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一种大范围干旱的识别方法及其应用
引用本文:殷雨婷,荣艳淑,吕星玥,刘书言.一种大范围干旱的识别方法及其应用[J].气象科学,2021,41(4):495-506.
作者姓名:殷雨婷  荣艳淑  吕星玥  刘书言
作者单位:河海大学 水文水资源学院, 南京 210098
基金项目:国家重点基础研究发展计划项目(2016YFA0601504)
摘    要:基于日本APHRO格点降水数据计算格点SPI序列,兼顾时空连续性,定义了一种大范围长历时干旱的识别方法。该方法以我国国土面积的10%作为大范围干旱事件影响范围的最小阈值,同时给定了干旱事件影响区域的空间连续和时间连续的判定标准,另辅以干旱烈度计算方法和干旱中心的识别方法,给出了此类干旱事件的面积、历时、烈度及干旱中心的指数定义和事件的识别过程。在此基础上,识别了我国1961—2015年以来的69次大范围干旱事件,得出这69次大范围干旱事件的平均面积指数为30.49%,平均干旱历时为8.15个月,平均干旱烈度为-4.192。利用此方法对1998—2002年发生在华北地区的持续性区域干旱事件进行再分析。结果表明,这一时期的干旱事件不仅局限于华北地区,同时也波及到东北、西北、西南和东南等地,涉及了4次大范围长历时的干旱过程。

关 键 词:干旱  大范围长历时干旱  SPI  面积指数  历时指数  烈度指数
收稿时间:2020/12/22 0:00:00

An identification method for a large-scale drought and its application
Institution:College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Abstract:The APHRO grid precipitation data was used to calculate SPI series. Taking the continuity of time and space into account, a identifying method of large-scale drought events featureswas formulated, which takes 10% of Chinese land area as a minimum threshold of a large-scale drought event, and gives the criteria of spatial continuity and temporal continuity of the affected area of drought events. At the same time, with the recognition method of droughtcenterand calculation method of drought intensity, the area, duration, intensity and the drought index definitions and event identification process were given. And 69 long-scale drought events in China from 1961 to 2015 were assessed, which conclude that the average area index, average drought duration and average drought intensity are 30.49%, 8.15 months and -4.192 in China from 1961 to 2015. In addition, a persistent drought event occurred in North China from 1998 to 2002 was reanalyzed. Results show that notonly North China were affected by this drought, but Northwest China, Northeast China, Southwest China and Southeast China etc. Specifically, four large-scale droughts occurred in China from 1998 to 2002.
Keywords:drought  large-scale and long-duration drought events  SPI  area index  duration index  severity index
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