DOI: 10.1007/s11069-021-04711-y
论文题名: Temperature trend analysis and extreme high temperature prediction based on weighted Markov Model in Lanzhou
作者: Pang Z. ; Wang Z.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 108, 期: 1 起始页码: 891
结束页码: 906
语种: 英语
中文关键词: Mann–Kendall test
; Meteorological variables
; Trend analysis
; Weighted Markov model
英文摘要: In this study, temporal trend analysis was conducted on the annual and quarterly meteorological variables of Lanzhou from 1951 to 2016, and a weighted Markov model for extremely high temperature prediction was constructed. Several non-parametric methods were used to analyse the trend of meteorological variables. Considering that sequence autocorrelation may affect the accuracy of the trend test, we performed an autocorrelation test and carried out trend analysis for sequences with autocorrelation after removing correlation. The results show that the maximum temperature, minimum temperature and average temperature in Lanzhou all have a significant upward trend and show different performances in each season. In detail, the trend of maximum temperature in the summer is not significant, while the upward trend of minimum temperature in the winter is the most significant, which leads to more and more “warm winter” phenomenon. Finally, we construct a weighted Markov prediction model for extremely high temperature and obtain the conclusion that the prediction results by the model are consistent with the actual situation. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169280
Appears in Collections: 气候变化与战略
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作者单位: School of Statistics, Lanzhou University of Finance and Economics, Lanzhou, Gansu, China; School of Mathematics and Statistics, Qinghai Normal University, Xining, Qinghai, China
Recommended Citation:
Pang Z.,Wang Z.. Temperature trend analysis and extreme high temperature prediction based on weighted Markov Model in Lanzhou[J]. Natural Hazards,2021-01-01,108(1)