摘要
利用2018—2023年四川省气象灾害预警信息发布数据,运用分类统计的方法分析了预警信息发布类别、等级和区域的时空分布特征。结果表明:发布量排在前五位的四川省气象灾害预警信息依次为雷电、暴雨、大风、高温和道路结冰,共占发布总量的92.6%;发布次数最多的黄色预警信息占发布总量的59.9%,发布次数最少的红色预警信息仅占发布总量的3.0%;预警信息发布次数最多的地区是凉山州,其次为阿坝州和宜宾市,整体上呈西多东少的分布特征;预警信息发布量在3、4月开始呈现出上升趋势,7、8月达到峰值,9月呈现出断崖式的下降趋势。根据上述时空分布特征所提出的四川省气象灾害预警信息精准靶向发布工作建议,有利于进一步提升四川省气象预警信息靶向发布能力,进而更好地发挥气象防灾减灾第一道防线的作用。
The spatial and temporal distribution characteristics of the categories,grades and regions of meteorological disaster early warning information release were analyzed by the method of classification statistics,based on the release records of early warning information in Sichuan Province from 2018 to 2023.The results show that the top five meteorological disaster warning information in Sichuan are lightning,rainstorm,gale,high temperature and road icing,accounting for 92.6%of the total.The yellow warning information issued the most,accounting for 59.9%of the total,while the red warning information issued the least,accounting for only 3.0%of the total.On the whole,the warning information showed a spatial distribution of more in the west and less in the east.Liangshan Prefecture issued the most times,followed by Aba Prefecture and Yibin City.The frequency of warning information release showed an upward trend in March and April,reached a peak in July and August,and showed a cliff-like decline in September.On the basis of the above,the suggestions on the accurate targeted release of meteorological disaster early warning information in Sichuan are put forward,which is conducive to further improving the targeted release ability of meteorological early warning information in Sichuan Province,so as to better play the role of the first line of defense for meteorological disaster prevention and reduction.
作者
徐诚
袁媛
张虹娇
叶巍
王悦
XU Cheng;YUAN Yuan;ZHANG Hongjiao;YE Wei;WANG Yue(Sichuan Provincial Meteorological Service Centre,Chengdu 610072,China)
出处
《高原山地气象研究》
2024年第S01期118-124,共7页
Plateau and Mountain Meteorology Research
基金
中国气象局软科学研究项目自主项目(2023ZZXM9)。
关键词
气象灾害
预警信息
时空分布
靶向发布
防灾减灾
Meteorological disaster
Early warning information
Spatial and temporal distribution
Targeted release
Disaster prevention and mitigation