杨秋珍,徐明,李军. 2010. 对气象致灾因子危险度诊断方法的探讨[J]. 气象学报, 68(2):277-284, doi:10.11676/qxxb2010.028
对气象致灾因子危险度诊断方法的探讨
A quantitative and objective approach to diagnosing the hazard degree of the meteorological disastrous factors
投稿时间:2008-11-02  修订日期:2009-03-18
DOI:10.11676/qxxb2010.028
中文关键词:  气象致灾因子,风险阈值,危险度诊断
英文关键词:Meteorological hazard factors, Risk thresholds, Hazard degree diagnosis
基金项目:国家重点基础研究发展计划(2009CB421500)和上海市科技兴农重点攻关项目“林地结构布局与提高生态功能及抗灾能力研究”
作者单位
杨秋珍 中国气象局上海台风研究所上海200030 
徐明 中国气象局上海台风研究所上海200030 
李军 上海区域气候中心上海200030 
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中文摘要:
      气象灾害损失与风险大小取决于气象致灾因子危险性、承灾体脆弱性、自然与人为防控在孕灾环境中时空配置格局及交互作用。但对于一定区域与时段而言,后两个因素相对稳定,气象致灾因子多变,其不同时空分布格局很大程度上决定了灾害的地域性及时间变化特征。对致灾因子危险性予以准确诊断是客观评估气象灾害损失与风险大小的基本前提。为此,文中提出了气象致灾因子危险度定义及点面相结合的诊断模型:(1)将危险度定义为事件致灾因子量值与风险阈值场中各级风险水平阈值之间的接近程度;(2)采用随机变量概率分布模型估计各地各种特定概率下的气象事件致灾因子量级,构建气象致灾因子风险阈值场;(3)联合空间相似和距离参量构建危险度诊断模型,以刻划事件致灾因子与各级风险阈值分布形态相似性及数值差异大小,据此计算事件致灾因子与风险阈值场中各级风险阈值的接近程度,以接近度最大为原则确定某过程致灾因子总体危险性水平等级。然后以上海地区风致灾因子危险性诊断为例,计算了上海各地不同风险水平下年最大风速阈值以及各地各级年最大风速的风险水平,构建了上海地区年最大风速的风险阈值场,结果表明:上海沿海地区的南汇、崇明、金山等地为年最大风速高值区,也是一定风险水平下的最大风速高值区,同时又是8级以上强风频发区及高危险区;相对地,本市较内陆的区域,则是年最大风速低值区,也是一定风险水平下的最大风速低值区,同时又是8级以上强风稀遇区及低危险区;一定重现期下最大风速阈值地区分布也有类似规律。最后,应用该模型对影响上海地区热带气旋及其他天气过程共30余个例作出风危险度诊断,结果表明,以1977年9月11日的7708号热带气旋风危险度最高,总体上与风险水平为8年一遇的年最大风速阈值最为接近;1986年8月27日8615号热带气旋与1983年6月3日其他天气过程个例风危险度为第2,总体接近于7年一遇年最大风速阈值;8114号与9711号热带气旋风危险度则与4年一遇年最大风速阈值最为接近;7413号、7503号、7909号、8506号热带气旋的风危险度接近3年一遇年最大风速阈值;而0509号热带气旋“麦莎”、0515号热带气旋“卡努”风危险度总体上接近于2年一遇的年最大风速阈值。其他热带气旋影响个例,其风危险度多数与重现期约2年一遇的年最大风速阈值接近。实际应用结果表明,所提出的这一点面结合的危险度的诊断方法,能较客观定量地评定气象致灾因子的危险性程度。
英文摘要:
      The losses and risks caused by meteorological disasters are determined by the potential hazard of the meteorological events, vulnerability of the hazard affected body, as well as natural and man made resilience in the disaster pregnant environment. Among these factors, two of them related to hazard affected body or disaster pregnant environment are comparatively stable for a certain place and period, and meteorological hazards are however changeable. The spatial and temporal distribution patterns of meteorological hazards largely determine the place and evolution of disasters. Accurate diagnosis of the hazard degree is the base for assessing the loss and risk of meteorological disasters. In this paper, the definition of meteorological hazard and its diagnostic model for both local and regional areas are put forward, and the relationship between the value of the random variables and its probability is applied to describe the distribution of weather event hazards and build up the risk threshold field that is composed of hazard threshold values at each risk probability level. The meteorological hazard degree is defined as the integration of the similarity and approach degree of the observational values for an event to the threshold value at various probability risk levels in the risk field. Using the random variable probability distribution model, the meteorological hazard threshold values under the specific risk probability levels in any given place and their threshold field are determined, and the quantitative hazard degree diagnostic model is established by combining the spatial similarity with the distance parameters. As a demonstration, the gale(strong wind) hazard diagnostic model is set up and then the hazard degrees about TC0509,TC0515 and the other gale events in the thirty cases in Shanghai are estimated. The results are as follows : the largest gale hazard degree is from TC 7708,its overall hazard degree level is mostly close to the threshold of maximum wind speed of 8-year return period. The gale hazard degrees of TC 8615 and the case of other weather process in 3 June, 1983 are secondary, with the value close to that of 7-year return period, and the maximum wind speed hazard degrees of TC 9711 and TC 8114 are close to that of 4-year return period. The gale hazard degrees of TC7413, TC7503,TC7909 and TC8506 are close to the 3-year return period, and the TC0509 "Matsa" and the TC0515 “Kanu” are close to 2-year return period. The results also show the main distribution characteristic of annual maximum wind speed with return periods from 1 to several hundreds years in Shanghai. The coastal regions in Shanghai such as Nanhui, Chongming, Jinshan are the areas of high wind speed and also the high-value areas of the maximum wind speed under a certain risk probability level, and, at the same time, the high frequency and high-risk areas of strong winds more than eight grade are located here as well. In contrast, the inland regions in Shanghai are the low wind speed areas and the low-value areas of maximum wind speed under the certain risk levels where strong winds more than eight grade are rare observed.Application results show that the diagnostic approach is objective and quantitative in assessing the hazard degree of weather events, which provides a reference for the meteorological disaster evaluation.
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