Spatio-temporal Probability Behaviors of Maximum Consecutive Wet Days in Hexi Region

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Spatio-temporal Probability Behaviors of Maximum Consecutive Wet Days in Hexi Region

- Spatio-temporal Probability Behaviors of Maximum Consecutive Wet Days in Hexi Region
- Bulletin of Soiland Water Conservation Vol. 32, Issue 2, Pages: 43-48(2013)
- 作者机构：
  
  西北师范大学地理与环境科学学院,甘肃,兰州,730070
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- Published：2013
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LI Xiao-ya, ZHANG Bo. Spatio-temporal Probability Behaviors of Maximum Consecutive Wet Days in Hexi Region[J]. Bulletin of Soiland Water Conservation, 2013, 32(2): 43-48.
DOI：

LI Xiao-ya, ZHANG Bo. Spatio-temporal Probability Behaviors of Maximum Consecutive Wet Days in Hexi Region[J]. Bulletin of Soiland Water Conservation, 2013, 32(2): 43-48. DOI：

摘要

选取河西地区13个气象站点1960-2011年逐年日降水资料

采用线性趋势、反距离加权法、Mann-Kendall检验以及R/S分析法

选取4个极端降水指标

分析了河西地区极端降水事件的时空变化特征及未来变化趋势。结果表明

河西地区近52a最大1d降水量和最大2～3d连续降水量呈增加趋势

而最大4d连续降水量呈减少趋势

但变化都不显著。除最大4d连续降水量未来表现为持续性外

其它不同天数最大连续降水未来变化趋势与过去相反。最大1d降水量和最大2d连续降水量与降水总量有很好的相关性

可见最大1d和最大2d连续降水量对降水总量有很好的指示性。在空间分布上

不同天数最大连续降水表现出明显的空间差异

且不同区域的过去和未来变化趋势也不尽相同。研究还发现

在0.05的置信度下

河西地区不同天数最大连续降水发生了明显的突变现象

但突变年份不尽相同。

Abstract

Based on the daily precipitation data from 13meteorological stations in Hexi Region during 1960-2011

the methods of linear regression

inverse distance weighted

Mann-Kendall analysis and rescaledrange analysis were employed to analyze the spatial and temporal variability of precipitation extremes and predict its extremely precipitation variations in future.Four indices of extreme precipitation were studied.Theresults showed that over the 1960-2009period

the regionally averaged occurrence of annual maximum precipitations within 1dand 2～3dincreased whereas annual maximum precipitation of 4ddecreased.With theexception of annual maximum 4dprecipitation

the predicted trends of the other indices in future were opposite compared to the past.The annual maximum 1and 2dprecipitations correlated with annual total precipitation very well

which implies that annual maximum 1and 2dprecipitations are good indicators for annualtotal precipitation.The four indices differed substantially in spatial distribution with varying past and futuretendencies.In addition

abrupt changes in extreme precipitation indices could be readily identified at the 0.05confidence level

although they were not the same year.

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