1951～2013年江苏省极端最高和最低气温变化趋势及概率特征  

Trend and Probability Characteristics of Extreme Maximum and Minimum Temperature in the Jiangsu Province from 1951 to 2013

作　　者：尹义星[1] 王小军[2,3] 叶正伟[4] 焦士兴[5] 潘欣[1] YIN Yi-xing;WANG Xiao-jun;YE Zheng-wei;JIAO Shi-xing;PAN Xin(College of Hydrometeomlogy, Nanjing University of Information Science and Technology, Nanjing 210044, China;Nanjing Hydraulic Research Institute, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing 210029, China;Research Center for Climate Change, Ministry of Water Resources, Nanjing 210029, China;Huaiyin Normal University, School of Urban and Environmental Sciences, Huaiyin 223300, China;Department of Resource ＆ Environment and Tourism, Anyang Normal University, Anyang 455002, China)

机构地区：[1]南京信息工程大学水文气象学院,江苏南京210044 [2]南京水利科学研究院水文水资源与水利工程科学国家重点实验室,江苏南京210029 [3]水利部应对气候变化研究中心,江苏南京210029 [4]淮阴师范学院城市与环境学院,江苏淮安223300 [5]安阳师范学院资源环境与旅游学院,河南安阳455002

出　　处：《长江流域资源与环境》2018年第6期1351-1360,共10页Resources and Environment in the Yangtze Basin

基　　金：国家自然科学基金(41671022;41471425);江苏省普通高校自然科学研究项目(15KJB170014);国家"万人计划"青年拔尖人才支持计划;江苏省"333高层次人才培养工程"专项资金;中央财政水资源节约;管理与保护项目(126302001000160081)

摘　　要：选用江苏省13个气象站1951~2013年的日最高、最低气温资料,采用RClim Dex软件包提取极端气温指数,并借助线性倾向估计、改进的Mann-Kendall趋势和突变检验、GEV模型等方法研究极端气温的趋势和概率特征,并基于Arc GIS对百年一遇的极端气温进行空间分布特征的分析。结果表明:(1)以最高气温来度量的冰冻日数和冷昼日数呈下降趋势,夏季日数和暖昼日数呈上升趋势;以最低气温来度量的霜冻日数和冷夜日数呈下降趋势,炎热夜数和暖夜日数呈上升趋势。(2)改进的Mann-Kendall检验表明,极端最高气温的上升趋势弱于最低气温,极端最高气温主要在2000年左右发生突变,而最低气温的突变主要发生在1980年代。(3)基于平稳和非平稳GEV模型得到极端最高和最低气温的重现水平,其中非平稳模型的重现水平随序列存在的趋势而变化。(4)江苏省百年一遇极端最高气温的空间分布由西到东递减,最低气温则呈现由西北到东南递增的变化。The paper selected the daily data of maximum and minimum temperature from the 13 meteorological stations in the Jiangsu Province,and explored the trend and probability characteristics based on linear trend estimation,improved Mann-Kendall trend and abrupt change test and GEV model; Moreover, the spatial characteristics of extreme temperature with the return period of 100 years are also investigated based on ARCGIS.The results indicate：① For the indices measured by maximum temperature,ice days and cool days show negative trend; summer days and warm days show positive trend. For the indices measured by minimum temperature,frost days and cool nights show decreasing trend; tropical nights and warm nights show increasing trend.② The upward trend of extreme minimum temperature is weaker than that of extreme maximum temperature based on the improved Mann-Kendall test. The abrupt years are mainly during the 2000 s for extreme maximum temperature,and they are mainly during the 1980 s for extreme minimum temperature.③ The return levels for extreme maximum and minimum temperature were obtained using the stationary and non-stationary GEV models. The return level obtained by the non-stationary GEV model change with the trend of the original time series.④ The spatial patterns of extreme maximum temperature for return level of 100 years increase from the west to the east,and those of the extreme minimum temperature decrease from the northwest to the southeast.

关 键 词：极端最高气温 极端最低气温 改进的Mann-Kendall检验 概率特征 

分 类 号：P423[天文地球—大气科学及气象学]