摘要
利用区域性极端事件客观识别法(Objective Identification Technique for Regional Extreme Events,OITREE)和1960-2010年中国西南地区(四川、云南、贵州省和重庆市)101个站综合气象干旱指数(CI)进行区域性气象干旱事件识别研究,确定了相应的()ITREE方法参数组,并识别得出87次中国西南地区区域性气象干旱事件,其中9次达到极端强度,而2009年9月一2010年4月发生的特大干旱是中国西南地区近50年最严重的区域性气象干旱事件。进一步分析表明,中国西南地区区域性气象干旱事件的持续时间一般为10—80 d,最长可达231 d;11—4月是西南地区的旱季。云南和四川南部是西南干旱的频发和强度中心地区;强的(极端及重度)干旱事件可分为5种分布类型,其中南部型出现机会最多。过去50年西南地区区域性气象干旱事件频次显著增多,强度有所增强,其主要原因可能是该地区降水量显著减少所致,而气温升高也起到了推波助澜的作用。
An objective identification technique for the regional extreme events （OITREE）and the daily composite-drought index （CI） of the 101 stations in southwestern China including Sichuan,Yunnan,Guizhou and Chongqing were used to investigate the southwest-ern China regional meteorological drought events during 1960-2010.The values of the parameters of the OITREE method were deter-mined.87 events were identified,including 9 extreme events in which the 2009/2010 severe drought in southwestern China is the most serious meteorological drought event for the past 50 years.Further analysis reveals that：The durations are generally between 10-80 d,with the longest period being 231 d.November to April is the dry season in southwestern China.As far as the regional distribution is concerned,Yunnan and southern Sichuan have the highest drought frequency and intensity,and strong （extreme and severe）south-western China regional meteorological drought events could be divided into five types,with the Southern type occurring more frequent-ly.During the past 50 years,the southwestern China regional meteorological drought events show a significant increase trend in fre-quency and an obvious increase trend in intensity,for which the main reason may be the significant decrease of the annual precipitation in this region,with a contribution by the significant increase trend in temperature.
出处
《气象学报》
CAS
CSCD
北大核心
2014年第2期266-276,共11页
Acta Meteorologica Sinica
基金
国家自然科学基金项目(41175075)
中国气象局气候变化专项“近50年我国干旱频发地区的区域性气象干旱事件的检测与变化”
关键词
中国西南地区
区域性气象干旱事件
时间变化
地域特征
Southwestern China, Regional meteorological drought event, Temporal characteristics, Spatial distribution
