1958-2013年豫南地区极端气温变化特征及周期分析

通过对豫南地区每日气温资料的搜集和整理，运用线性倾向估计法、Mann-Kendall突变检验法、Morlet复数小波等方法对WMO发布的10种极端气温指数随时间的变化趋势、突变年份及周期性进行了分析与研究。结果表明，1958-2013年豫南地区的极端最高气温缓慢下降，极端最低气温呈显著上升趋势，夏季日数、热夜日数、暖昼日数、暖夜日数呈现波动上升，冰冻日数、霜冻日数、冷昼日数、冷夜日数呈下降趋势。极端最高（低）气温、冰冻日数、霜冻日数、夏季日数、热夜日数、冷昼日数、冷夜日数、暖昼日数、暖夜日数都存在30a左右的周期。其中极端最低气温、冰冻日数、冷昼日数、冷夜日数、暖昼日数都存在5a及以下的周期。总体来说，1958-2013年，豫南地区极端天气热指数呈上升趋势，极端天气冷指数呈下降趋势。

Analysis on Characteristics of Extreme Temperature Change and Cycle of Southern Henan from 1958 to 2013

Based on daily temperature data in southern Henan from 1958 to 2013, the indices of 10 kinds of extreme temperature published by the WMO were analyzed using linear regression, Mann-Kendall Examination and the Morlet complex wavelet. We describe temporal variability in climate extremes, mutation years, the periodicity of those indices and the relationships between them. We found that from 1958 to 2013, the extreme maximum temperature has fallen slightly and the extreme minimum temperature has increased significantly. The occurrence of extreme maximum temperature, ice days, frost days, cold days, cold nights has significantly decreased by -0.13/10a, -0.36/10a, -3.78/10a, -0.56/10a and -4.06/10a, respectively. The occurrence of extreme minimum temperature, summer days, tropical nights, warm days and warm nights has increased at a rate of 0.63/10a, 2.35/10a, 2.81/10a, 0.07/10a and 7.35/10a, respectively. The extreme temperature exhibited several obvious changing periods: the numbers of summer days, hot nights, warm days and warm nights showed a fluctuated increasing trend and the numbers of ice days, frost days, cold days and cold nights showed a decreasing trend. The extreme maximum temperature and extreme minimum temperature, numbers of ice days, frost days, summer days, hot nights, cold days, cold nights and warm days all have cycles of 30 years. The extreme minimum temperature, ice days, cold days, cold nights and warm days all have cycles of no more than 5 years. Overall, extreme cold indices in southern Henan decreased and the extreme warm indices increased; the possibility of occurrence of extreme weather phenomena has increased. The number of extreme high temperature days and reduction in the number of extreme cold days will likely result in disasters in the future.