西南地区的极端降水时空演变特征研究
Study on the Spatiotemporal Evolution Characteristics of Extreme Precipitation in Southwest China
DOI: 10.12677/gser.2026.152034, PDF,   
作者: 董 怡:成都信息工程大学资源环境学院,四川 成都;徐潍溢*:泸州市纳溪区气象局,四川 泸州;胡兴宇:西和县气象局,甘肃 陇南;李雨虹:三台县气象局,四川 绵阳;刘昱含:垫江县气象局,重庆;胡 进:青神县气象局,四川 眉山;贾思源:乐东黎族自治县气象局,海南 乐东
关键词: 极端降水时空演变ETCCDI指数Hurst指数西南地区Extreme Precipitation Spatiotemporal Evolution ETCCDI Indices Hurst Exponent Southwest China
摘要: 基于西南地区1960~2023年高分辨率逐日降水格点数据,选取最大1日降水量(Rx1day)、持续干燥日数(CDD)、持续湿润日数(CWD)和中雨日数(R10)等极端降水指数,采用Theil-Sen斜率估计、Mann-Kendall趋势检验及Hurst指数等方法,系统分析了西南地区极端降水的时空演变特征及未来趋势。结果表明:(1) 西南地区极端降水空间分布呈显著异质性,整体呈现东南高、西北低的格局,Rx1day高值区集中在四川盆地西南部、贵州东部和广西北部;(2) 时间变化上,Rx1day呈显著上升趋势(0.071 mm/a, p < 0.05),CDD波动上升(0.043 day/a),CWD呈显著下降趋势(−0.041 day/a, p < 0.05),降水过程趋于“碎片化”;(3) Hurst指数分析显示各指数均具有强持续性(H = 0.71~0.75),表明极端降水增强与干旱延长的趋势难以逆转;(4) 西南地区极端降水呈现“强度增强、历时缩短、旱涝急转”的显著特征,未来极端降水风险将进一步累积。研究结果可为区域水资源管理、极端气候事件风险评估及防灾减灾对策制定提供科学依据。
Abstract: Based on high-resolution daily precipitation gridded data from 1960 to 2023 in Southwest China, this study selects extreme precipitation indices such as maximum 1-day precipitation (Rx1day), consecutive dry days (CDD), consecutive wet days (CWD), and the number of moderate precipitation days (R10). Methods including Theil-Sen slope estimation, Mann-Kendall trend test, and Hurst index are employed to systematically analyze the spatiotemporal evolution characteristics and future trends of extreme precipitation in the region. The results indicate that: (1) The spatial distribution of extreme precipitation in Southwest China exhibits significant heterogeneity, generally presenting a pattern of high in the southeast and low in the northwest. High-value areas of Rx1day are concentrated in Southwestern Sichuan Basin, Eastern Guizhou and Northern Guangxi; (2) Temporally, Rx1day shows a significant increasing trend (0.071 mm/a, p < 0.05), CDD fluctuates upward (0.043 day/a), while CWD demonstrates a significant decreasing trend (−0.041 day/a, p < 0.05), suggesting a trend towards more “fragmented” precipitation processes; (3) Hurst index analysis reveals strong persistence for all indices (H = 0.71~0.75), indicating that the trends of intensified extreme precipitation and prolonged drought are difficult to reverse; (4) Extreme precipitation in Southwest China exhibits notable characteristics of “intensifying intensity, shortening duration, and rapid transitions between drought and flood”, with future risks of extreme precipitation expected to accumulate further. The findings can provide a scientific basis for regional water resource management, risk assessment of extreme climate events, and the formulation of disaster prevention and mitigation strategies.
文章引用:董怡, 徐潍溢, 胡兴宇, 李雨虹, 刘昱含, 胡进, 贾思源. 西南地区的极端降水时空演变特征研究[J]. 地理科学研究, 2026, 15(2): 356-366. https://doi.org/10.12677/gser.2026.152034

参考文献

[1] IPCC (2021) Climate Change 2021: The Physical Science Basis. Cambridge University Press.
