing climate change.
WOS关键词NORTHERN-HEMISPHERE ; EASTERN CHINA ; PRECIPITATION ; TEMPERATURE ; VARIABILITY ; INCREASE ; DECLINE ; AFRICA
资助项目Key Research and Development Program of China[2023YFF0805504] ; National Natural Science Foundation of China[42375174] ; National Natural Science Foundation of China[42361134582] ; Yunnan Province Basic Research Project[202401AW070008] ; Yunnan Province Basic Research Project[202301AT070199] ; High-level Talent Project of Yunnan Province-Special Program for Young Talents ; High-level Talent Program of Yunnan University-Donglu Young Scholars ; Chinese Jiangsu Collaborative Innovation Center for Climate Change China
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
语种英语
WOS记录号WOS:001310424900001
出版者KEAI PUBLISHING LTD
资助机构Key Research and Development Program of China ; National Natural Science Foundation of China ; Yunnan Province Basic Research Project ; High-level Talent Project of Yunnan Province-Special Program for Young Talents ; High-level Talent Program of Yunnan University-Donglu Young Scholars ; Chinese Jiangsu Collaborative Innovation Center for Climate Change China
源URL[http://ir.igsnrr.ac.cn/handle/311030/208429]  
专题区域可持续发展分析与模拟院重点实验室_外文论文
通讯作者Wu, Jian
作者单位1.Univ Gothenburg, Dept Earth Sci, Reg Climate Grp, S-40530 Gothenburg, Sweden
2.Consejo Super Invest Cientif CIDE CSIC UV Generali, Ctr Invest Desertificac, Climate Atmosphere & Ocean Lab, Climatoc Lab, Moncada 46113, Spain
3.Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China
4.Sun Yat Sen Univ, Sch Atmospher Sci, Zhuhai 519082, Peoples R China
5.Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R China
6.Chinese Acad Sci, Key Lab Reg Sustainable Dev Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
7.Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China
8.Chinese Acad Sci, Key Lab Reg Climate Environm Temperate East Asia, Inst Atmospher Phys, Beijing 100029, Peoples R China
9.Yunnan Univ, Dept Atmospher Sci, Key Lab Atmospher Environm & Proc Boundary Layer L, Kunming 650091, Peoples R China
推荐引用方式
GB/T 7714		 Zha, Jin-Lin,Chuan, Ting,Qiu, Yuan,et al. Projected near-surface wind speed and wind energy over Central Asia using dynamical downscaling with bias-corrected global climate models[J]. ADVANCES IN CLIMATE CHANGE RESEARCH,2024,15(4):669-679.
APA Zha, Jin-Lin.,Chuan, Ting.,Qiu, Yuan.,Wu, Jian.,Zhao, De-Ming.,...&Chen, Deliang.(2024).Projected near-surface wind speed and wind energy over Central Asia using dynamical downscaling with bias-corrected global climate models.ADVANCES IN CLIMATE CHANGE RESEARCH,15(4),669-679.
MLA Zha, Jin-Lin,et al."Projected near-surface wind speed and wind energy over Central Asia using dynamical downscaling with bias-corrected global climate models".ADVANCES IN CLIMATE CHANGE RESEARCH 15.4(2024):669-679.

入库方式： OAI收割

来源：地理科学与资源研究所

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