The impacts of three periods of urban land expansion during 1990–2010 on near-surface air temperature in summer in Beijing were simulated in this study, and then the interrelation between heat waves and urban warming...The impacts of three periods of urban land expansion during 1990–2010 on near-surface air temperature in summer in Beijing were simulated in this study, and then the interrelation between heat waves and urban warming was assessed. We ran the sensitivity tests using the mesoscale Weather Research and Forecasting model coupled with a single urban canopy model,as well as high-resolution land cover data. The warming area expanded approximately at the same scale as the urban land expansion. The average regional warming induced by urban expansion increased but the warming speed declined slightly during 2000–2010. The smallest warming occurred at noon and then increased gradually in the afternoon before peaking at around 2000 LST—the time of sunset. In the daytime, urban warming was primarily caused by the decrease in latent heat flux at the urban surface. Urbanization led to more ground heat flux during the day and then more release at night, which resulted in nocturnal warming. Urban warming at night was higher than that in the day, although the nighttime increment in sensible heat flux was smaller. This was because the shallower planetary boundary layer at night reduced the release efficiency of near-surface heat. The simulated results also suggested that heat waves or high temperature weather enhanced urban warming intensity at night. Heat waves caused more heat to be stored in the surface during the day, greater heat released at night, and thus higher nighttime warming. Our results demonstrate a positive feedback effect between urban warming and heat waves in urban areas.展开更多
采用"自上而下"的能源清单法,研究了长株潭城市群2017年人为热排放量及其时空分布特征;同时,利用中尺度天气预报模式(Weather Research and Forecasting, WRF)及其耦合的UCM对夏冬两季分别进行数值模拟试验,定量分析了不同类...采用"自上而下"的能源清单法,研究了长株潭城市群2017年人为热排放量及其时空分布特征;同时,利用中尺度天气预报模式(Weather Research and Forecasting, WRF)及其耦合的UCM对夏冬两季分别进行数值模拟试验,定量分析了不同类型建成区人为热排放增温效应的季节性差异。结果表明:(1)长株潭2017年人为热排放总量为3.49×10^(17)J/a,平均人为热排放强度为14.22 W/m^(2),工业、建筑、交通和人体新城代谢对人为热的贡献率分别为48.15%、40%、11.3%和0.55%。(2)人为热的引入使得城市群主城区夏季和冬季的平均温度分别升高了约0.7℃和1.5℃;冬季增温效果是夏季的2倍。(3)不同密度分区人为热排放导致的增温效果不同,总的来说,工业/商业区>高密度住宅区>低密度住宅区。展开更多
基金supported by the National Basic Research Program of China(Grant No.2015CB953602)the National Social Science Fund of China(Grant No.17BGL256)
文摘The impacts of three periods of urban land expansion during 1990–2010 on near-surface air temperature in summer in Beijing were simulated in this study, and then the interrelation between heat waves and urban warming was assessed. We ran the sensitivity tests using the mesoscale Weather Research and Forecasting model coupled with a single urban canopy model,as well as high-resolution land cover data. The warming area expanded approximately at the same scale as the urban land expansion. The average regional warming induced by urban expansion increased but the warming speed declined slightly during 2000–2010. The smallest warming occurred at noon and then increased gradually in the afternoon before peaking at around 2000 LST—the time of sunset. In the daytime, urban warming was primarily caused by the decrease in latent heat flux at the urban surface. Urbanization led to more ground heat flux during the day and then more release at night, which resulted in nocturnal warming. Urban warming at night was higher than that in the day, although the nighttime increment in sensible heat flux was smaller. This was because the shallower planetary boundary layer at night reduced the release efficiency of near-surface heat. The simulated results also suggested that heat waves or high temperature weather enhanced urban warming intensity at night. Heat waves caused more heat to be stored in the surface during the day, greater heat released at night, and thus higher nighttime warming. Our results demonstrate a positive feedback effect between urban warming and heat waves in urban areas.
文摘采用"自上而下"的能源清单法,研究了长株潭城市群2017年人为热排放量及其时空分布特征;同时,利用中尺度天气预报模式(Weather Research and Forecasting, WRF)及其耦合的UCM对夏冬两季分别进行数值模拟试验,定量分析了不同类型建成区人为热排放增温效应的季节性差异。结果表明:(1)长株潭2017年人为热排放总量为3.49×10^(17)J/a,平均人为热排放强度为14.22 W/m^(2),工业、建筑、交通和人体新城代谢对人为热的贡献率分别为48.15%、40%、11.3%和0.55%。(2)人为热的引入使得城市群主城区夏季和冬季的平均温度分别升高了约0.7℃和1.5℃;冬季增温效果是夏季的2倍。(3)不同密度分区人为热排放导致的增温效果不同,总的来说,工业/商业区>高密度住宅区>低密度住宅区。
