吴利华, 彭汐, 马月伟, 程希平, 巩合德, 董李勤. 1951—2016年昆明极端气温和降水事件的变化特征[J]. 云南大学学报(自然科学版), 2019, 41(1): 91-104. doi: 10.7540/j.ynu.20180144
引用本文: 吴利华, 彭汐, 马月伟, 程希平, 巩合德, 董李勤. 1951—2016年昆明极端气温和降水事件的变化特征[J]. 云南大学学报(自然科学版), 2019, 41(1): 91-104. doi: 10.7540/j.ynu.20180144
WU Li-hua, PENG Xi, MA Yue-wei, CHENG Xi-ping, GONG He-de, DONG Li-qin. Variation characteristics of extreme temperature and precipitation events during 1951—2016 in Kunming[J]. Journal of Yunnan University: Natural Sciences Edition, 2019, 41(1): 91-104. DOI: 10.7540/j.ynu.20180144
Citation: WU Li-hua, PENG Xi, MA Yue-wei, CHENG Xi-ping, GONG He-de, DONG Li-qin. Variation characteristics of extreme temperature and precipitation events during 1951—2016 in Kunming[J]. Journal of Yunnan University: Natural Sciences Edition, 2019, 41(1): 91-104. DOI: 10.7540/j.ynu.20180144

1951—2016年昆明极端气温和降水事件的变化特征

Variation characteristics of extreme temperature and precipitation events during 1951—2016 in Kunming

  • 摘要: 为系统了解昆明极端气温和降水事件的变化特征,基于昆明气象站1951—2016年逐日最高气温、最低气温和降水量,采用线性倾向估计、Mann-Kendall突变检验和Morlet复小波方法对16个极端气温指数和11个极端降水指数的变化趋势、突变特性和周期特征进行了分析和研究. ①变化趋势分析结果表明:极端气温指数霜冻日数、冷夜日数、冷昼日数、冷日持续指数和月平均日较差呈明显下降趋势,月最低气温极大值、月最低气温极小值、夏季日数、热夜日数、暖夜日数、暖昼日数和热日持续指数则呈明显上升趋势,而月最高气温极大值、月最高气温极小值、冰封日数和作物生长期呈不显著上升趋势,并且月最低气温指数比月最高气温指数升温幅度快. 极端降水指数强降水量、特强降水量、持续干期、持续湿期、1日最大降水量、5日最大降水量、降水强度均呈上升趋势,日降水≥ 1 mm的降水日数、中雨日数、大雨日数、年总降水量均呈下降趋势. ②突变检验分析结果表明:极端气温和降水指数的突变点大部分集中在20世纪80年代末至21世纪初,各指数发生突变的时间不同,极端冷事件指数在突变点后呈显著下降趋势,而极端暖事件指数在突变点后呈显著上升趋势. ③周期变化分析结果表明:极端气温指数存在2~6个准周期,介于4~57 a之间,存在1~3个主周期,介于6~55 a之间. 极端降水指数存在4~6个准周期,介于4~57 a之间,存在1~3个主周期,介于15~57 a之间. 部分极端气温指数或降水指数有着相同或相近的主周期.

     

    Abstract: In order to systematically reveal the variation characteristics of extreme temperature and precipitation events in Kunming, based on the data of daily maximum and minimum temperature and daily precipitation from 1951 to 2016 at Kunming meteorological stations, the variation trends, mutation characteristics and periodic change of 16 extreme temperature indices and 11 extreme precipitation indices have been analyzed with methods of the linear regression analysis, Mann-Kendall abrupt change test, and Morlet complex wavelet analysis. Firstly, the results of variation trends are as follow: there are significant downward trends of extreme temperature indices of FD, TN10p, TX10p, CSDI and DTR. However, there are significant upward trends of extreme temperature indices of TNx, TNn, SU, TR, TN90p, TX90p and WSDI. There are non-significant upward trends of extreme temperature indices of TXx, TXn, ID and GSL. Moreover, the monthly minimum temperature indices increases faster than the monthly maximum temperature indices. The extreme precipitation indices of R95pTOT, R99pTOT, CDD, CWD, Rx1day, Rx5day and SDII show upward trends whereas the indices of R1, R10, R20 and PRCPTOT show downward trends. Secondly, the results of mutation test are as follows: most of the abrupt change years of extreme temperature and precipitation indices are from the late 1980s to early 21st century. And there are different mutation years of extreme indices. The extreme indices of cold events show significant downward trends after the mutation years, while the extreme indices of warm events show significant upward trends after the mutation years. In addition, the periodic results of wavelet analysis are as follows : the extreme temperature indices present 2—6 quasi-periods of ranging from 4 to 57 years, with 1—3 main periods ranging from 6 to 55 years. The extreme precipitation indices present 4—6 quasi-periods of ranging from 4 to 57 years, with 1—3 main periods ranging from 15 to 57 years. Therefore, there are parellel or similar main periods for part of the extreme temperature and precipitation indices.

     

/

返回文章
返回