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【目的】为分析全球变暖背景下中国大陆历史和未来不同排放情景下极端降水事件的变化特征,研究我国不同地区极端降水事件频率和强度的变化规律。【方法】选取日尺度历史降水数据(1979—2021年)和CMIP6未来情景模式降水数据(2015—2100年),使用Mann-Kendall检验等方法,分析历史和未来低(SSP1-2.6)、中低(SSP2-4.5)、中高(SSP3-7.0)和高(SSP5-8.5)排放情景下极端降水的时空变化趋势。【结果】结果表明:1979—2021年,我国各区域极端降水指数呈现东高西低的空间格局,连续干旱日数(CDD)、雨日日数(RD)在全国范围内呈下降趋势,其他极端降水量指数(如最大1 d降水量Rx1day)和日数指数(如大雨日数R25)等均为上升趋势,其中华东、华南和西南地区趋势最显著。未来不同时期,极端降水日、量数指数在不同经济路径下变化趋势亦有差异,2045—2075年上升面积占比增幅最大;华东地区在SSP3-7.0路径下极端降水量上升幅度最大,华南地区在SSP2-4.5路径下极端降水日指数上升面积最小,华北、西北和东北地区极端降水量指数随排放升高规律变化,西南地区受排放升高影响极端降水量指数上升面积占比最高。【结论】历史数据表明,我国极端降水事件频率与降水强度有增加趋势。未来情景模式4种经济路径下,全国范围内极端降水强度增加的面积占比有不同程度增加,本世纪后期(2060—2100年)面积占比变化趋于稳定。华中、东北、西北和西南青藏高原及其周边地区随排放升高极端降水事件发生频率与降水强度增加。不同地区极端降水对排放升高的响应有明显的区域差异,华北、东北和西北地区响应程度相近且规律性增加,华中、西南地区响应程度相近但无规律变化,华东和华南地区响应程度接近且强度升高面积占比接近于1。
Abstract:[Objective]In order to analyze the change characteristics of extreme precipitation events in Chinese mainland under different historical and future emission scenarios under the background of global warming, and to study the change law of frequency and intensity of extreme precipitation events in different regions of China, [Methods]Historical precipitation data of daily scale(1979—2021) and precipitation data of CMIP6 future scenario model(2015—2100) were selected. Using Mann-Kendall test and other method, the spatial and temporal trends of extreme precipitation under historical and future low(SSP1-2.6), medium low(SSP2-4.5), medium high(SSP3-7.0) and high(SSP5-8.5) emission scenarios were analyzed.[Results]The result show that: From 1979 to 2021, the extreme precipitation index in all regions of China presents a spatial pattern of high in the east and low in the west, and the number of consecutive dry days(CDD) and rainy days(RD) show a downward trend nationwide, while other extreme precipitation indexes(such as the maximum 1 d precipitation Rx1day) and the number of days(such as the number of heavy rain days R25) show an upward trend. The trend is most significant in East, South and Southwest China.In the future, the change trend of extreme precipitation day and quantity index will also be different under different economic paths, and the proportion of rising area will increase the most from 2045 to 2075. Under the SSP3-7.0 path, the increase of extreme precipitation in East China is the largest, and the increase area of extreme precipitation daily index in South China is the smallest under the SSP2-4.5 path. The extreme precipitation index in North China, Northwest and Northeast China changes with the increase of emission, and the increase area of extreme precipitation index affected by the increase of emission is the highest in southwest China.[Conclusion]The historical data show that the frequency and intensity of extreme precipitation events in China have an increasing trend. Under the four economic paths of the future scenario model, the area proportion of the increase of extreme precipitation intensity in the whole country has increased to different degrees, and the change of the area proportion tends to be stable in the later part of this century(2060—2100).In central China, Northeast China, Northwest China and Southwest Tibet Plateau and its surrounding areas, the frequency and intensity of extreme precipitation events increased with the increase of emission. There are obvious regional differences in the response of extreme precipitation to emission increase in different regions. The response degree of extreme precipitation in North China, Northeast China and Northwest China is similar and increases regularly; the response degree of extreme precipitation in central China and Southwest China is similar but changes irregularly; the response degree of extreme precipitation in East China and South China is similar and the proportion of area with intensity increase is close to 1.
