沈阳农业大学学报2018，Vol.49Issue(1)：82-87,6.DOI:10.3969/j.issn.1000-1700.2018.01.012
基于分数阶导数的天气和气候要素时间序列关系分析
Analysis on the Relationship between the Time Series of Weather and Climate Factors based on Fractional Derivative
摘要
Abstract
Research on characteristics of time series of weather and climate factors and theirrelationship will improve our understanding on effect of weather and climate extreme events, and willenhance our abilityon simulation and prediction of weather and climate extreme events. In this paper, the average air temperature anomaly time series with different time scales(daily, monthly and yearly scales) from 1951 to 2010 in Shenyang city were selected,which represents the time series of weather and climate factors. The characteristics of autocorrelation and long-trail probability distribution for these time series was analyzed by using the autocorrelation function and the normalized probability density function. Furthermore, thefractional derivative relationships between monthly, yearly average air temperature anomaly and daily average air temperature anomaly were established by using second order structure function,i.e., the fractional order derivative relationship between the time series of climate and weather factors. The results showed that the time series of daily, monthly, and yearly average air temperature anomaly in Shenyang city presented the characteristics of non-memory, short-term memory and long-term memory, respectively. The normalized probability function of yearlyaverage air temperature anomaly series showed obvious long-tail trait, compared to that of daily and monthly air average temperature anomaly series. Which means that the probability of climate extreme events is greater than that of weather extreme events.These results suggested that there were fractional derivative relationships between the monthly, yearlyaverage air temperature anomaly series (time series of climate elements)and daily average air temperature anomaly series (time series of weather elements), the calculated order ofderivative were 0.524 and 0.83,respectively.关键词
天气和气候/分数阶导数/气候的记忆性/极值事件Key words
weather and climate/fractional derivative/memory of climate/extreme event分类
农业科技引用本文复制引用
黄荟羽,张琳,王若男,宫诏健,李大为,刘利民..基于分数阶导数的天气和气候要素时间序列关系分析[J].沈阳农业大学学报,2018,49(1):82-87,6.基金项目
国家自然科学基金项目(31201124) （31201124）
中国科学院战略性先导科技专项项目(XDA05050601) （XDA05050601）
