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2022 , Vol. 45 >Issue 3: 706 - 714

DOI: https://doi.org/10.12118/j.issn.1000-6060.2021.341

气候变化

祁连山及周边降水分布聚类检验和典型流域增雨效果评价

  • 郭小芹 ,
  • 李光明 ,
  • 孙占峰 ,
  • 王兴涛
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  • 1.中国气象局云雾物理环境重点开放实验室,北京 100081
    2.武威市气象局,甘肃 武威 733000
郭小芹（1965-）,女,高级工程师,主要从事应用气象与人影应用研究. E-mail: gxq9179@126.com

收稿日期: 2021-07-30

  修回日期: 2021-11-14

  网络出版日期: 2022-05-31

基金资助

第二次青藏高原综合科学考察项目(2019QZKK0104);国家重点研发计划(2019YFC1510302);甘肃省气象局科研项目(Ms2022-21)

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Cluster analysis with statistical test of precipitation distribution in Qilian Mountains and its surrounding area and evaluation of artificial precipitation enhancement in typical watershed

  • Xiaoqin GUO ,
  • Guangming LI ,
  • Zhanfeng SUN ,
  • Xingtao WANG
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  • 1. Key Laboratory for Cloud Physical Environment of China Meteorological Administration, Beijing 100081, China
    2. Wuwei Meteorological Bureau, Wuwei 733000, Gansu, China

Received date: 2021-07-30

  Revised date: 2021-11-14

  Online published: 2022-05-31

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摘要

祁连山及周边区域地形复杂,降水分布极不均匀,如何科学地分区分型,对把握研究区域降水分布特征具有极为重要的意义。利用该区域31个国家基本站1961—2020年5—9月降水量资料,采用主成分分析方法（PCA）对该区域降水量进行分析,再通过聚类分析（CAST）对该结果进行显著性检验,最后将分区分型结果应用于人工增雨作业效果评估。结果表明：（1） 祁连山及周边可分成7个区域（Z1~Z7）,累积方差贡献率超过78%。（2） 这7个区域分别以乐都、海晏、野牛沟、武威、高台、临泽、刚察为中心点,划分结果与降水量、地理地形、海拔高度显著关联。（3） 依托区域历史回归统计方法对人工增雨作业效果进行评价,发现1992—2020年石羊河流域5—9月绝对增雨量、相对增雨率分别为8.91 mm、6.51%,其中7月最高（6.30 mm、21.86%）,8月次之（5.44 mm、16.11%）。基于地面降水量的作业效果评价往往受对比区选择的影响,聚类检验方法不仅有助于复杂地形下降水量的分区研究,还为科学选择对比区提供了客观依据。

关键词： 聚类检验; 主成分分析; 分区分型; 增雨效果评价

本文引用格式

郭小芹 , 李光明 , 孙占峰 , 王兴涛 . 祁连山及周边降水分布聚类检验和典型流域增雨效果评价[J]. 干旱区地理, 2022 , 45(3) : 706 -714 . DOI: 10.12118/j.issn.1000-6060.2021.341

Abstract

The topography of Qilian Mountains and its surrounding areas in northwest China is complex, and the precipitation it receives is extremely irregular in time and space. The ability to characterize the distribution of rainfall and snowfall has great practical significance for understanding changes in precipitation patterns. Using data from 31 base stations covering the months of May-September, 1961—2020, precipitation was analyzed by principal component analysis (PCA). The significance of the results was then tested by cluster analysis with statistical test (CAST). Finally, a geographic zonation was applied to evaluate the effects of artificial precipitation enhancement. The results show that: (1) Seven geographic areas (Z1-Z7) can satisfactorily represent the characteristics of precipitation distribution in the study area (the contribution rate of cumulative variance exceeds 78%). (2) The zones take Ledu, Haiyan, Yeniugou, Wuwei, Gaotai, Linze, and Gangcha stations as the central points respectively, and their zonal characteristics significantly reflect precipitation, terrain, and altitude. (3) Effects of artificial precipitation enhancement were evaluated by statistical regression of regional historical data. For the months of May-September during 1992—2020, the benefit was most pronounced in the Shiyang River Basin, where the absolute enhancement was 8.91 mm and the relative precipitation enhancement rate was 6.51% with the highest in July (6.30 mm, 21.86%), followed by August (5.44 mm, 16.11%). Assessing artificial enhancement of precipitation based on ground data relies heavily on the selection of a suitable comparison area, so results can change significantly with different comparison choices. The method of cluster analysis with statistical testing is not only helpful in zoning and classification of precipitation in complex terrain, but it also provides an objective basis for the selection of comparison areas.