[1] 周天军,陈梓明,陈晓龙,等.IPCC AR6报告解读:未来的全球气候:基于情景的预估和近期信息[J].气候变化研究进展,2021,17(6):652-663.ZHOU T J,CHEN X M,CHEN X L,et al.Interpreting IPCC AR6:future global climate based on projection under scenarios and on near-term information[J].Climate Change Research,2021,17(6):652-663.
[2] MAZDIYASNI O,AGHAKOUCHAK A,DAVIS S J,et al.Increasing probability of mortality during Indian heat waves[J].Science Advance,2017,3(6):e1700066.
[3] GE F,ZHU S P,LUO H L,et al.Future changes in precipitation extremes over Southeast Asia:insights from CMIP6 multi-model ensemble[J].Environmental research letters,2021,16(2):24013.
[4] THASNEEM S A,CHITHRA N R,THAMPI S G.Analysis of extreme precipitation and its variability under climate change in a river basin[J].Natural Hazards,2019,98(3):1169-1190.
[5] ZHU H H,JIANG Z H,LI L.Projection of climate extremes in China,an incremental exercise from CMIP5 to CMIP6[J].Science Bulletin,2021,66(24):2528-2537.
[6] XU H W,CHEN H P,WANG H J.Future changes in precipitation extremes across China based on CMIP6 models[J].International Journal of Climatology,2022,42(1):635-651.
[7] ELIZABETH A M,BUNTING E,HERNDON J,et al.Conflict and its relationship to climate variability in Sub-Saharan Africa[J].Science of The Total Environment,2021,775:145646.
[8] 梁丽霞,张忠扬,梁洁.祖厉河流域降水指标的周期性研究[J].水利发展研究,2022,22(6):65-70.LIANG Lixia,ZHANG Zhongyang,LIANG Jie.Periodicity of precipitation index in Zuli River Basin[J].Water Resources Development Research,2022,22(6):65-70.
[9] KAMAE Y,IMADA Y,KAWASE H,et al.Atmospheric rivers bring more frequent and intense extreme rainfall events over East Asia under global warming[J].Geophysical Research Letters,2021,48(24):e2021GL096030.
[10] PAPALEXIOU S M,MONTANARI A.Global and regional increase of precipitation extremes under global warming[J].Water Resources Research,2019,55(6):4901-4914.
[11] SUN Q H,ZHANG X B,ZIWER F,et al.A global,continental,and regional analysis of changes in extreme precipitation[J].Journal of Climate,2021,34(1):243-258.
[12] PATZ J A,VAVURS S J,UEJIO C K,et al.Climate change and waterborne disease risk in the Great Lakes Region of the U.S[J].American Journal of Preventive Medicine,2008,35(5):451-458.
[13] LI X,ZHANG K,BAO H J,et al.Climatology and changes in hourly precipitation extremes over China during 1970—2018[J].Science of The Total Environment,2022,839:156-297.
[14] 魏培培,董广涛,史军,等.华东地区极端降水动力降尺度模拟及未来预估[J].气候与环境研究,2019,24(1):86-104.WEI P P,DONG G T,SHI J,et al.Dynamical downscaling simulation and projection of extreme precipitation over East China[J].Climatic and Environmental Research,2019,24(1):86-104.
[15] GUO W Z,YANG I,QUAN L C,et al.The increasing predominance of extreme precipitation in Southwest China since the late 1970s[J].Atmospheric and Oceanic Science Letters,2022,15(5):100227.
[16] HU W,YAO J,HE Q,et al.Changes in precipitation amounts and extremes across Xinjiang (Northwest China) and their connection to climate indices[J].PeerJ,2021,9(6903):e10792.
[17] NASHWAN M S,SHAHID S.A novel framework for selecting general circulation models based on the spatial patterns of climate[J].International Journal of Climatology,2020,40(10):4422-4443.
