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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。
Abstract：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.
[1] IPCC AR5.Intergovernmental panel on climate change 2013 fifth assessment report (AR5) [R].London:Cambridge University Press,2013.
[2] IPCC SREX.Managing the risks of extreme events and disasters to advance climate change adaptation[R].London:Cambridge University Press,2012.
[3] IPCC SR1.5.Global warming of 1.5℃:An IPCC special report on the impacts of global warming of 1.5℃ above pre-industrial levels and related global greenhouse gas emission pathways,in the context of strengthening the global response to the threat of climate change,sustainable development,and efforts to eradicate poverty [R].London:Cambridge University Press,2018.
[4] DONAT M G,LOWRY A L,ALEXANDER L V,et al.More extreme precipitation in the world's dry and wet regions[J].Nature Climate Change,2016,6(5):508- 513.
[5] TIAN F,ZHENG Y,TAO Z,et al.Statistical characteristics of environmental parameters for warm season short-duration heavy rainfall over central and eastern China[J].Journal of Meteorological Research,2015,29(3):370- 384.
[6] JIANG X.Interannual variation of mid-summer heavy rainfall in the eastern edge of the Tibetan Plateau[J].Climate Dynamics,2015,45(11- 12):3091- 3102.
[7] WEI L,HU K H,HU X D.Rainfall occurrence and its relation to flood damage in China from 2000 to 2015[J].Journal of Mountain Science,2018,15(11):161- 173.
[8] ZHANG W,VILLARINI G.Heavy precipitation is highly sensitive to the magnitude of future warming[J].Climatic Change,2017,145(1):249- 257.
[9] DONAT M G,PETERSON T C,BRUNET M,et al.Changes in extreme temperature and precipitation in the Arab region:Long-term trends and variability related to ENSO and NAO[J].International Journal of Climatology,2014,34(3):581- 592.
[10] FUNK C,PETERSON P,LANDSFELD M,et al.The climate hazards infrared precipitation with stations:A new environmental record for monitoring extremes.[J].Scientific Data,2015,2(1):150066- 150066.
[11] SIPPEL S,ZSCHEISCHLER J,HEIMANN M,et al.Quantifying changes in climate variability and extremes:Pitfalls and their overcoming[J].Geophysical Research Letters,2015,42(22):9990- 9998.
[12] PIELKE R A,PITMAN A J,NIYOGI D,et al.Land use/land cover changes and climate:Modeling analysis and observational evidence[J].Wiley Interdisciplinary Reviews:Climate Change,2011,2(6):828- 850.
[13] LUONG T M,CASTRO C L,CHANG H,et al.The more extreme nature of North American Monsoon precipitation in the Southwestern United States as revealed by a historical climatology of simulated severe weather events[J].Journal of Applied Meteorology and Climatology,2017,56(9):2509- 2529.
[14] LIU R,LIU S C,CICERONE R J,et al.Trends of extreme precipitation in eastern China and their possible causes[J].Advances in Atmospheric Sciences,2015,32(8):1027- 1037.
[15] RAGULINA G,REITAN T.Generalized extreme value shape parameter and its nature for extreme precipitation using long time series and the Bayesian approach[J].Hydrological Sciences Journal-Journal Des Sciences Hydrologiques,2017,62(6):863- 879.
[16] ZHENG Y,CHEN J,TAO Z,et al.Distribution characteristics of the intensity and extreme intensity of tropical cyclones influencing China[J].Journal of Meteorological Research,2014,28(3):393- 406.
[17] CHEN H,SUN J.Changes in climate extreme events in China associated with warming[J].International Journal of Climatology,2015,35(10):2735- 2751.
[18] WANG D,JIANG P,WANG G,et al.Urban extent enhances extreme precipitation over the Pearl River Delta,China[J].Atmospheric Science Letters,2015,16(3):310- 317.
[19] 张亚宁,张明军,王圣杰,等.1961—2015年中国降水面积变化特征研究[J].干旱区地理,2019,42(4):762- 773.
[20] 贺冰蕊,翟盘茂.中国1961—2016年夏季持续和非持续性极端降水的变化特征[J].气候变化研究进展,2018,14(5):437- 444.
[21] 李鑫鑫,桑燕芳,谢平,等.我国不同历时年最大降雨量的随机性及空间差异性[J].地球信息科学学报,2018,20(8):1094- 1101.
[22] 马丁.雄安新区暴雨特性分析[J].河北水利,2019(5):44- 45.
[23] 车蕊,林澍,范中亚,等.连续极端降雨对东江流域水质影响分析[J].环境科学,2019,40(10):4440- 4449.
[24] 芦鑫,殷淑燕,高涛涛.1960—2017年秦岭南北地区降雨侵蚀力的时空变化特征研究[J].浙江大学学报(理学版),2019,46(3):380- 390.
[25] 何泽仕,郑巧雅,徐曹越,等.1960—2013年福建省台风暴雨时空特征研究[J].人民珠江,2019,40(3):1- 8+18.
[26] 李艳,马百胜,杨宣.两类ENSO事件对中国东部地区极端降水的影响[J].长江流域资源与环境,2019,28(2):469- 482.
