|国家科技期刊平台
首页|期刊导航|气象学报|江苏寒潮天气过程风险预评估方法研究

江苏寒潮天气过程风险预评估方法研究OA北大核心CSTPCD

Methodology in pre-assessment of the cold surge induced risks in Jiangsu province of China

中文摘要英文摘要

利用江苏省 1961-2020年 70个国家级及 1300多个区域自动气象站同时段的日最低气温重构数据,选取最低气温48h最大降温幅度、累计降温幅度、过程日极端最低气温和寒潮过程持续天数共 4个要素作为寒潮灾害气象致灾因子,综合信息熵权法和专家打分法确定各致灾因子权重,构建寒潮过程致灾危险性评估模型,形成致灾危险性指数长时间序列,采用百分位法确定危险等级.基于智能网格气温预报数据,计算寒潮过程预估致灾危险性指数,在此基础上结合承灾体暴露度及脆弱性信息,构建寒潮过程风险预评估模型,对高分辨率人口、国内生产总值(Gross Domestic Product,GDP)和小麦等承灾体进行风险预估,同时考虑前期气温对小麦生长的影响,修正了小麦脆弱性指标.结果表明:(1)江苏省历年寒潮过程发生频次总体呈现 20世纪后 40年多、21世纪前 20年少的态势,北部地区发生频次显著多于南部地区;寒潮过程的气象致灾因子强度大体上具有西部强于东部、北部强于南部的分布特征;(2)通过对 2022年 11月 28日—12月 3日江苏全省性寒潮天气过程的个例分析,可以得出与实际灾情基本相符的寒潮天气过程的致灾危险性预评估和风险预估结果.

Based on daily minimum temperature data collected at 70 national weather stations and reconstructed data collected at more than 1300 regional automatic stations during the same period from 1961 to 2020 in Jiangsu province,four variables related to cold waves are selected as the meteorological disaster causing factors of cold wave disasters.The weight of each disaster causing factor is determined by combining the information entropy weighting method and Delphi method.A disaster risk assessment model is established to produce a long-term series of disaster risk index,which is then used to determine the risk level by the percentile method.Based on intelligent grid temperature prediction data,the predicted disaster risk index for the cold wave process is calculated.A risk pre-assessment model for cold wave processes is then constructed by combining the exposure and vulnerability information of the disaster bearing body.The impact of early temperature on wheat growth is also considered to modify the wheat vulnerability index.The results are as follows:(1)The frequency of cold wave events in Jiangsu province generally has shown an upward trend in the last century and a downward trend in the 21 century,and the frequency of occurrence is significantly higher in northern Jiangsu than in southern Jiangsu.The intensities of meteorological disaster causing factors are generally stronger in the west than in the east,and stronger in the north than in the south.(2)Based on the case study of the cold wave event from 28 November to 3 December 2022,it is found that the results of the risk pre-assessment basically are consistent with actual disaster situation.

顾荣直;田心如;禹梁玉;陈小宇;李泽宇

江苏省气象台,南京,210041

大气科学

寒潮过程气象致灾因子智能网格预报危险性预估风险预估

Cold wave processMeteorological disaster causing factorIntelligent grid prediction dataHazard pre-assessmentRisk pre-assessment

《气象学报》 2024 (002)

247-256 / 10

中国气象局决策气象服务专项(CZX2022003)、江苏省气象局科研基金(KM202301)、江苏省社会发展重大科技示范项目(BE2023766).

10.11676/qxxb2024.20230085

评论