[18] VELAZQUEZ J A,TROIN M,CAYA D,et al.Evaluating the time-invariance hypothesis of climate model bias correction:Implications for hydrological impact studies[J].Journal of Hydrometeorology,2015,16(5):2013-2026.
[19] 李双林,韩乐琼,卞洁.基于IPCC AR4部分耦合模式结果的21世纪长江中下游强降水预估[J].暴雨灾害,2012,31(3):193-200.LI S L,HAN L Q,BIAN J.Projecting heavy rainfall events in the middle and lower reach of the Yangtze River valley in the 21st century based on IPCC AR4 simulations[J].Torrential Rain Disaster,2012,31(3):193-200.
[20] LI W,JIANG Z H,ZHANG X B,et al.Additional risk in extreme precipitation in China from 1.5℃ to 2.0℃ global warming levels[J].Science Bulletin,2018,63(4):228-234.
[21] 吴佳,周波涛,徐影.中国平均降水和极端降水对气候变暖的响应:CMIP5 模式模拟评估和预估[J].地球物理学报,2015,58(9):3048-3060.WU J,ZHOU B T,XU Y.Response of precipitation and its extremes over China to warming:CMIP5 simulation and projection[J].Chinese Journal of Geophysics,2015,58(9):3048-3060.
[22] 刘占明,徐丹,魏兴琥,等.北江流域汛期降水结构变化特征[J].热带地理,2020,40(1):145-153.Li Z M,XU D,WEI X H,et al.Variation characteristics of the precipitation structure during the rainy season in the Beijiang River Basin,China[J].Tropical Geography,2020,40(1):145-153.
[23] DU H,WANG Y,WANG Z,et al.Spatial and temporal characteristics of the daily precipitation concentration index over China from 1979 to 2015[J].Hydrology Research,2020,51(3):562-582.
[24] 黄国如,陈晓丽.北江飞来峡流域TRMM卫星降雨数据适应性研究[J].南水北调与水利科技,2019,17(4):27-36.HUANG G R,CHEN X L.Adaptability of TRMM satellite rainfall data in Feilaixia catchment of Beijiang River Basin[J].South-to-North Water Transfers and Water Science & Technology,2019,17(4):27-36.
[25] 雷华锦,马佳培,李弘毅,等.基于分位数映射法的黑河上游气候模式降水误差订正[J].高原气象,2020,39(2):266-279.LEI H J,MA J P,LI H Y,et al.Bias correction of climate model precipitation in the upper Heihe River Basin based on quantile mapping method[J].Plateau Meteorology,2020,39(2):266-279.
[26] 刘倩,高路,马苗苗,等.辽宁大凌河流域气温和降水降尺度研究[J].水利水电技术(中英文),2021,52(9):16-31.LIU Qian,GAO Lu,MA Miaomiao,et al.Downscaling of temperature and precipitation in the Daling River Basin,Liaoning Province[J].Water Resources and Hydropower Engineering,2021,52(9):16-31.
[27] 向竣文,张利平,邓瑶,等.基于CMIP6的中国主要地区极端气温/降水模拟能力评估及未来情景预估[J].武汉大学学报(工学版),2021,54(1):46-57.XIAN W J,ZHANG L P,DENG Y,et al.Projection and evaluation of extreme temperature and precipitation in major regions of China by CMIP6 models[J].Engineering Journal of Wuhan University,2021,54(1):46-57.
[28] 李佳欣,张歌,秦紫东,等.挠力河流域地表水-地下水联合模拟及未来水资源量评估[J].水利水电技术(中英文),2022,53 (11):78-85.LI Jiaxin,ZHANG Ge,QIN Zidong,et al.Joint modelling of surface-groundwater interaction and assessment of future water resources in the Naoli River Basin[J].Water Resources and Hydropower Engineering,2022,53(11):78-85.
基本信息:
DOI:10.13928/j.cnki.wrahe.2023.08.002
中图分类号:P467
引用信息:
[1]李慧慧,栾承梅,夏栩,等.基于CMIP6气候模式的中国大陆未来极端降水情景预估[J],2023,54(08):16-29.DOI:10.13928/j.cnki.wrahe.2023.08.002.
基金信息:
国家自然科学基金项目(41877147)