长江流域资源与环境 >> 2018, Vol. 27 >> Issue (06): 1351-.doi: 10.11870/cjlyzyyhj201806019

• 生态环境 • 上一篇    下一篇

1951~2013年江苏省极端最高和最低气温变化趋势及概率特征

尹义星1,王小军2,3,叶正伟4,焦士兴 5,潘   欣1   

  1. (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
  • 出版日期:2018-06-20

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

YIN Yi-xing 1, WANG Xiao-jun 2,3, YE Zheng-wei4, JIAO Shi-xing 5, PAN Xin 1   

  1. (1. College of Hydrometeorology, Nanjing University of Information Science and Technology, Nanjing  210044,China; 2.Nanjing Hydraulic Research Institute, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing 210029,China;
    3. Research Center for Climate Change, Ministry of Water Resources, Nanjing 210029,China;
    4. Huaiyin Normal University, School of Urban and Environmental Sciences, Huaiyin 223300,China;
    5.Department of Resource & Environment and Tourism, Anyang Normal University, Anyang 455002,China)
  • Online:2018-06-20

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RClimDex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ArcGIS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。
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

Abstract: 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 2000s for extreme maximum temperature, and they are mainly during the 1980s 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.
Key words:extreme maximum temperature; extreme minimum temperature; improved Mann-Kendall test; probability characteristics

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