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1951—2010年长沙市极端气温事件的变化特征
引用本文:陈 勇,陈 阳,范 昱.1951—2010年长沙市极端气温事件的变化特征[J].气象与环境科学,2012,35(3):41-44.
作者姓名:陈 勇  陈 阳  范 昱
作者单位:1. 长沙市气象局,长沙,410205
2. 湘西自治州气象局,湖南吉首,416000
基金项目:长沙市气象局科研项目“长沙市应对气候变化的可行性研究报告”
摘    要:利用1951-2010年长沙最高和最低气温资料,运用国际上通用的百分位阈值法确定暖日、暖夜和冷日、冷夜数,采用线性倾向估计法和M-K突变检测等方法,研究长沙市60 a来极端气温事件的时空变化特征。结果表明,暖日和暖夜数分别以3.48个.(10a)-1和3.06个.(10a)-1的速率显著增加,冷日和冷夜数分别以-2.13个.(10a)-1和-1.78个.(10a)-1的速率显著减少,白天增暖幅度大于夜间增暖幅度。研究还表明,阶段性特征明显,近60 a来暖日和冷日、冷夜数发生了明显的突变。暖日数增加秋季最显著,春季次之;暖夜数增加夏季最显著,冬季次之。冷日(夜)数减少的季节主要是春季和冬季;四季都在变暖,但以春季、冬季变暖最明显。7月暖日(暖夜)数增加最显著,4月和2月冷日(冷夜)数减少最显著。

关 键 词:极端气温  空间分布  年代际变化

Variation Characteristics of Extreme Temperature Events in Changsha from 1951 to 2010
Chen Yong,Chen Yang,Fan Yu.Variation Characteristics of Extreme Temperature Events in Changsha from 1951 to 2010[J].Meteorological and Environmental Sciences,2012,35(3):41-44.
Authors:Chen Yong  Chen Yang  Fan Yu
Affiliation:1. Changsha Meteorological Office, Changsha 410205, China; 2. West Hunan Meteorological Office, Jishou 416000, China)
Abstract:Based on the highest and lowest temperature data in Changsha from 1951 to 2010, by u- sing the international common percentage threshold method which can determine the warm day, warm night, cold day and cold night, linear tendency estimation method and M-K mutations detection method, the temporal and spatial variation characteristics of extreme temperature events in Changsha during the past 60 years were analyzed. The research results indicated that the warm day and warm night increased with a rate of 3.48 d ·(10a) -1 and 3.06 d · (10a) -1, while the cold day and cold night decreased with a rate of -2.13 d· (10a) -1 and - 1.78 d · (10a) -1. The warming in daytime increased more than in night. It also indicated that the periodic characteristic was significant and the warm day, cold day and cold night had abrupt changes. The most significant increase of warm day was in fall, followed by in spring. The most significant increase of warm night was in summer, followed by in winter. The decrease of cold day or night happened most in spring and winter. All seasons were becoming warmer, especially in spring and winter. The most significant increase of warm day or night was in July, and the most signifi- cant decrease of cold day or night was in April and February.
Keywords:extreme temperature  spatial distribution  interdecadal variability
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