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中国不同月份暴雨的多属性时空演变特征及区域差异(1961—2016年) 被引量:7

Multi-attribute spatio-temporal evolution characteristics and regional differences of heavy rainfall in different months in China from 1961 to 2016
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摘要 为了诊断变暖背景下中国不同月份暴雨多属性时空差异特征,采用1961—2016年中国545个气象站点的日值降水数据,利用线性回归、变异系数和图谱对比分析等方法,从气候态特征、变化趋势和年际变异3个方面诊断了中国不同月份的暴雨雨量和雨日的时空变化特征。结果表明:(1)1961—2016年中国不同月份的暴雨雨量与暴雨雨日在对应月份具有相似的空间分异特征。暴雨雨量和暴雨雨日的高值区1—7月份逐渐从东南沿海向西北内陆扩张,但主要分布在胡焕庸线以东地区;8—12月份则从西北地区向东南沿海地区缩减;胡焕庸线以西地区的暴雨雨量和暴雨雨日在不同月份分布较少。(2)1961—2016年中国不同月份的暴雨雨量与暴雨雨日的变化趋势时空分异特征基本一致。5—8月份是中国暴雨雨量和暴雨雨日变化趋势最显著的月份,主要分布在东南季风区,且以增加趋势为主;西北地区的暴雨雨量和暴雨雨日的趋势则在不同月份变化较小。(3)1961—2016年中国不同月份的暴雨雨量与暴雨雨日的年际变异特征相似。其中北方地区在4—10月份波动特征较大;南方地区则在1—3月份、11—12月份波动较大。暴雨雨量和暴雨雨日波动较大的高值区随月份发展逐渐从东南向西北、东北和西南地区扩张,且东南地区的波动趋于减小,随后再从西北、东北和西南地区向东南地区缩减,同时伴随东南地区波动增大。研究对于防洪减灾和水资源规划与利用具有一定的参考意义。 In order to diagnose the multi-attribute spatio-temporal differential characteristics of heavy rainfall under the background of climate warming in different months in China, the daily precipitation data from 1961 to 2016 observed from 545 meteorological stations in China are adopted for diagnosing the spatio-temporal variation characteristics of the heavy rainfall amounts and heavy rainfall days in different months in China with the methods of linear regression, coefficient of variation and spectral comparative analysis from the three aspects, i.e. climatologic characteristics, variation trend and inter-annual variability. The results show that(1) The heavy rainfall amounts in different months from 1961 to 2016 in China have similar spatial differentiation characteristics in the corresponding months. The areas with high value of heavy rainfall amounts and heavy rainfall days gradually are expanded from the southeast coast to the northwest inland from January to July in China, but are mainly distributed in the eastern area of Hu Huanyong Line and are reduced from the northwest China to southeast China from August to December, while the heavy rainfall amounts and heavy rainfall days in the western area of Hu Huanyong Line are less distributed in different months.(2) The spatio-temporal differential characteristics of the variation trends of heavy rainfall amounts and heavy rainfall days in different months from 1961 to 2016 in China are basically the same. May to August are the most significant months for the variation trends of heavy rainfall amounts and heavy rainfall days in China, which are mainly distributed in the southeastern monsoon area in China with the main trends of increase. The trends of heavy rainfall amounts and heavy rainfall days in the northwest China are slightly varied in different months.(3) The inter-annual differential characteristics of heavy rainfall amounts in different months from 1961 to 2016 in China are similar to those of heavy rainfall days, among which the fluctuated characteristics from April to October in the northern region are larger;while the fluctuations are larger from January to March and from November to December in the Southeast China. The areas with high value of heavy rainfall amounts and heavy rainfall days are gradually expanded along with the change of months from the southeast China to the northwest China, and then the fluctuations in the southeast China tend to be decreased and are reduced again from the northwest China, the northeast China and the southwest China to the southeast China with the fluctuations in the southeast China afterwards. The study has a certain referential significance for flood control and disaster mitigation as well as water resources planning and utilization.
作者 孔锋 KONG Feng(School of Public Policy and Management,Tsinghua University,Beijing 100084,China;Center for Crisis Management Research,Tsinghua University,Beijing 100084,China;Training Center,China Meteorological Administration,Beijing 100081,China)
出处 《水利水电技术》 北大核心 2020年第2期26-37,共12页 Water Resources and Hydropower Engineering
基金 国家自然科学基金(41801064,41605079,71790611) 北京市社科基金研究基地项目(19JDGLA008) 中国博士后科学基金资助(2019T120114,2019M650756) 中亚大气科学研究基金(CAAS201804).
关键词 暴雨 月际差异 空间格局 变化趋势 波动特征 气候变化 中国 heavy rainfall inter-monthly difference spatial pattern variation trend fluctuation characteristics climate change China
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