粤港澳大湾区极端降雨的时空变化及其驱动因素探究
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(1.南方科技大学深圳市城市环境健康风险精准测量与预警技术重点实验室,广东 深圳 518055;2.南方科技大学环境科学与工程学院,广东 深圳 518055 )

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王垚(1995—),男,博士研究生,主要从事极端水文事件研究。E-mail:12131078@mail.sustech.edu.cn 通信作者:史海匀(1985—),男,研究员,博士,主要从事极端水文事件研究。E-mail:shihy@sustech.edu.cn

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深圳市基础研究专项面上项目 (JCYJ20210324105014039)


Exploring spatiotemporal variations and driving factors of extreme precipitation in Guangdong-Hong Kong-Macao Greater Bay Area
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(1.Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, Southern University of Science and Technology, Shenzhen 518055, China;2.School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China)

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    摘要:

    基于1979—2018年中国区域地面气象要素驱动数据集和多种大气环流模式指数,采用改进的Mann-Kendall趋势检验法、皮尔逊相关分析、小波分析等方法,探究了粤港澳大湾区极端降雨的时空分布特征及其与大气环流模式的关系。结果表明:粤港澳大湾区极端降雨总体呈现上升趋势,空间分布以中北部地区上升趋势较为显著,且主要集中在6月;与大湾区极端降雨相关性最强的大气环流模式是东亚季风,其次是太平洋年代际振荡和厄尔尼诺南方涛动;东亚季风对大湾区不同极端降雨指数有稳定的8~16月周期影响;厄尔尼诺南方涛动和太平洋年代际振荡的影响则较为复杂,其与东亚季风存在一定的耦合作用。

    Abstract:

    Based on the China Regional Ground Surface Meteorological Element Driving Dataset from 1979 to 2018 and multiple atmospheric circulation mode indices, the spatiotemporal distribution characteristics of extreme precipitation in the Guangdong-Hong Kong-Macao Greater Bay Area and their relationships with atmospheric circulation modes were explored using improved Mann Kendall trend test method, Pearson correlation analysis, wavelet analysis and other methods. The results show that extreme precipitation in the Greater Bay Area shows an overall increasing trend, with the most significant increasing trend spatially distributed in the central and northern regions, and extreme precipitation is concentrated in June mostly. The atmospheric circulation mode which is most strongly correlated with extreme precipitation in the Greater Bay Area is EAM(East Asian Monsoon), followed by PDO(Pacific Decadal Oscillation) and ENSO(El NioSouthern Oscillation). The EAM has a stable 8~16 month cyclic impact on different extreme precipitation indices in this region, while ENSO and the PDO show more complex correlations, with some coupling effects existing between them and the EAM.

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王垚,史海匀.粤港澳大湾区极端降雨的时空变化及其驱动因素探究[J].水资源保护,2024,40(6):28-37, 77.(WANG Yao, SHI Haiyun. Exploring spatiotemporal variations and driving factors of extreme precipitation in Guangdong-Hong Kong-Macao Greater Bay Area[J]. Water Resources Protection,2024,40(6):28-37, 77.(in Chinese))

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  • 收稿日期:2024-02-07
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  • 在线发布日期: 2025-01-02
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