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贵州省雷暴日数的时空分布、周期及突变特征
引用本文:丁旻.贵州省雷暴日数的时空分布、周期及突变特征[J].防灾技术高等专科学校学报,2013(4):36-42.
作者姓名:丁旻
作者单位:贵州省防雷减灾中心,贵州贵阳550002
基金项目:贵州省防雷业务集约化办公系统建设(黔科合SY字[2011]3113);贵州省雷电风险评估交互平台(黔气科合ZD[2010]02)
摘    要:利用1961—2011年贵州省87个台站地面雷暴观测资料,对该省境内雷暴日数的时空分布、周期和突变特征进行了分析。结果表明:贵州省雷暴日数年际变化较大,下降趋势显著;雷暴日数的时空分布形态不对称,92.16%正偏,峰度76.47%为正值,48a贵州区域内空间分布在0.05置信水平上服从正态分布。雷暴日数分布地域特征明显,从贵州西南部向东北方向呈梯状递减趋势,安顺市、六盘水市和黔西南州3个地区为雷暴高发区。贵州省逐年雷暴日数存在不太明显的18a左右的长周期以及4—5a和8—9a显著的周期变化。贵州省年雷暴日数的下降是一突变现象,具体是从1995年开始的,突变前后平均雷暴日数相差9.32d。

关 键 词:雷暴日数  时空分布  小波分析  M-K检验

The Temporal and Spatial Distribution,Cycle and Change Characteristics of the Thunderstorm Days in Guizhou
Ding.The Temporal and Spatial Distribution,Cycle and Change Characteristics of the Thunderstorm Days in Guizhou[J].Journal of College of Disaster Prevention Techniques,2013(4):36-42.
Authors:Ding
Institution:Ding Min ( Guizhou Lightning Protection Center, Guiyang, Guizhou 550002, China)
Abstract:By using the thunderstorm data of 87 stations in Guizhou province from 1961 to 2011, the temporal and spatial distribution, the cycle and the sudden change characteristics of the thunderstorm days in the province were analyzed. The results indicate that the number of the thunderstorm days which have a distinct annual variance decreased significantly. The skewness (kurtosis) coefficient of thunderstorm days among stations is positive for the 92. 16% (76.47%) years, 48a Guizhou regional spatial distribution obeys normal distribution at the 0. 05 confidence level. These show spatial and temporal distribution shape asymmetry of the number of the thunderstorm days. There are obvious geographical characteristics, with a decreasing trend from the southwest to northeast in Guizhou. Anshun, Liupanshui and Qianxinan are 3 regions of high-incidence area of thunderstorm. There are 18a and 4 - 5a and 8 - 9a significant periodic variations. Decline in the annual number of thunderstorm days is a change, particularly from the beginning of 1995, and the gap of average number of thunderstorm days is 9.32d.
Keywords:thunderstorm days  spatiotemporal distribution  wavelet analysis  M-K test
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