气温的天气和气候记忆性特征分析:以济南和青岛为例

气温的天气和气候记忆性特征分析对于提高气候预测水平具有积极意义。利用济南和青岛1961—2020 年逐日、月和年平均气温资料,运用自相关性函数和标准化频率分布分析了上述时间序列的气温记忆性特征和概率分布特征,并利用结构函数法建立了月、年平均气温距平与日平均气温距平之间的分数阶导数关系。结果表明:(1)济南和青岛的月、年平均气温距平呈现不同程度的记忆性特征,其中年平均气温距平相比于月平均气温距平具有更好的记忆性。(2)济南和青岛的月、年平均气温距平与日平均气温距平之间存在分数阶导数关系,济南和青岛相应的月、年尺度阶数分别为0. 529、0. 665 和0. 553、0. 791,两地的月尺度阶数相近,但青岛略大,青岛的年尺度阶数大于济南,即青岛月和年平均气温距平的记忆性大于济南。(3)济南和青岛的月和年平均气温距平相比于日平均气温距平有不同程度的长尾特征,长尾特征反映了极值温度发生的概率。

Characteristic analysis of weather and climate memory in temperature: taking Jinan and Qingdao as examples

Analyzing the characteristics of weather and climate memory in temperature has positive significance for improving climate prediction. Based on the daily,monthly,and annual mean temperature data from 1961 to 2020 in Jinan and Qingdao,the characteristics of temperature memory and probability distribution for these time series are analyzed by using autocorrelation function and normalized frequency distribution. And the fractional derivative relationships between monthly / annual mean temperature anomaly and daily mean temperature anomaly are established by using structure function. The results are as follows. (1)The monthly and annual mean temperature anomalies in Jinan and Qingdao show different degrees of memory characteristics,and the annual mean temperature anomaly has better memory than the monthly mean temperature anomaly. (2)There are fractional derivative relationships between monthly / annual mean temperature anomaly and daily mean temperature anomaly both in Jinan and Qingdao. The corresponding derivative orders on monthly and annual scales are 0. 529 and 0. 665 in Jinan,while 0. 553 and 0. 791 in Qingdao,respectively. On the monthly scale,the derivative orders in Jinan and Qingdao are similar with the value in Qingdao slightly larger,while the derivative order on the annual scale in Qingdao is larger than that in Jinan,namely the memory of monthly and annual mean temperature anomalies in Qingdao is better than that in Jinan. (3)Compared with the daily mean temperature anomaly,the monthly and annual mean temperature anomalies in Jinan and Qingdao have different degrees of long-tail characteristics,which reflect the probability of extreme temperature.