城市化对长沙市两气象站气温记录的影响

为深入认识城市对其附近气象站气温的影响，采用位于长沙市区东部和西部两个气象观测站的2007-2009年的逐日气温、风向和风速资料，结合地表覆盖特征数据，对比分析了两站气象记录差异，并通过改进的城市影响指数模型估算了气温资料中的城市影响偏差。分析显示：（1）2007-2009年东、西气象站逐月平均气温（T_mean）、最高气温（T_max）和最低气温（T_min）差异很大，最大差异分别可达0.90℃、0.83℃和1.34℃；（2）受城市及风向的影响，两气象站的逐月城市影响指数（K）差异较大，东、西站平均K值分别为2.01和1.50，年内同一台站的K值存在季节变化规律；（3）两站逐月△K与△T之间存在极显著正相关关系；（4）东、西两站2007年T_mean中的城市增温最大，分别达0.63℃和0.45℃。城市附近气象站气温记录受城市规模、风向和风速等因素影响明显，在分析长历时气候变化特征和利用站点记录数据进行空间分析时，有必要对气温数据进行订正。

Urbanization Effects on the Observed Temperature of Two Meteorological Stations in Changsha City

The daily data of temperature, wind direction and wind speed during 2007-2009 of the two meteorological stations located in the east and west regions of Changsha city, as well as the land cover dataset, were analyzed for better understanding of the impact of urbanization on the temperature records of meteorological stations close to city. The differences of climatic factors between the two stations were contrastively analyzed and the urban biases of temperature data were estimated by using the modified urban impact indicators. The results showed that the monthly mean temperature (T_mean), mean maximum temperature (T_max) and mean minimum temperature (T_min) at two stations differed greatly, and the largest difference were up to 0.90℃, 0.83℃ and 1.34℃, respectively. As influenced by urban area and wind directions, significant difference of monthly urban impact indicator (△K) between the two stations was observed, and the average K of East station and West station were 2.01 and 1.50, respectively. There was seasonal variation of the K at each station, and the △K and △T of two stations were positively and significantly correlated. The largest urban warming in T_mean of East station and West station were observed in 2007, which were up to 0.63℃ and 0.45℃, respectively. It is necessary to adjust the temperature data when analyzing the long-term climate change and using station records to analyze the spatial change of climate because the temperature records of meteorological stations near cities were significantly influenced by urban size, wind direction and wind speed.