Key words： cluster analysis with statistical test (CAST); principal component analysis (PCA); division and classification; evaluation of precipitation enhancement effects

参考文献

[1] 杨昭明, 张调风. 1961-2017年青藏高原东北部雨季降水量变化及其贡献度分析[J]. 干旱区研究, 2021, 38(1): 22-28.
[1] [ Yang Zhaoming, Zhang Tiaofeng. Analysis of precipitation change and its contribution in rainy season in northeast Qinghai Tibet Plateau from 1961 to 2017[J]. Arid Zone Research, 2021, 38(1): 22-28. ]
[2] 王春林, 司建华, 赵春彦, 等. 河西走廊近57年来干旱灾害特征时空演化分析[J]. 高原气象, 2019, 38(1): 196-205.
[2] [ Wang Chunlin, Si Jianhua, Zhao Chunyan, et al. Analysis of temporal and spatial evolution of characteristics of drought disaster in the Hexi Corridor in recent 57 years[J]. Plateau Meteorology, 2019, 38(1): 196-205. ]
[3] 陈乾, 陈添宇, 肖宏斌. 祁连山区夏季各类降水过程的典型个例分析[J]. 干旱气象, 2008, 26(3): 1-7.
[3] [ Chen Qian, Chen Tianyu, Xiao Hongbin. Typical cases study of classified precipitation process in summer over Qilian Mountains[J]. Arid Meteorology, 2008, 26(3): 1-7. ]
[4] 郭小芹, 罗永忠. 1961-2016年祁连山区季节性干旱综合指数特征分析[J]. 气象与环境学报, 2019, 35(1): 88-93.
[4] Guo Xiaoqin,Luo Yongzhong. Study on characteristics of seasonal drought composite index in Qilian Mountain area from 1961 to 2016
[4] [ J. Journal of Meteorology and Environment, 2019, 35(1): 88-93. ]
[5] 曾光平, 方仕珍, 肖锋. 1975-1986年古田水库人工降雨效果总分析[J]. 大气科学, 1991, 15(4): 97-108.
[5] [ Zeng Guangping, Fang Shizhen, Xiao Feng. The total analysis of the effect of artificial rainfall in Gutian reservoir area, Fujian (1975-1986)[J]. Chinese Journal of Atmospheric Sciences, 1991, 15(4): 97-108. ]
[6] 王婉, 姚展予. 2006 年北京市人工增雨作业效果统计分析[J]. 高原气象, 2009, 28(1): 195-202.
[6] [ Wang Wan, Yao Zhanyu. tatistical estimation of artificial precipitation enhancement effectiveness in Beijing in 2006[J]. Plateau Meteorology, 2009, 28(1): 195-202. ]
[7] 常倬林, 崔洋, 张武, 等. 基于CERES的宁夏空中云水资源特征及其增雨潜力研究[J]. 干旱区地理, 2015, 38(6): 1112-1120.
[7] [ Chang Zhuolin, Cui Yang, Zhang Wu, et al. Characteristics and developing potential of cloud water resource in Ningxia with the CERES data[J]. Arid Land Geography, 2015, 38(6): 1112-1120. ]
[8] 严采蘩, 陈万奎. 统计评价人工增雨效果的一些问题研究[J]. 应用气象学报, 2001, 12(增刊1): 80-86.
[8] [ Yan Caifan, Chen Wankui. Issues existed in the statistical assessment of artificial rainfall effect[J]. Journal of Applied Meteorology, 2001, 12(Suppl. 1): 80-86. ]
[9] 许焕斌. 关于在人工影响天气中更新学术观念的探讨[J]. 干旱气象, 2009, 27(4): 305-307.
[9] [ Xu Huanbin. On the ideal renew in weather modification[J]. Journal of Arid Meteorology, 2009, 27(4): 305-307. ]
