作　　者： ; ; ; ;

机构地区： 广东省气候中心

出　　处： 《应用生态学报》 2018年第8期2667-2674,共8页

摘　　要： 寒害是广东省继洪涝、台风之后的第三大灾害性天气,预测寒害重现期对科学防寒减灾具有实际意义.本研究基于广东省86个县(市)气象站1961—2015年冬季(12月—翌年2月)逐日气象资料,以积寒指数为寒害指标,采用Gumble分布、Weibull分布、对数正态分布和Pearson-Ⅲ型分布4个模型对各站寒害极值进行概率分布拟合,并检验筛选最优模型,计算不同重现期的寒害极值.结果表明:广东省86个县(市)气象站中,有77个站适用Pearson-Ⅲ型分布,8个站适用对数正态分布,1个站用Gumble分布拟合最佳,Weibull分布函数不适用于广东寒害极值分布的拟合.根据各站最优拟合分布函数,预测广东86个站点10、25、50和100年寒害重现期,其相对误差均较小(≤6%);其多年一遇的积寒极值呈明显的纬向分布特征,表现为北多南少,与寒害发生过程中最低气温、平均气温、降温幅度等分布特征一致.研究成果可为广东相关行业科学防寒提供依据. Chilling is the third weather disaster following flood and typhoon in Guangdong Province.Prediction of chilling return period is of practical significance for scientific reduction and protection of disaster. Four models,including Gumbel distribution,Weibull distribution,log-normal distribution and Peasron-III distribution,were applied,based on the chilling index,to fit the probability distribution of chilling extreme calculated by chilling accumulation for 86 weather stations of Guangdong Province from 1961 to 2015（ December to the following February）. The optimal models were selected to calculate the chilling extreme value of return periods. Results showed that Pearson-III distribution was the optimal model for 77 out of the 86 weather stations. The log-normal distribution was optimal for eight weather stations and Gumbel distribution was optimal for only one station.Weibull distribution was not suitable for modeling extreme value of Guangdong Province. Different return periods of 10-,25-,50-and 100-year were predicted by optimal distribution models respectively,with a relative error less than 6%. Chilling extreme for years presented obviously latitude distribution feature,with more in north side and less in south side,which matched the distributions of the lowest temperature,average temperature and temperature dipping scale during chilling period.Our results are useful for guiding the chilling defense for relevant industries in Guangdong Province.

关 键 词： 寒害 极值分析 皮尔逊 分布 耿贝尔分布 对数正态分布 分布

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