一维气候时间序列的李亚普诺夫指数所显示的动态系统的演化特征

EVOLUTIONAL FEATURES OF A DYNAMIC SYSTEM DISPLAYED BY LYAPUNOV EXPONENTS IN A 1-DIMENSIONAL CLIMATGLOGICAL TIME SERIES

摘要:

本文利用广州1873—1980年共108年的月平均气温时间序列资料,在拓展了的三维相空间中,用Wolf的方法,求出了在不同参数条件下的李亚普诺夫指数λ₁。从中发现,对每一组参数,均得到λ_1,2>0（其中λ₁>λ₂）,λ₃<0。这说明我国季风区短期气候演化存在着浑沌吸引子,因而气候应该分享经历着浑沌力学行为的体系所具有的那种本征的演化特征。

Abstract:

Based on Guangzhou 1873-1980 monthly mean temperature time series in an extended 3-D phase space, Lyapunov exponent λ1 is calculated for different parameters following the method in Wolf et al. (1985). Results show that for each set of parameters λ_1,2>0 (where λ₁>λ₂) and λ₃ < 0 are acquired. Our further investigation indicates that chaotic attractors exist in the short-range evolution in the climate of China's monsoon area, in good agreement with the fractional dimensios obtained by calculating the same data (peng et al. , 1989), and thereby it is shown that climate is supposed to share characteristic evolutional features typical of a system experincing behavior of chaotic mechanics.