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暴雨灾害  2018, Vol. 37 Issue (02): 115-123    DOI: 10.3969/j.issn.1004-9045.2018.02.003
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四川雨季小时降水的概率分布特征及其降水分区
王彬雁1,赵琳娜2,许晖3,刘莹1
1. 四川省气象台 高原与盆地暴雨旱涝灾害四川省重点实验室,成都 610072;2. 中国气象科学研究院,北京 100081;
3. 广东省中山市气象局,中山 528400
Probability distribution and partition of hourly rainfall during the rainy season over Sichuan Province
WANG Binyan1,ZHAO Linna2,XU Hui3,LIU Ying1
1. Sichuan Meteorological Observatory, Heavy rain and Drought-Flood Disaster in Plateau and Basin key laboratory of Sichuan Province,
Chengdu
610072; 2. Chinese Academy of Meteorological Sciences, Beijing 100081; 3.
Zhongshan Meteorological
office of Guangdong Province, Zhongshan
528400
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摘要 利用2010—2016年5—9月四川省157个国家自动气象站小时降水资料,采用皮尔逊Ⅲ型概率分布模型对四川全省小时降水进行拟合,给出全省超过不同阈值的降水累积概率空间分布;在此基础上,计算最大小时降水量的概率分布及其重现期极值。结果表明:四川盆地西部沿山一带出现降水频次较少,但易发生较大量级的小时降水,攀西地区东部虽是降水高发区,但出现大量级小时降水的可能性小;50 a一遇小时降水高值中心分布在乐山市北部、遂宁市西北部与绵阳交界处以及达州市北部,其极值可达60 mm以上;100 a一遇小时降水极值分布趋势同50 a一遇的基本一致,其极值达70 mm;小时降水的皮尔逊Ⅲ型概率分布模型偏差系数与降水站点的海拔高度呈对数递减关系,决定系数达0.654 5,表明地形高度对四川小时降水分布有一定影响;此外用 k均值聚类法可很好地对四川小时降水进行分区。
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王彬雁
赵琳娜
许晖
刘莹
关键词概率分布;   小时降水;   皮尔逊Ⅲ型;   重现期;   四川盆地     
Abstract: Using the hourly rain gauge data from 157 national automatic weather stations (AWS) over Sichuan province between May and September from 2010 to 2016, by applying the Pearson-Ⅲ distribution function, we have conducted a fitting of the hourly rainfall in Sichuan to find out the spatial probability distribution that exceeds different thresholds. Based on the results, we calculated the probability distribution pattern and their extreme values under different return period scenarios of hourly rainfall. The results indicate that rainfall with low frequency but with high grade of hourly rainfall occurs the most often along mountains in the western Sichuan Basin. The rainfall that occurs frequently but with the high grade of hourly rainfall seldom happens in the east part of Panxi region. High value areas of hourly rainfall within a recurrence period of 50 years are located in the northern part of Leshan, in the junction between northwestern Suining and Mianyang, and in the northern part of Dazhou, whose the maximum value can be over 60 mm. The extreme hourly rainfall within a recurrence period of 100 years is up to 70 mm, with a distribution similar to that with a recurrence period of 50 years. The deviation coefficient (Cv) of the Pearson-Ⅲ distribution function to hourly rainfall has a logarithmic decreasing correlation with the altitude of AWSs, the statistic coefficient (R2) between them being up to 0.6545, indicating that terrain has an effect to the hourly rainfall patterns significantly. In addition, the k-means clustering method can be used to group hourly rainfall over Sichuan province.
Key wordsprobability distribution;   hourly rainfall;   Pearson-Ⅲ distribution function;   return period;   Sichuan Basin   
引用本文:   
王彬雁, 赵琳娜, 许晖,等 .2018. 四川雨季小时降水的概率分布特征及其降水分区[J]. 暴雨灾害, 37(02): 115-123.
WANG Bin-Yan, ZHAO Lin-Na, XU Hui, et al .2018. Probability distribution and partition of hourly rainfall during the rainy season over Sichuan Province[J]. Torrential Rain and Disasters, 37(02): 115-123.
 
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