中文摘要：

分别采用高斯分布函数和偏态分布函数分析了厦门市1954—2004年51年日观测温度资料中的高温破纪录事件的统计规律,并以此采用蒙特卡罗方法对厦门市未来高温破纪录事件发展趋势进行了模拟.结果显示：厦门近50年来6月的日温度观测资料更符合偏态函数统计规律性;但理论研究表明偏态函数与高斯函数有着同样的收敛极限,即Gumbel分布函数.模拟结果还显示：在全球增暖背景下的基于偏态函数分布的蒙特卡罗模拟能较好地揭示未来厦门市极端事件发生规律,并对厦门未来的10年6月份日温度概率分布做了预测.全球增暖背景,一方面使日均温度升高;另一方面增加了高温破纪录事件发生的概率.并基于中国131个站点1954—2004年51年日观测温度资料,给出了中国未来10年6月日平均温度的最概然温度分布图.

英文摘要：

Statistical characteristic of daily temperature series （1954—2004） of Xiamen station is analyzed by using Gaussian and skew distribution functions,and then the future probable trend of record temperature events （RBTE） is also simulated by using Monte-Carlo（MC） methods based on the Gaussian and skew distribution functions,respectively.Results show that the statistical property of nearly 50a daily observation temperature data in June of Xiamen station is more consistent with that obtained from the skew function.However,the theoretical study shows that the skew function and Gaussian function have the same limit of convergence,i.e.the Gumbel distribution function.The results also show that the MC simulation based on the skew distribution with global warming background can reveal the future probable extreme events well,and the Xiamen ＇s daily temperature distribution of June in the next 10 a is predicted.The global warming background can lead the occurrence probabilities of high-temperature record-breaking event and the average daily temperature to increase.In addition,based on the observed date in China,the spatial temperature distribution of the occurrence with the max probability over China in coming 10 years is also presented.