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珠江三角洲地区暴雨事件驱动因子研究
引用本文:宋金帛,张强,王港,吴文欢.珠江三角洲地区暴雨事件驱动因子研究[J].北京师范大学学报(自然科学版),2022,58(2):293-299.
作者姓名:宋金帛  张强  王港  吴文欢
作者单位:北京师范大学 地表过程与资源生态国家重点实验室, 地理科学学部, 100875,北京
基金项目:国家自然科学基金资助项目(41771536);;国家重点研发计划资助项目(2019YFA0606900);
摘    要:利用CMORPH降水数据、ERA5气象数据、欧空局土地利用数据、热带气旋灾害资料等多源异构数据,运用相关分析、M-K检验、合成分析、Student’s t-test等多种统计方法辨识珠江三角洲地区暴雨关键驱动因子.研究发现:不同时间尺度上暴雨事件年际变化趋势均不显著;净水汽通量、强热带风暴、气压变化等是研究区暴雨事件的主要驱动因子,夏季西北太平洋副高位置及强度对研究区暴雨的发生也有影响,城市化程度、厄尔尼诺/拉尼娜现象等对研究区暴雨事件影响不显著.研究结果可为珠三角暴雨事件、暴雨致洪及城市内涝的预测与灾害风险评估提供理论支撑和决策依据. 

关 键 词:暴雨事件    珠江三角洲    驱动因子    相关分析    M-K检验    Student’s  t-test
收稿时间:2021-05-22

Rainstorm events and driving factors in Pearl River Delta
Institution:State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, 100875, Beijing, China
Abstract:Pearl River Delta is socioeconomically highly developed.Flash floods and urban inundation are mainly attributed to rainstorms.It is of great significance to investigate causes and driving factors behind such rainstorms.Most previous studies were done focusing on singular factors.In this study, precipitation indices were defined, potential driving factors of rainstorm events were identified, from CMORPH precipitation data, ERA5 meteorological data, ESA land use data and tropical cyclone disaster data.The driving factors of rainstorm events over Pearl River Delta were identified by correlation analysis, M-K test, synthetic analysis and Student’s t-test.Trends in rainstorm events were found not statistically significant on varied time scales.Net water vapor flux, air pressure and frequency of tropical cyclones were identified to be important variables behind changes in rainstorm events.Location and intensity of western Pacific subtropical high in summer was found to affect occurrence of rainstorm events.Urbanization and El Nino/La Nina phenomenon had no influence on rainstorm events.Rainstorm events tended to decrease surface temperature, attributing to increased cloud coverage.Our work provides some theoretical support and decision-making basis for predicting occurrence of rainstorm events, and for human mitigation of rainstorm-related disasters. 
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