REN Zhihan,NI Xue,NI Changjian,et al.Study on the Probabilistic Characteristics of Heavy Precipitation of Chengdu Economic Zone based on Poisson Distribution[J].Journal of Chengdu University of Information Technology,2021,36(01):80-85.[doi:10.16836/j.cnki.jcuit.2021.01.013]
基于泊松分布的成都经济区暴雨概率特征研究
- Title:
- Study on the Probabilistic Characteristics of Heavy Precipitation of Chengdu Economic Zone based on Poisson Distribution
- 文章编号:
- 2096-1618(2021)01-0080-06
- Keywords:
- atmospheric science; heavy precipitation; Chengdu economic zone; Poisson distribution; probabilistic characteristics
- 分类号:
- P426.61
- 文献标志码:
- A
- 摘要:
- 为得到成都经济区暴雨频次概率特征,利用成都经济区个测站(成都、德阳、绵阳、眉山和资阳)1960-2018年逐日降水数据,统计出各站年暴雨频次,结合Poisson分布函数,得到年暴雨频次分布模型。将理论和实测数据进行对比,验证了年暴雨频次分布模型的有效性,个测站暴雨概率的分布均符合Poisson分布模型。研究结果表明,成都和眉山每年出现3次暴雨的概率最大,德阳、绵阳和资阳每年出现2次暴雨的概率最大; 成都、绵阳、眉山和资阳暴雨频次在时间上总体呈减少趋势,德阳暴雨频次呈略微增加趋势; 位于区内中部的成都暴雨频次最大,危险性相对最高,位于东南部的眉山、资阳次之,暴雨危险性相对较弱,位于北部的德阳、绵阳最小,暴雨危险性相对最低。
- Abstract:
- In order to draw the probabilistic characteristics of heavy rain in Chenngdu economic areas, we use the daily precipitation data of Chengdu Economic Zone which are Chengdu, Deyang, Mianyang, Meishan and Ziyang respectively from 1960 to 2018 to count the annual heavy rain frequency. These are Combined with the Poisson distribution function to get the distribution model of annual heavy precipitation. The comparison of theoretical value and measured value shows the availability of the distribution model of the distribution of frequency of heavy precipitation. The distribution of heavy rain in the five stations is consist with the Poisson distribution model. The results shows that Chengdu and Meishan have the highest probability of three times heavy precipitation per year, Deyang, Mianyang and Ziyang have the highest probability of twice heavy precipitation per year among the five stations; The frequency of heavy precipitation in Chengdu, Mianyang, Meishan and Ziyang generally decreased in time, and the frequency of that in Deyang changed slightly; Chengdu, located in the middle of the region, has the highest rainstorm frequency and the highest rainstorm risk, followed by Meishan and Ziyang in the southeast, which have a relatively weak rainstorm risk, Mianyang and Deyang, located in the north, has the lowest rainstorm risk.
参考文献/References:
[1] 徐菲菲,孙良鑫,汪梦瑶,等.基于小波分析的宿州地区暴雨时空分布特征[J].气象科学,2018,38(4):559-564.
[2] 陈朝基.中国1951～2000年特大暴雨气候特征[J].安徽农业科学,2011,39(03):1605-1606.
[3] 周鹏康,秦金梅.云南1981～2010 年雨季暴雨时空分布特征[J].云南地理环境研究,2016,28(4):63-69.
[4] 黄鹤,杨超,于雷,等.1958-2012年河北省汛期暴雨气候变化特征分析[J].气象科学,2015,31(2).
[5] 郑逢春,石燕清,张丹丹,等.近52年湘西自治州暴雨时空分布特征分析[J].安徽农业科学,2016,44(31):181-184.
[6] 谢晓丽,王洪丽,刘晓梅.呼伦贝尔市暴雨时空分布特征及类型分析[J].内蒙古农业科技,2012(4):97-99.
[7] 李玲萍,陈雷,罗小玲,等.河西走廊东部大到暴雨特征分析[J].资源科学,2013,35(6):1277-1284.
[8] 朱艳飞,哈建强.1972-2007年河北沧州大暴雨变化趋势分析[J].黄河水利职业技术学院学报,2016,28(1):21-23.
[9] 丁一汇.陶诗言先生与中国暴雨[C].东亚季风和中国暴雨——庆贺陶诗言先生八十华诞集,1998:137-141.
[10] 康桂红,韩永清,孙兴池,等.近30a山东首场暴雨的气候特征及环流形势[J].干旱气象,2015,33(6):955-962.
[11] 黄骏凯,刘丽琴,苗蓓蓓,等.黄山市两次暴雨天气过程分析[J].南方农业,2016,10(32):87-88.
[12] 于新文,丁裕国.中国东部地区暴雨的概率特征―基于泊松分布的统计模拟[J].自然灾害学报,2006,15(4):13-18.
[13] 彭丽英,苏小山,李英,等.茂名市暴雨的气候特征[J].广东气象,2018,40(2):1-5.
