Long-term trend of surface wind speed in the Guangdong-Hong Kong-Macau Greater Bay Area during 1980-2020: Spatiotemporal variation and urbanization effect

被引:4
作者
Wang, Ran [1 ,2 ,3 ]
Mo, Ziwei [1 ,2 ,3 ]
Yang, Liting [4 ]
Chang, Ming [4 ]
Hang, Jian [1 ,2 ,3 ]
机构
[1] Sun Yat Sen Univ, Sch Atmospher Sci, Haiqin 2 Bldg,Zhuhai Campus, Zhuhai 519082, Peoples R China
[2] Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China
[3] Minist Educ, Key Lab Trop Atmosphere Ocean Syst, Zhuhai 519082, Peoples R China
[4] Jinan Univ, Inst Environm & Climate Res, Guangdong Hongkong Macau Joint Lab Collaborat Inno, Guangzhou 511443, Peoples R China
基金
中国国家自然科学基金;
关键词
Surface wind speed; Urbanization; Empirical orthogonal function; Reanalysis; Guangdong -Hong Kong -Macau Greater Bay; Area; LAND-USE; IMPACT; CHINA; INCREASE;
D O I
10.1016/j.uclim.2024.101999
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Understanding the surface wind speed variations is important for the climate and air quality assessment in the Guangdong -Hong Kong -Macau Greater Bay Area (GBA), known as the world class urban agglomeration in China. This study investigates the spatial and temporal variations of surface mean wind speed (MWS) in the GBA from 1980 to 2020, drawing upon ground observations and reanalysis data. After accounting for station relocations, the observed wind speed demonstrated a fluctuating declining trend of -0.036 m center dot s - 1 per decade over the examined period in line with reanalysis data. Wind speeds were found stronger during winter and daytime than summer and nighttime. The southern coastal regions exhibited higher MWS compared with northern mountainous areas. The Empirical Orthogonal Function (EOF) revealed the dominant mode of MWS changes was characterized by a cyclical pattern lasting over 20 years, probably influenced by atmospheric circulation. The urbanization reduced the observed wind speeds by 4.71% - 10.11% over the past decade (2011-2020) in urban areas of the GBA based on urbanminus -rural (UMR), observation -minus -reanalysis (OMR), and urban impact factor (UIF) methods. The long-term spatio-temporal analyses of MWS could benefit the climate and air quality studies and provide data support for regional and micro -scale modeling in the GBA.
引用
收藏
页数:13
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