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1962~2012年西南地区极端温度事件时空变化特征
引用本文:袁文德,郑江坤.1962~2012年西南地区极端温度事件时空变化特征[J].长江流域资源与环境,2015,24(7):1246-1254.
作者姓名:袁文德  郑江坤
作者单位:四川农业大学长江上游林业生态工程四川省重点实验室, 四川 雅安 625014
基金项目:中国博士后科学基金面上项目(2012M511938),四川省高等学校建设项目:“水土保持与荒漠化防治重点实验室”,国家“十二五”科技支撑计划项目(2011BAC09B05)
摘    要:基于西南地区88站1962~2012年日气温数据,采用百分位阈值法定义极端温度事件,结合线性倾向率、Mann-Kendall秩次相关法、反距离加权插值法对其时空变化进行了分析。结果表明:极端温度指数存在明显的空间分布差异,暖日指数、暖夜指数、冷夜指数和年内日最低气温整体上均由东南向西北逐渐降低;霜冻天指数则由东南向西北部逐渐升高,西北部梯度变化明显;冷日指数和年内日最高气温呈马鞍状分布,较高值均在西南和东北部;因多数地区高温天数极少,故没有明显的梯度变化。霜冻天指数、冷夜指数和冷日指数减少趋势明显,分别为2.7、4.6和3.5d/10a;暖日指数和暖夜指数、年内日最低气温和最高气温均呈增加趋势,分别为3.6、4.9、0.4和0.1℃/10a;高温天指数变化不显著。整体上来看,西南地区极端高温事件和极端低温事件分别呈上升和下降趋势,但有部分区域呈相反变化趋势,体现出西南地区气候变化的独特性。

关 键 词:极端温度  线性倾向率  MannKendall秩次相关法  空间分布  西南地区  

SPATIAL AND TEMPORAL VARIATIONS OF EXTREME TEMPERATURE EVENTS IN SOUTHWESTERN CHINA DURING 1962-2012
YUAN Wen-de,ZHENG Jiang-kun.SPATIAL AND TEMPORAL VARIATIONS OF EXTREME TEMPERATURE EVENTS IN SOUTHWESTERN CHINA DURING 1962-2012[J].Resources and Environment in the Yangtza Basin,2015,24(7):1246-1254.
Authors:YUAN Wen-de  ZHENG Jiang-kun
Institution:Key Laboratory of Ecological Engineering of Sichuan Province, College of Forestry, Sichuan Agricultural University, Ya'an 625014, China
Abstract:In recent years, the magnitude of global warming was more serious than before, increasing the occurrence frequency of drought, frost and other natural disasters. In Southwestern China, persistent snow, ice storms and persistent drought events attracted a lot of attentions since 2008. Therefore, it is very important to investigate the variation of extreme temperature events and its mechanisms. By using daily maximum and minimum temperature at 88 meteorological stations in Southwestern China in the period between 1962 and 2012 provided by China Meteorological Administration, temporal and spatial variation of extreme temperature events were investigated using the methods of regression analysis, Mann-Kendall rank correlation and inverse distance weighted interpolation. Eight indices of extreme temperature were studied. The results indicated that extreme temperature indices were obviously different in spatial distribution. The indices of warm days, warm nights, cold nights, and extra-minimum air temperature decreased gradually from southeast to northwest, with changing rates of 13.1-36.3℃,-1-23.5℃,-15-15.2℃ and-30.6-6.7℃, respectively. Nevertheless the index of frost days increased in the same direction with maximum change over the northwest of Sichuan. Both the distributions of cold days index and extra-maximum air temperature are like a saddle, with the highest values over the southwest and northeast. There were few high temperature days over most areas. Obvious gradient of hot day index can only be seen over central Yunnan. The indices of cold day, frost days and cold nights have significantly decreased by the rate of 2.7 d/10 a, 3.5d/10 a and 4.9 d/10 a, respectively. Warm days indices, warm nights indices, extra-minimum air temperature and extra-maximum air temperature have significant increased by the rate of 1 d/10 a, 4.7 d/10 a, 0.4℃/10 a and 0.1℃/10 a, respectively. Only hot days indices did not change significantly. The magnitudes of changes in cold indices are much greater than those in warm indices. The changing ranges of night indices were larger than those of day indices, which indicated that the changes of day and night temperature were asymmetrical. The variation of extreme cold indices showed a downward trend, and that of extreme warm indices showed an upward trend. Their overall performance had a warming trend over Southwestern China. Whereas, the variation range of extreme temperature events was less than other regions of China which reflected the unique feature of climate change over Southwest China.
Keywords:extreme temperature event  linear trend rate  Mann-Kendall rank correlation method  spatial distribution  Southwestern China
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