城市化对北京气象站极端气温指数趋势变化的影响

Urban effect on trends of extreme temperature indices at Beijing Meteorological Station

利用5个乡村气象站和北京气象站(简称北京站)1960～2008年日最高、最低气温资料,比较分析了北京地区城市和乡村极端气温指数年、季节的时间变化以及城市化对北京站各极端气温指数趋势变化的影响.结果表明:1960～2008年北京站霜冻日数、冷夜日数、冷昼日数和平均日较差均显著减少,暖夜日数、暖昼日数、平均最高气温和平均最低气温均显著上升,这些指数的趋势变化全部通过了0.01显著性水平检验,其中霜冻日数、冷夜日数、暖夜日数、平均最低气温、平均气温日较差等与最低气温有关的极端气温指数比冷昼日数、暖昼日数、平均最高气温等基于最高气温记录的极端气温指数变化趋势更明显;城市化因素已致使北京站1960～2008年期间霜冻日数、冷夜日数和平均气温日较差显著减少,暖夜日数和平均最低气温显著增加,这些与最低气温有关的极端气温指数序列,其城市化影响都通过了0.01显著性水平检验.在北京站的霜冻日数、冷夜日数和平均气温日较差长期减少趋势中,城市化影响分别达到-5.78 d/10a、-17.83 d/10a和-0.73℃/10a,而在北京站暖夜日数和平均最低气温增加趋势中,城市化影响分别为14.76 d/10a和0.70 ℃/10a.在所有与最低气温有关的年平均极端气温指数的趋势变化中,城市化影响贡献率均达到100%,即观测到的趋势变化完全是由城市化因素造成的.城市化致使四季北京站冷夜日数、平均气温日较差均显著减少,暖夜日数、平均最低气温均显著增加,其中平均最低气温和平均气温日较差序列中的城市化影响在冬季最大,暖夜日数序列中的城市化影响在夏季最显著.

This research analyzes the urban effect on annual and seasonal trends and the extreme temperature indices at Beijing Meteorological Station, using daily maximum and minimum temperature data of 6 meteorological stations from 1960 to 2008. The results show that the warm nights, warm days, mean maximum temperature and mean minimum temperature increase, the frost days, cold days, cold nights and mean diurnal temperature range decrease at Beijing Observatory during the time period, and these changes are significant statistically. The extreme temperature indices based on daily minimum temperature including frost days, cold nights, warm nights, mean minimum temperature and mean diurnal temperature range undergo more significant changes than those indices based on daily maximum temperature such as cold days, warm days and the mean maximum temperature. The effects of urbanization causes a significant decrease of frosts days （-5.78 d/10a）, cold nights （-17.83 d/10a） and the average daily temperature range or DTR （-0. 73℃/10a）, and a significant increase of warm nights （14. 76 d/10a） and the average minimum temperature （0.70℃/10a） in Beijing Station. Urban effects on the trends of the indices series of Beijing Station relative to daily minimum temperature are significant at the 0.01 confidence level, and the contributions of the urban effect to the overall changes of the annual mean extreme indices series all reach 100%, indicating that the changes observed are overwhelmingly caused by the urban effect. Due to the urban effect, cold nights and DTR significantly decrease, and warm nights and mean minimum temperature significantly increase for all seasons （significant at the 0.01 confidence level）. The urban effects on trends of the indices series of mean minimum temperature and mean DTR are the largest in wintertime, and the urban effects on trends of the indices series of warm nights are mainly in summertime. It is essential to pay more attention to the urban effects on extreme temperature indices trends of China meteorological stations near big cities like Beijing.