[14] 王佳津,陈朝平,刘莹,等.四川省持续性暴雨定义及时空分布特征[J].气象科技,2017,(2):331-341.
[15] Thomas R.Karl,Richard W.Knight.Secular trends of precipitation amount,frequency,and intensity in the United States[J].Bulletin of the American Meteorological
society,1998,79(2):231-242.
[16] Groisman P Y,Knight R W,Karl T R.Heavy precipitation and high streamflow in the contiguous United States:Trends in the twentieth century[J].Bulletin of the American Meteorological Society,2001,82(2):219-246.
[17] Alexander L,Zhang X,Peterson T.Global observed changes in daily climate extremes of temperature and precipitation[J].Geophys Res Lett,2006,111.
[18] Park J S,Jung H S.Modelling Korean extreme rainfall using a Kappa distribution and maximum likelihood estimate[J].Theoretical and Applied climatology,2002,72(1/2):55-64.
[19] 周浩澜,陈洋波,徐会军.基于GEV分布模型参数与历时关系的暴雨强度公式推求[J].四川大学学报(工程科学版),2012,44(S1):37-41.
[20] 吕忠东,邹阳,李一波.基于泊松分布的川东暴雨概率特征分析[J].成都信息工程学院学报,2010,25(5):531-535.
[21] 周其龙,梁洪运,刘敏,等.基于概率分布模型的暴雨研究[J].科技资讯,2013(9):1-3.
[22] 任照环,倪长健.基于复合极值模型的暴雨重现期研究——以川东北地区为例[J].西南师范大学学报(自然科学版),2014,39(5):131-137.
[23] Korolev V Y,Gorshenin A.The probability distribution of extreme precipitation[C].Doklady Earth Sciences,2017:1461-1466.
[24] 范擎宇,何福红,马国斌,等.基于过程降雨的暴雨灾害危险性评估——以松花江流域为例[J].地理与地理信息科学,2016,32(2):100-104.
[25] 丁裕国,申红艳,江志红,等.气候概率分布理论及其应用新进展[J].气象科技,2009,37(3):257-262.
[26] 邵远坤,沈桐立,游泳,等.四川盆地近40年来的降水特征分析[J].西南农业大学学报,2005,27(6):749-752.
[27] 彭丽,胡林龙.成都经济区环保产业发展趋势分析[J].中国环保产业,2015,(7):67-69.
[28] 周路.成都经济区先进制造业与现代物流业融合发展的研究[J].经济研究导刊,2018(18):44-47.
[29] 傅军和.二项分布和泊松分布的剖析[J].统计教育,2006(10):10-11.
相似文献/References:
[1]梁家豪,陈科艺,李 毓.WRF模式中积云对流参数化方案对南海土台风“Ryan”模拟的影响研究[J].成都信息工程大学学报,2019,(02):162.[doi:10.16836/j.cnki.jcuit.2019.02.010]
LIANG Jiahao,CHEN Keyi,LI Yu.The Impact of Different Cumulus Parameterization Schemes of the WRF
Model on the Typhoon “Ryan” Simulation over the South China Sea[J].Journal of Chengdu University of Information Technology,2019,(01):162.[doi:10.16836/j.cnki.jcuit.2019.02.010]
[2]廖 琦,肖天贵,金荣花.东亚副热带西风急流年际变化特征分析[J].成都信息工程大学学报,2018,(01):68.[doi:10.16836/j.cnki.jcuit.2018.01.013]
LIAO Qi,XIAO Tian-Gui,JIN Rong Hua.Analysis on Inter-annual Variation of EastAsian Subtropical Westerly Jet[J].Journal of Chengdu University of Information Technology,2018,(01):68.[doi:10.16836/j.cnki.jcuit.2018.01.013]
[3]高清泉,韩瑽琤,肖天贵.微波通信链路监测降水试验及可行性探究[J].成都信息工程大学学报,2018,(02):197.[doi:10.16836/j.cnki.jcuit.2018.02.015]
GAO Qing-quan,HAN Cong-cheng,XIAO Tian-gui.Feasibility Study of Microwave CommunicationLink for Rainfall Monitoring Purposes[J].Journal of Chengdu University of Information Technology,2018,(01):197.[doi:10.16836/j.cnki.jcuit.2018.02.015]
[4]黄 瑶,肖天贵,刘思齐.2016年7月四川持续性强降水的中尺度滤波分析[J].成都信息工程大学学报,2018,(03):307.[doi:10.16836/j.cnki.jcuit.2018.03.014]
HUANG Yao,XIAO Tian-gui,LIU Si-qi.Mesoscale Filtering Analysis of Persistent Heavy Rainfall in Sichuan in July 2016[J].Journal of Chengdu University of Information Technology,2018,(01):307.[doi:10.16836/j.cnki.jcuit.2018.03.014]
[5]李雅婷,苏德斌,孙晓光,等.四川盆地风廓线雷达大气折射率结构常数特征分析[J].成都信息工程大学学报,2018,(04):375.[doi:10.16836/j.cnki.jcuit.2018.04.005]
LI Ya-ting,SU De-bin,SUN Xiao-guang,et al.Characteristic Analysis of Atmospheric Structure Constant of Refractive Index of