[27] 孔锋,孙劭,王一飞,等.近56 a来中国东部地区雨涝事件时空演变特征[J].长江流域资源与环境,2018,27(7):1554- 1564.
[28] 谭畅,孔锋,郭君,等.1961—2014年中国不同城市化地区暴雨时空格局变化:以京津冀、长三角和珠三角地区为例[J].灾害学,2018,33(3):132- 140.
[29] 李伟.中国区域极端降水变化的人为信号检测及其未来预估[D].南京:南京信息工程大学,2018.
[30] 李慧,周顺武,陆尔,等.1961—2010年中国华南地区夏季降水结构变化分析[J].气候变化研究进展,2018,14(3):247- 256.
[31] 孔锋,史培军,吕丽莉,等.全球陆地暴雨时空格局变化的自然和人文影响因素研究(1981—2010年)[J].北京师范大学学报(自然科学版),2018,54(2):208- 216.
[32] 王雨枭,游庆龙,谢星旸.1961—2014年中国东部地区夏季极端降水事件时空变化特征[J].气象科技,2018,46(2):299- 306.
[33] 杨子凡.全球旱地1948—2008年温度和降水的变化特征[D].兰州:兰州大学,2018.
[34] 尹占娥,田鹏飞,迟潇潇.基于情景的1951—2011年中国极端降水风险评估[J].地理学报,2018,73(3):405- 413.
[35] 孔锋,方建,吕丽莉.1961—2015年中国暴雨变化诊断及其与多种气候因子的关联性研究[J].热带气象学报,2018,34(1):34- 47.
[36] 余锦华,祁淼,孙齐颖,等.中国东部夏季极端降水统计特征及其与El Nino的联系[J].大气科学学报,2018,41(1):77- 84.
[37] 刘海涛,杨洁.1951—2015年北京极端降水变化研究[J].中国农学通报,2018,34(1):109- 117.
[38] 孙军,张福青.中国日极端降水和趋势[J].中国科学:地球科学,2017,47(12):1469- 1482.
[39] 孔锋,王一飞,吕丽莉,等.中国累积暴雨与自然和人文因素的关联性分析[J].现代农业科技,2017(23):137- 142.
[40] 王佳雯,廖威林,王大刚,等.中国大陆地区极端降水与温度的相关性[J].中山大学学报(自然科学版),2017,56(6):22- 30.
[41] 孔锋,吕丽莉,方建,等.中国不同强度暴雨年代际时空演变特征(1951—2010)[J].首都师范大学学报(自然科学版),2017,38(5):75- 85.
[42] 顾西辉,张强,孔冬冬,等.中国年和季节极端降水时空特征及极值分布函数上尾部性质[J].地理科学,2017,37(6):929- 937.
[43] 史培军,孙劭,汪明,等.中国气候变化区划(1961—2010年)[J].中国科学:地球科学,2014,44(10):2294- 2306.
[44] 吴绍洪,潘韬,刘燕华,等.中国综合气候变化风险区划[J].地理学报,2017,72(1):3- 17.
[45] 张昕怡,方国华,闻昕,等.中国格点化日降水极值统计模型及阈值的选取[J].气候变化研究进展,2017,13(4):346- 355.
[46] 武文博.中国东部夏季极端降水事件及可能原因分析[D].南京:南京信息工程大学,2017.
[47] 孔锋,吕丽莉,方建.1991—2010年中国小时暴雨时空变化格局及其与城镇化因子的空间相关分析[J].气候与环境研究,2017,22(3):355- 364.
[48] 孔锋,史培军,方建,等.全球变化背景下极端降水时空格局变化及其影响因素研究进展和展望[J].灾害学,2017,32(2):165- 174.
[49] 孔锋,吕丽莉,方建,等.基于日值和小时降水数据诊断中国暴雨时空变化差异的研究(1991—2010)[J].灾害学,2017,32(1):72- 79.
[50] 孔锋,方建,吕丽莉,等.中国长短历时暴雨时空变化格局及其对总暴雨贡献的研究(1951—2010)[J].中国人口·资源与环境,2016,26(S2):316- 320.
[51] 陈金明,陆桂华,吴志勇,等.1960—2009年中国夏季极端降水事件与气温的变化及其环流特征[J].高原气象,2016,35(3):675- 684.
[52] 祁淼.中国东部夏季极端降水统计特征及其与大尺度气候变化的关系[D].南京:南京信息工程大学,2016.
[53] 顾西辉,张强,孔冬冬.中国极端降水事件时空特征及其对夏季温度响应[J].地理学报,2016,71(5):718- 730.
[54] 吴梦雯.中国极端降水的统计分析和个例研究[D].北京:中国气象科学研究院,2016.
[55] 姜贵祥.形成我国东部持续性极端强降水的次季节变率特征[D].南京:南京大学,2016.
[56] 孔锋,王铸,刘凡,等.全球、大洲、区域尺度暴雨时空格局变化(1981—2010年)[J].北京师范大学学报(自然科学版),2016,52(2):228- 234.
基本信息:
DOI：10.13928/j.cnki.wrahe.2020.02.002
中图分类号:P426.6
引用信息:
[1]孔锋.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)[J],2020,51(02):26-37.DOI:10.13928/j.cnki.wrahe.2020.02.002.
基金信息:
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)