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Regionalization of precipitation and the spatiotemporal distribution of extreme precipitation in southwestern China

机译:中国西南地区降水的区域化和极端降水的时空分布

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Daily precipitation data from 1951 to 2010 at 33 meteorological stations in five provinces/cities, including Sichuan Province, Yunnan Province, the Guangxi Zhuang Autonomous Region, Guizhou Province and Chongqing City, are used to partition the study area based on precipitation and analyze the spatiotemporal distribution of extreme precipitation. The rotated empirical orthogonal function (REOF) analysis method is used to divide the study area into five parts according to precipitation. The precipitation exhibited greater fluctuations in the last two decades. This finding indicates that extreme precipitation events are increasing. The frequent occurrence of extreme precipitation has made drought and flood disasters more serious. The Mann-Kendall test (M-K test) and moving t test methods are used to analyze the jump and monotonic trends of extreme precipitation indices. It is determined that extreme precipitation indices, including Rx1d, Rx5d, R95p, R99p, CWD and R10 mm, exhibited a weak upward trend during the past 60 years, suggesting that the precipitation amount in the study area decreased slightly, but the maximum daily precipitation amount (Rx1d) and the extremely wet day precipitation (R99p) increased. This finding indicates that precipitation is more concentrated and the extreme precipitation is more serious. The jump for most of the extreme precipitation indices occurred in the 1990s. In terms of spatial scale, extreme precipitation indices, except CDD and CWD, exhibited an increasing trend from the northwest to the southeast. The regions with especially high or low values are easy to identify. Drought risk in northwest Sichuan and the junction of Sichuan and Yunnan is higher. Guangxi Zhuang Autonomous Region and southern part of Yunnan Province have a higher flood risk. The trends of nine extreme precipitation indices also demonstrated the spatial differences. There are more stations exhibiting upward trends than stations showing downward trends for six extreme precipitation indices. The risk of drought/flood may increase in Yunnan and Guangxi, and the storm flood risk in Chongqing exhibited an increasing trend.
机译:利用1951年至2010年在四川,云南,广西壮族自治区,贵州省和重庆市等五个省/市的33个气象站的每日降水数据,根据降水量划分研究区域并分析时空极端降水的分布。旋转经验正交函数(REOF)分析方法用于根据降水量将研究区域分为五个部分。在过去的二十年中,降水表现出更大的波动。这一发现表明极端降水事件正在增加。极端降水的频繁发生使干旱和洪水灾害更加严重。使用Mann-Kendall检验(M-K检验)和移动t检验方法来分析极端降水指数的跳跃和单调趋势。经确定,过去60年中,包括Rx1d,Rx5d,R95p,R99p,CWD和R10 mm在内的极端降水指数均呈现微弱的上升趋势,这表明研究区域的降水量略有下降,但每日降水量最大。雨量(Rx1d)和极湿天降水(R99p)增加。这一发现表明降水更加集中,极端降水更加严重。大多数极端降水指数的跃迁发生在1990年代。在空间规模上,除CDD和CWD外,极端降水指数从西北向东南呈增加趋势。值特别高或特别低的区域易于识别。川西北和川滇交界处的干旱风险较高。广西壮族自治区和云南省南部的洪灾风险较高。 9个极端降水指数的变化趋势也表明了空间差异。对于六个极端降水指数而言,表现出上升趋势的台站比表现出下降趋势的台站多。云南和广西的干旱/洪灾风险可能增加,而重庆的洪灾风险呈上升趋势。

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