[10] 孙倩倩, 刘晶淼. 基于聚类分析的中国东北地区气温和降水时空变化特征[J]. 气象与环境学报, 2014, 30(3): 59-65.
[10] [ Sun Qianqian, Liu Jingmiao. Temporal-spatial change of temperature and precipitation based on CAST in northeast China[J]. Journal of Meteorology and Environment, 2014, 30(3): 59-65. ]
[11] 韩微, 翟盘茂. 三种聚类分析方法在中国温度区划分中的应用研究[J]. 气候与环境研究, 2015, 20(1): 111-118.
[11] [ Han Wei, Zhai Panmao. Three cluster methods in regionalization of temperature zones in China[J]. Climatic and Environmental Research, 2015, 20(1): 111-118. ]
[12] 么枕生. 聚类统计检验用于气候分类[M]. 北京: 气象出版社, 1997: 85-94.
[12] [ Yao Zhensheng. Cluster statistical test for climate classification[M]. Beijing: Meteorological Press, 1997: 85-94. ]
[13] 邱美娟, 宋迎波, 王建林, 等. 新型统计检验聚类方法在精细化农业气象产量预报中的应用[J]. 中国农业气象, 2014, 35(2): 187-194.
[13] [ Qiu Meijuan, Song Yingbo, Wang Jianlin, et al. Application of newly developed cluster analysis of statistical test in fine agrometeorological yield prediction[J]. China Journal of Agrometeorology, 2014, 35(2): 187-194. ]
[14] 全占军, 李远, 李俊生, 等. 采煤矿区的生态脆弱性--以内蒙古锡林郭勒草原胜利煤田为例[J]. 应用生态学报, 2013, 24(6): 1729-1738.
[14] [ Quan Zhanjun, Li Yuan, Li Junsheng, et al. Ecological vulnerability of coal mining area: A case study of Shengli Coalfield in Xilinguole of Inner Mongolia, China[J]. Chinese Journal of Applied Ecology, 2013, 24(6): 1729-1738. ]
[15] 李湘阁, 胡凝. 实用气象统计方法[M]. 北京: 气象出版社, 2015: 11-28.
[15] [ Li Xiangge, Hu Ning. Practical meteorological statistical method[M]. Beijing: Meteorological Press, 2015: 11-28. ]
[16] 丁裕国, 张耀存, 刘吉峰. 一种新的气候分型区划方法[J]. 大气科学, 2007, 31(1): 129-136.
[16] [ Ding Yuguo, Zhang Yaocun, Liu Jifeng. A new method of climate classification and compartment using the conjunction between CAST and REOF[J]. Chinese Journal of Atmospheric Sciences, 2007, 31(1): 129-136. ]
[17] 刘吉峰, 李世杰, 丁裕国. 等. 一种用于中国年最高(低)气温区划的新的聚类方法[J]. 高原气象, 2005, 24(6): 966-973.
[17] [ Liu Jifeng, Li Shijie, Ding Yuguo, et al. A new cluster method applied to yearly highest and lowest air temperature region division in China[J]. Plateau Meteorology, 2005, 24(6): 966-973. ]
[18] 谢飞, 顾继光, 林彰文. 基于主成分分析和熵权的水库生态系统健康评价--以海南省万宁水库为例[J]. 应用生态学报. 2014, 25(6): 1773-1779.
[18] [ Xie Fei, Gu Jiguang, Lin Zhangwen. Assessment of aquatic ecosystem health based on principal component analysis with entropy weight: A case study of Wanning Reservoir[J]. Chinese Journal of Applied Ecology, 2014, 25(6): 1773-1779. ]
[19] 孙莉娟, 陈金华, 徐阳, 等. 基于多指数安徽省强降水灾害近45年的时空演变[J]. 水土保持研究, 2020, 27(3): 128-133.
