Application Of Markov Chain Predication Method On Meiyu

Climate statistics is a powerful tool to study weather, climate change. Statistical analysis of climate in the nineties of the last century has become the main direction of the modern climate statistics. Climate statistics much importance in the international arena, its climate is far from the rapid development of the field can be compared to other branches. Climate statistics for the study has become an international collaborative research on major issues. The powerful tool researching on this important and complex climate change is statistical theory and method of climate. Climate statistics is based on mathematical statistics. In the statistics climate, usually research on the questions like using the distribution function or frequency function to describe and compare the recorded probability structure or distribution feature, then estimate the values of unknown parameters.This paper has taken the Markov chain as main tool, the article first reviewed the application of Markov chain, the following described the basic theory of Markov chain, the classification methods of Markov chain theory and the steps of it. And then based on the method of Weighted Markov chain, predicting the plum rains intensity, there were two classifications be used and compared, in the last of this paper, random sequence was applied to farther compared different classifications and different categories’ impact of prediction accuracy.Through the results of the methods and analysis by this paper, it has proved that the using of Markov Chain to predict the strength of plum rains was efficacious, and orderly classification was better than sample average and variance classification in some applications, and the results of prediction accuracy of Markov chain describes the reliability of the method.