[2] Trenberth, K. (2011) Changes in Precipitation with Climate Change. Climate Research, 47, 123-138. [Google Scholar] [CrossRef
[3] Allan, R.P. and Soden, B.J. (2008) Atmospheric Warming and the Amplification of Precipitation Extremes. Science, 321, 1481-1484. [Google Scholar] [CrossRef] [PubMed]
[4] Fischer, E.M. and Knutti, R. (2016) Observed Heavy Precipitation Increase Confirms Theory and Early Models. Nature Climate Change, 6, 986-991. [Google Scholar] [CrossRef
[5] Pfleiderer, P., Schleussner, C., Kornhuber, K. and Coumou, D. (2019) Summer Weather Becomes More Persistent in a 2 °C World. Nature Climate Change, 9, 666-671. [Google Scholar] [CrossRef
[6] 张强, 张良, 崔显成, 等. 中国春季区域极端降水事件及其与前期海温的关系[J]. 气象学报, 2019, 77(4): 684-700.
[7] 翟盘茂, 王萃萃, 李威. 极端降水事件变化的观测研究[J]. 气候与环境研究, 2007, 12(2): 133-144.
[8] 任国玉, 封国林, 严中伟. 中国极端天气变化事件变化检测研究进展[J]. 气候与环境研究, 2010, 15(4): 337-353.
[9] Zhai, P., Zhang, X., Wan, H. and Pan, X. (2005) Trends in Total Precipitation and Frequency of Daily Precipitation Extremes over China. Journal of Climate, 18, 1096-1108. [Google Scholar] [CrossRef
[10] 中国气象局气候变化中心. 中国气候变化蓝皮书(2023) [R]. 北京: 科学出版社, 2023.
[11] 中国气象局气候变化中心. 中国气候变化蓝皮书(2024) [R]. 北京: 科学出版社, 2024.
[12] 黄建平, 冉津江, 季明霞. 干旱半干旱区气候变化研究综述[J]. 气候变化研究进展, 2013, 9(1): 31-38.
[13] 中国极端天气气候事件和灾害风险管理与适应国家评估报告发布[J]. 中国应急管理, 2015(3): 63-63.
[14] 郑度, 杨勤业, 刘燕华, 等. 中国的地理区划[M]. 北京: 科学出版社, 2008.
[15] 李吉均. 中国地貌格局与演变[J]. 地理研究, 1990, 9(3): 1-10.
[16] 丁一汇, 任国玉, 石广玉, 等. 气候变化国家评估报告(Ⅰ): 中国气候变化的历史和未来趋势[J]. 气候变化研究进展, 2006, 2(1): 3-8.
[17] 邹用昌, 李国平, 范广洲. 西南地区降水的水汽来源分析[J]. 大气科学学报, 2012, 35(2): 217-227.
[18] Xiong, Y.J., Qiu, G.Y., Mo, D.K., Lin, H., Sun, H., Wang, Q.X., et al. (2009) Rocky Desertification and Its Causes in Karst Areas: A Case Study in Yongshun County, Hunan Province, China. Environmental Geology, 57, 1481-1488. [Google Scholar] [CrossRef
[19] 丁文荣. 西南地区极端降水的时空变化特征[J]. 长江流域资源与环境, 2014, 23(7): 1071-1079.
[20] 四川省气象局. 四川省气候影响评价(2012年) [R]. 成都: 四川省气象局, 2012.
[21] 贵州省气象局. 贵州省气候影响评价(2020年) [R]. 贵阳: 贵州省气象局, 2020.
[22] 苏爱芳, 吕晓娜, 崔丽曼, 等. “21·7”河南极端暴雨过程的基本观测分析[J]. 气象, 2022, 48(1): 1-15.
