基于混合Copula模型的灾害相关结构分析——以内蒙古中部强沙尘暴为例

Dependence Analysis of Disaster Based on Mixed Copula Model——A Case Study of the Severe Dust Storm Disaster in Central Inner Mongolia

为解决自然灾害发生频率评估中的偏差问题,利用内蒙古中部强沙尘区的植被返青期和春季大风事件资料,构建了单一类型和多类型混合的Copula函数模型,对比了拟合精度并进行了相关结构的分析,通过计算极端灾害事件对应的各变量的尾部阈值,评估了变量的尾部风险。结果表明:混合Copula函数比单一Copula函数更适合于构建两个特征变量的联合分布模型;两个特征变量具有非对称的尾部关系,且极端下尾有较强的正相关关系,出现极端低值时,两者具有更高的相关性;植被返青期早于90d和春季大风事件小于9次,以及植被返青期晚于223d和春季大风事件大于100次时,两个特征变量有较高的正相关关系,当两者同时取得尾部阈值时,发生强沙尘暴可能性更高。因此利用混合Copula函数能够有效提高灾害特征变量相关结构模型的拟合优度,改善灾害发生频率评估精度。

Aiming at solving the deviation problem of natural disaster frequency assessment,based on the vegetation green up date(G)and spring strong wind event(D)data in central Inner Mongolia,this study established the single as well as mixed Copula model,compared the fitting results of both models,conducted corresponding dependence structure analysis,calculated the tail thresholds of variables that correspond to the extreme events and evaluate the risk of variables in the tails.The results show that:mixed Copula is more suitable for building the joint distribution model of G and D than single Copula;G and D show an asymmetrical pattern in the upper and lower tails.G and D have a strong positive correlation in the lower tail,and the correlations between the two variables become significantly stronger when the extreme low values occur;there is a strong positive correlation between the two variables when G<90 day and D<9 or G>223 day and D>100.Severe dust storms are more likely to occur when the two variables reach the thresholds.Therefore,the goodness of fit of dependence structure model and the accuracy of frequency assessment can be improved by using mixed Copula function.