Temperature trend analysis and extreme high temperature prediction based on weighted Markov Model in Lanzhou

In this study, temporal trend analysis was conducted on the annual and quarterly meteorological variables of Lanzhou from 1951 to 2016, a weighted Markov model for extremely high temperature prediction constructed. Several non-parametric methods were used analyse variables. Considering that sequence autocorrelation may affect accuracy test, we performed an test carried out sequences with after removing correlation. The results show maximum temperature, minimum average in all have significant upward different performances each season. detail, summer is not significant, while winter most which leads more “warm winter” phenomenon. Finally, construct obtain conclusion by are consistent actual situation.