[19] [ Sun Lijuan, Chen Jinhua, Xu Yang, et al. Spatial and temporal evolution of heavy rainfall disasters in Anhui Province in recent 45 years based on multi-indictors[J]. Research of Soil and Water Conservation, 2020, 27(3): 128-133. ]
[20] 韩群柱, 冯起, 高海东, 等. 基于主成分分析的关中地区农业粮食生产变化的影响因素研究[J]. 干旱区地理, 2020, 43(2): 474-480.
[20] [ Han Qunzhu, Feng Qi, Gao Haidong, et al. Influencing factors of agricultural production changes in Guanzhong based on PCA[J]. Arid Land Geography, 2020, 43(2): 474-480. ]
[21] 韩微, 翟盘茂. 三种聚类分析方法在中国温度区划分中的应用研究[J]. 气候与环境研究, 2015, 20(1): 111-118.
[21] [ Han Wei, Zhai Panmao. Three cluster methods in regionalization of temperature zones in China[J]. Climatic and Environmental Research, 2015, 20(1): 111-118. ]
[22] 冯克鹏, 田俊灿, 沈辉. 基于K-means聚类分区的西北地区近半个世纪气温变化特征分析[J]. 干旱区地理, 2019, 42(6): 1239-1252.
[22] [ Feng Kepeng, Tian Juncan, Shen Hui. Temperature variation characteristics of northwest China based on K-means clustering partition in the past half century[J]. Arid Land Geography, 2019, 42(6): 1239-1252. ]
[23] 雷月, 宫彦龙, 邓茹月, 等. 基于主成分分析和聚类分析综合评价蒸谷米的品质特性[J]. 食品工业科技, 2021, 42(7): 258-267.
[23] [ Lei Yue, Gong Yanlong, Deng Ruyue, et al. Comprehensive evaluation of quality characteristics of parboiled rice based on principal component analysis and cluster analysis[J]. Science and Technology of Food Industry, 2021, 42(7): 258-267. ]
[24] 邓北胜. 人工影响天气技术与管理[M]. 北京: 气象出版社, 2011: 140-147.
[24] [ Deng Beisheng. Technology and management of weather modification[M]. Beijing: China Meteorological Press, 2011: 140-147. ]
[25] 梁潇云, 刘屹岷, 吴国雄. 热带、 副热带海陆分布与青藏高原在亚洲夏季风形成中的作用[J]. 地球物理学报, 2006, 49(4): 983-992.
[25] [ Liang Xiaoyun, Liu Yimin, Wu Guoxiong. Roles of tropical and subtropical land-sea land distribution and the Qinghai-Xizang Plateau in the formation of the Asian summer monsoon, China[J]. Chinese Journal of Geophysics, 2006, 49(4): 983-992. ]
[26] 高荣, 韦志刚, 钟海玲. 青藏高原陆表特征与中国夏季降水的关系研究[J]. 冰川冻土, 2017, 39(4): 741-747.
[26] [ Gao Rong, Wei Zhigang, Zhong Hailing. Relationship between land surface characteristics in the Tibetan Plateau and summer precipitation in China[J]. Journal of Glaciology and Geocrylogy, 2017, 39(4): 741-747. ]
[27] 黄嘉佑. 气象统计分析与预报方法[M]. 第三版. 北京: 气象出版社, 2004.
[27] [ Huang Jiayou. Meteorological statistical analysis and forecasting methods[M]. 3rd ed. Beijing: Meteorological Press, 2004. ]
[28] 张敏静, 刘雅娜, 薛志群. 一元线性回归方程有关检验问题的研究[J]. 价值工程, 2012, 31(2): 1-2.
[28] [ Zhang Minjing, Liu Yana, Xue Zhiqun. Linear regression equation study of relevant inspection question[J]. Value Engineering, 2012, 31(2): 1-2. ]
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