LYAPUNOV EXPONENT AND CORRELATION DIMENSION ANALYSIS OF TIME SERIES DATA OF ATMOSPHERIC TEMPERATURE

Kamad Nath Shandilya1, Satish Kumar2, Supriya Rani3 & Sumita Singh4

Abstract

Calculations of Lyapunov exponent and correlation dimension are popular methods to identify chaotic behavior of a nonlinear dynamical system. In these methods time series data of a single dynamical variable of the system is used. Here we have taken atmosphere as a nonlinear dynamical system and atmospheric temperature as a single dynamical variable. The objective of this study is to analyze chaotic behavior of time series data of daily atmospheric temperature of Delhi during dry season from 1995 to 2019. We have calculated the positive value of Lyapunov exponent and non-integral value of correlation dimensions 0.000397& 0.90860 respectively, which indicates the presence of chaotic behavior in the atmosphere. This study would help us in analyzing the chaotic nature of atmosphere based on temperatures well as other nonlinear dynamical variables existing in atmosphere.

Keywords:

:Nonlinear Dynamics, Chaos, Attractor, Lyapunov Exponent, Correlation Dimension, Time series data


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References


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