摘要:选取中国东部季风区长春、北京、武汉和广州市4个代表性城市，利用2012年9月至2014年8月和2016年1月至2017年12月共4年高密度自动站气温资料，比较了南北不同纬度带城市热岛效应（Urban Heat Island, UHI）强度的时空特征。结果表明：1）长春、北京、武汉和广州市建城区年平均UHII分别为0.96°C、1.06°C、0.91°C和0.78°C，北方城市秋、冬季多呈静稳和逆温天气，加上人为热释放量高于其他季节，UHII明显高于春夏季；而南方城市秋季“秋高气爽”，利于热岛的发生发展，冬季和夏季UHII次之，且季节间差异较小；2）4个城市热岛形成机制是一致的，均表现为夜间高于白天，清晨和午后UHII分别开始下降和上升；武汉市内水体较多，UHII日内波动幅度最大，广州市四季温和，UHII波动幅度最小；3）与南方城市比较，北方城市秋、冬季夜间高值时段长，白天低值时段短。本文揭示的南北不同气候带城市热岛强度差异，对于城市规划和城市运行管理具有实际意义。
关键词:气候带/
代表城市/
城市热岛强度/
空间分布/
时间变化
Abstract:The spatial distribution and temporal variation of the Urban Heat Island Intensity (UHII) are analyzed by using the hourly surface air temperature (SAT) data from automatic weather stations during September 2012?August 2014 and January 2016?December 2017 over four cities, those are Changchun, Beijing, Wuhan, and Guangzhou. The annual mean UHII in built-up areas of these cities are found as 0.96°C, 1.06°C, 0.91°C, and 0.78°C, respectively. The UHII in northern cities is higher in spring and summer than in autumn and winter due to calm and inversion weather and higher anthropogenic heat release than in other seasons. However, the autumn UHII is the most obvious in southern cities beacause the clear sky and crisp air is conducive to the development of heat island, followed by the UHII of winter and summer, and the UHII difference among the four seasons is small. Besides, the diurnal variation of UHII in each city is characterized by a stronger UHII at night than during the day, with UHII beginning to decline (rise) in the early morning (afternoon). The amplitude of UHII diurnal variation is the largest in Wuhan due to several water bodies and the smallest in Guangzhou due to the mild climate. For the UHII diurnal variations, the steadily strong UHII period at night (day) is longer (shorter) in autumn and winter for the northern cities. The UHII difference between north and south climate zones has practical significance for urban planning and urban operations management.
Key words:Climatic zone/
Representative city/
Urban Heat Island Intensity/
Spatial distribution/
Time variation
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