广义帕累托分布在广东重现期风速计算中的应用

利用广东省86个国家气象观测站建站以来近70a的逐月最大风速序列和近20a(1999-2018年)的逐月最大风速序列,基于POT抽样法,分别采用三参数广义帕累托分布函数对各站的重现期风速进行了概率计算,计算过程中三参数广义帕累托分布函数分别采用矩估计(MOM)、极大似然估计(MLE)、似然矩估计(LM)和概率权矩估计(PWM)等4种参数估计方法,结合表征参数估计优良性的指标:均方根误差RMSE、拟合相对偏差和显著性水平为0.05的科莫戈洛夫检验拟合适度指标Kf对拟合效果进行检验,结果表明:基于POT抽样的概率权矩估计(PWM)拟合效果最好。

Application of Generalized Pareto Distribution to Calculation of Return-Period Extreme Wind Speeds over Guangdong

By use of the monthly maximum wind sequences of 70 years and 20 years from 86 national meteorological observation stations in Guangdong Province,the three-parameter Generalized Pareto Distribution(GPD)function is used to calculate the return-period wind speeds of 86 national meteorological observation stations,respectively.The four parameter estimation methods such as Moment Estimation(MOM),Maximum Likelihood Estimation(MLE),Likelihood Moment Estimation(LM)and Probability and Weight Moment Estimation(PWM)are used based on the Peaks-Over-Threshold(POT)sampling.The characterization parameter estimation indicators such as root-mean-square error(RMSE),fitting relative deviation(Rf)and Komogorov Test with a reliability of 0.05(Kf)are used to test the fitting effect.The results show that Probability Weight Moment Estimation(PWM)based on POT has the best fitting effect.