Sichuan Basin based on Wind Profiler Radar[J].Journal of Chengdu University of Information Technology,2018,(01):375.[doi:10.16836/j.cnki.jcuit.2018.04.005]
[6]石 宇,肖子牛,朱克云.夏季角动量输送变化与中国东部降水的关系[J].成都信息工程大学学报,2018,(04):456.[doi:10.16836/j.cnki.jcuit.2018.04.016]
SHI Yu,XIAO Zi-niu,ZHU Ke-yun.Relationship between Angular Momentum Transportand Precipitation in Eastern China in Summer[J].Journal of Chengdu University of Information Technology,2018,(01):456.[doi:10.16836/j.cnki.jcuit.2018.04.016]
[7]于佳含,巩远发,毛文书.2017年7月吉林永吉两次极端强降水过程的对比分析[J].成都信息工程大学学报,2019,(03):287.[doi:10.16836/j.cnki.jcuit.2019.03.014]
YU Jiahan,GONG Yuanfa,MAO Wenshu.Comparative Analysis on Two Extreme Severe Precipitation Events in Yongji County, Jilin Province in July 2017[J].Journal of Chengdu University of Information Technology,2019,(01):287.[doi:10.16836/j.cnki.jcuit.2019.03.014]
[8]宾 昕,程志刚,王俊锋,等.近17a秦巴山区NDVI季节变化差异及其海拔依赖性特征分析[J].成都信息工程大学学报,2019,(03):302.[doi:10.16836/j.cnki.jcuit.2019.03.016]
BIN Xin,CHENG Zhigang,WANG Junfeng,et al.Seasonal Variation of NDVI and Altitude Dependent Characteristics in Qinling-Daba Mountains in Recent 17 Years[J].Journal of Chengdu University of Information Technology,2019,(01):302.[doi:10.16836/j.cnki.jcuit.2019.03.016]
[9]金凡琦,程志刚,靳立亚,等.成渝城市群热环境效应与植被覆盖度关系研究[J].成都信息工程大学学报,2019,(03):308.[doi:10.16836/j.cnki.jcuit.2019.03.017]
JIN Fanqi,CHENG Zhigang,JIN Liya,et al.Study on the Relationship between Thermal Environment Effect and Vegetation Coverage in Chengyu Urban Agglomeration[J].Journal of Chengdu University of Information Technology,2019,(01):308.[doi:10.16836/j.cnki.jcuit.2019.03.017]
[10]吴珍珍,刘海文,潘丽丽.2011年8月4-5日四川盆地双核西南低涡
及其带来的降水天气分析[J].成都信息工程大学学报,2018,(06):681.[doi:10.16836/j.cnki.jcuit.2018.06.014]
WU Zhen-zhen,LIU Hai-wen,PAN Li-li.Analysis of a Binary Southwest Vortex and its Precipitation
over the Sichuan Basin on 4-5 August 2011[J].Journal of Chengdu University of Information Technology,2018,(01):681.[doi:10.16836/j.cnki.jcuit.2018.06.014]
[11]蔺邹兴,华 维,范广洲,等.一次东移型西南低涡引发的强降水诊断分析[J].成都信息工程大学学报,2019,(04):384.[doi:10.16836/j.cnki.jcuit.2019.04.011]
LIN Zouxing,HUA Wei,FAN Guangzhou,et al.A Diagnostic Analysis of the Heavy Precipitation
Caused by Eastward Shift of Southwest Vortex[J].Journal of Chengdu University of Information Technology,2019,(01):384.[doi:10.16836/j.cnki.jcuit.2019.04.011]
[12]赵胜男,王 磊,李谢辉,等.一次南京特大暴雨的数值模拟及Q矢量诊断[J].成都信息工程大学学报,2020,35(06):678.[doi:10.16836/j.cnki.jcuit.2020.06.015]
ZHAO Shengnan,WANG Lei,LI Xiehui,et al.Numerical Simulation of a Heavy Rain in Nanjing[J].Journal of Chengdu University of Information Technology,2020,35(01):678.[doi:10.16836/j.cnki.jcuit.2020.06.015]
[13]邹德全,邹承立,宋鑫民,等.基于泊松分布的遵义市暴雨、大暴雨次数概率特征[J].成都信息工程大学学报,2022,37(06):716.[doi:10.16836/j.cnki.jcuit.2022.06.015]
ZOU Dequan,ZOU Chengli,SONG Xinmin,et al.Characteristics of the Number of Times and Probability of Rainstorm and Torrential Rain in Zunyi based on Poisson Distribution[J].Journal of Chengdu University of Information Technology,2022,37(01):716.[doi:10.16836/j.cnki.jcuit.2022.06.015]
备注/Memo
收稿日期:2019-12-16
基金项目:国家重点研发计划资助项目(2018YFC0214004、2018YF C1506006); 四川省科技厅重点研发资助项目(2018SZ0287)