摘要
热带气旋在广东省内造成的影响具有显著的时空不均匀性,采用统计方法对1949—2022年间热带气旋登陆广东省情况进行分析,并根据PRITC V1.0数据集提供的数据对1949—2018年间热带气旋潜在风险指数的时空分布特征开展分析。结果表明:热带气旋主要在6—10月登陆广东,数量占登陆总数的94.2%;主要在粤西三市登陆,占比47.8%;珠江口以西登陆的热带气旋强度较珠江口以东更大。1970年以来,逐年平均指数10 a滑动平均呈上升趋势。热带气旋给广东省带来的降水影响超过大风影响。累计潜在风险指数最高的城市为湛江、汕尾、阳江、江门;且湛江、茂名、汕头的风雨综合指数10 a滑动平均基本呈增加趋势;结果可为各地区水公共安全防御工作提供参考。
The impact of tropical cyclones on Guangdong Province has significant spatiotemporal heterogeneity.This article has analyzed the situation of tropical cyclones landing in Guangdong Province from 1949 to 2022 and analyzed the temporal and spatial distribution characteristics of the potential risk index based on the data provided by the PRITC V1.0 dataset(from 1949 to 2018).The results show that tropical cyclones mainly make landfall in Guangdong from June to October,accounting for 94.2%of the total landfall,mainly landing in three cities in western Guangdong,accounting for 47.8%.The intensity of tropical cyclones landing to the west of the Pearl River Estuary is greater than that to the east of the Estuary.Since 1970,the annual average potential risk index has increased on a ten-year moving average.In addition,the impact of tropical cyclones on precipitation exceeds that of winds.The cities with the highest cumulative potential risk index are Zhanjiang,Shanwei,Yangjiang,and Jiangmen.Also,the combined index of TC-induced precipitation and wind in Zhanjiang,Maoming,and Shantou shows an increasing trend on the ten-year moving average.Overall,the results can provide references for disaster prevention and reduction work in different regions.
作者
张之琳
邱静
洪昌红
刘达
ZHANG Zhilin;QIU Jing;HONG Changhong;LIU Da(Guangdong Research Institute of Water Resources and Hydropower,Guangzhou 510635,China;State and Local Joint Engineering Laboratory of Estuarine and Hydraulic Technology,Guangzhou 510635,China)
出处
《广东水利水电》
2024年第2期1-6,共6页
Guangdong Water Resources and Hydropower
基金
广东省水利科技创新项目(编号:2021-01)
广州市科技计划项目(编号:2023A04J0991)。
关键词
热带气旋
潜在风险指数
台风登陆
时空分布
广东省
tropical cyclone
potential risk index
typhoon landfall
spatial and temporal distribution
Guangdong Province
