摘要
The contributions of urban surface expansion to regional warming over subregions of Shanghai and Shanghai as a whole using different methods to calculate the daily mean surface temperature(SAT),including the averages of four daily time-records(0000,0600,1200,and 1800 UTC;T4),eight daily time-records(0000,0300,0600,0900,1200,1500,1800,and 2100 UTC;T8),and the averages of the SAT maximum(Tmax)and minimum(Tmin),Txn,were compared based on simulated results using nested numerical intergrations with the Weather Research and Forecasting regional climate model,where only the satellite-retrieved urban surface distributions differed between two numerical experiments.The contributions from urban-related warming expressed similar intensities when using T8 and Txn,while the smallest values occurred when using T4 over different subregions of Shanghai(with the exception of areas that were defined as urban for both time periods(U2U))and Shanghai as a whole.Similar values for the changing trends could be detected over different subregions when no urban surface expansion(EX1)was detected for both T4 and Txn.The corresponding values increased under urban surface expansion(EX2)and varied over different subregions,revealing much stronger intensities over urban-surface expansion areas;the weakest intensities occurred over U2U areas.The increasing trends for EX2 and relative contributions when using T4 were smaller than those when using Txn,with the exception of those over U2U areas,which could be explained by the changing trends in Tmax and Tmin due to urban surface expansion,especially during intense urban expansion periods.
本文利用反映过去三十多年中国城市下垫面扩张的土地利用遥感数据开展高分辨率数值试验,比较了基于不同方法计算日平均气温(一天四次平均T_4,日最高和最低气温平均T_(xn))对量化上海城市下垫面扩张增暖贡献的影响。不考虑城市下垫面变化,T_4和T_(xn)计算的增温趋势在不同子区域(城市-城市(U2U),非城市-城市(N2U)和整个区域)基本一致,考虑城市下垫面扩张后,T_4和T_(xn)计算的增温趋势在城市下垫面扩张区差别明显。基于T_4和T_(xn)计算的增暖贡献差异主要源于城市下垫面扩张对日最高和最低气温的影响不同。
基金
This work was supported by the National Natural Science Foundation of China [grant numbers 41775087 and41675149]
the National Key R&D Program of China [grant number 2016YFA0600403]
the Chinese Academy of Sciences Strategic Priority Program [grant number XDA05090206]
the National Key Basic Research Program on Global Change [grant number 2011CB952003]
the Jiangsu Collaborative Innovation Center for Climatic Change
