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.