[23] Alexander, L.V., Zhang, X., Peterson, T.C., Caesar, J., Gleason, B., Klein Tank, A.M.G., et al. (2006) Global Observed Changes in Daily Climate Extremes of Temperature and Precipitation. Journal of Geophysical Research: Atmospheres, 111, D05109. [Google Scholar] [CrossRef
[24] Moberg, A., Jones, P.D., Lister, D., Walther, A., Brunet, M., Jacobeit, J., et al. (2006) Indices for Daily Temperature and Precipitation Extremes in Europe Analyzed for the Period 1901-2000. Journal of Geophysical Research: Atmospheres, 111, D22106. [Google Scholar] [CrossRef
[25] 杨金虎, 江志红, 王鹏祥, 等. 中国年极端降水事件的时空分布特征[J]. 气候与环境研究, 2008, 13(1): 75-83.
[26] 王志福, 钱永甫. 中国极端降水事件的频数和强度特征[J]. 水科学进展, 2009, 20(1): 1-9.
[27] 罗玉, 范广洲, 华维, 等. 西南地区极端强降水变化趋势[J]. 气象科技, 2014, 42(3): 464-471.
[28] 袁文德, 郑江坤, 董奎. 1962-2019年西南地区极端降水事件的时空变化特征[J]. 资源科学, 2019, 36(4): 766-772.
[29] 李航, 杨啊丽, 贾志军. 西南地区极端降水时空变化及概率分布特征研究[J]. 地球科学前沿, 2024, 14(8): 1023-1035.
[30] 胡金龙, 张强, 李栋梁, 等. CHM_PRE V2.0: 考虑空间自相关和协变量的中国大陆高精度格点降水数据集[J]. 地球信息科学学报, 2023, 25(5): 1023-1038.
[31] Zhang, X., Alexander, L., Hegerl, G.C., Jones, P., Tank, A.K., Peterson, T.C., et al. (2011) Indices for Monitoring Changes in Extremes Based on Daily Temperature and Precipitation Data. Wiley Interdisciplinary Reviews: Climate Change, 2, 851-870. [Google Scholar] [CrossRef
[32] ETCCDI (2023) Climate Change Indices: Definitions.
http://etccdi.pacificclimate.org/list_27_indices.shtml
[33] Theil, H. (1950) A Rank-Invariant Method of Linear and Polynomial Regression Analysis. Proceedings of the Royal Netherlands Academy of Arts and Sciences, 53, 386-392.
[34] Sen, P.K. (1968) Estimates of the Regression Coefficient Based on Kendall’s Tau. Journal of the American Statistical Association, 63, 1379-1389. [Google Scholar] [CrossRef
[35] Mann, H.B. (1945) Nonparametric Tests against Trend. Econometrica, 13, 245. [Google Scholar] [CrossRef
[36] Kendall, M.G. (1975) Rank Correlation Methods. Griffin.
[37] Hurst, H.E. (1951) Long-Term Storage Capacity of Reservoirs. Transactions of the American Society of Civil Engineers, 116, 770-799. [Google Scholar] [CrossRef
[38] 李毅, 周慧, 李秦. 基于R/S分析的参考作物腾发量时间序列分形特征[J]. 节水灌溉, 2008(4): 5-8.
[39] Held, I.M. and Soden, B.J. (2006) Robust Responses of the Hydrological Cycle to Global Warming. Journal of Climate, 19, 5686-5699. [Google Scholar] [CrossRef
[40] 杨明鑫, 肖天贵, 李勇, 等. CMIP6模式对我国西南地区夏季气候变化的模拟和预估[J]. 高原气象, 2022, 41(6): 1557-1571.
[41] 田立德, 马鹏飞, 张伟, 等. 中国西南地区夏季早期大气水汽和降水中氧-18与过量氘的滞后及其驱动机制[J]. 水文学报, 2024, 36(5): 678-689.
[42] 黄荣辉, 陈际龙, 周连童, 等. 关于中国重大气候灾害与东亚气候系统之间关系的研究[J]. 气候与环境研究, 2003, 8(1): 1-15.
[43] 丁一汇, 司东. 中国汛期降水的年代际变化与季风系统[J]. 气候与环境研究, 2013, 18(4): 405-415.