蚩志锋, 闫军辉, 刘金科, 武黎黎. 基于信息熵的武汉市近110年气温变化特征研究[J]. 信阳师范学院学报(自然科学版), 2019, 32(4): 579-583. DOI: 10.3969/j.issn.1003-0972.2019.04.011
引用本文: 蚩志锋, 闫军辉, 刘金科, 武黎黎. 基于信息熵的武汉市近110年气温变化特征研究[J]. 信阳师范学院学报(自然科学版), 2019, 32(4): 579-583. DOI: 10.3969/j.issn.1003-0972.2019.04.011
CHI Zhifeng, YAN Junhui, LIU Jinke, WU Lili. Study on Characteristics of Temperature Variation in Wuhan City for the Past 110 Years Based on Information Entropy[J]. Journal of Xinyang Normal University (Natural Science Edition), 2019, 32(4): 579-583. DOI: 10.3969/j.issn.1003-0972.2019.04.011
Citation: CHI Zhifeng, YAN Junhui, LIU Jinke, WU Lili. Study on Characteristics of Temperature Variation in Wuhan City for the Past 110 Years Based on Information Entropy[J]. Journal of Xinyang Normal University (Natural Science Edition), 2019, 32(4): 579-583. DOI: 10.3969/j.issn.1003-0972.2019.04.011

基于信息熵的武汉市近110年气温变化特征研究

Study on Characteristics of Temperature Variation in Wuhan City for the Past 110 Years Based on Information Entropy

  • 摘要: 利用1906-2015年武汉市逐月平均气温数据,采用Shannon熵、Renyi熵和Tsallis熵等方法分析了不同时间尺度下武汉市气温的变化特征;利用边际熵分析了月时间尺度气温变化特征,季节年代分配熵和年份年代分配熵分析气温年代(10 a)的季节和年际变化特征.结果表明:(1)武汉市近110 a2月的月均温最稳定,变异性最小;5月的月均温最不稳定,变异性最大.(2)武汉市近110 a夏季均温在8个年代稳定性最差,变异性最大;春季均温在3个年代稳定性最差,变异性最大,5个年代稳定性最好,变异性最小.(3)武汉市近110 a的年均温变异性呈周期性变化,变化周期为30年,未来10 a武汉市年均温将趋于稳定.

     

    Abstract: Based on the monthly temperature data of Wuhan City from 1906 to 2015, Shannon entropy, Renyi entropy and Tsallis entropy were used to analyze the variation characteristics of Wuhan city temperature at different time scales. The results show that:(1) the monthly mean temperature in February is the most stable and the variability is the smallest in Wuhan in past 110 years. The monthly average temperature in May is the most unstable and the variability is the biggest;(2) the seasonal mean temperature of Wuhan in the past 110 years in summer is the worst and the variability is the highest in the eight ages. The seasonal mean temperature in spring is the worst in the three ages, the variability is the biggest, the stability is the best in the five ages, and the variability is the smallest; (3) the annual mean temperature variability of Wuhan City from 1906 to 2015 is cyclical and the period of change is 30 years. It is predicted that the annual average temperature of Wuhan will stabilize in the next 10 years.

     

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