关键词: 灰色模型, 马尔可夫链, 降水量, 预测, 吉林省

Abstract:

For more accurately predication and analysis of the spatial and temporal variation characteristics of precipitation of eight representative stations of Jilin Province, we used the unbiased grey Markov chain model to discuss the relationship between historical data volatility and the forecast accuracy. More than 83% predicted results are qualified. Baicheng, Qian’an, Changchun, Jiaohe, Siping, Tonghua six regional yearly precipitation shows a trend of decline, the damping ranges are 0.23%, 0.09%, 0.24%, 1.01%, 0.51%, 0.54%; while Yanji and Jingyu two regional precipitation is increasing, with growth rates of 2.6% and 0.54% respectively. The results show that the modified unbiased gray Markov chain model is suitable for Jilin Province’s precipitation forecast with higher accuracy. It shows that the precipitation has a trend of decreasing in Midwest of Jilin Province and the precipitation has a trend of increasing in eastern of Jilin Province. In the relation between volatility and forecast precision, the study finds that the greater the volatility of time series is, the larger the prediction error is.

Key words: gray model, Markov chain, precipitation, predication, Jilin Province