Study of nonlinear time series and wavelet power spectrum analysis using solar wind parameters and geomagnetic indices

Abstract

ABSTRACT We investigate the time series of solar wind parameters (interplanetary magnetic field, Bz and solar wind speed, Vx) and geomagnetic indices (disturbance storm time, Dst and auroral electrojet, AE) using wavelet analysis and nonlinear dynamics time series techniques. The data were collected from the Flight Center Space Physics Data Facility (GSFC/SPDF) OMNIWEB interface between 2008 and 2017. Wavelet power spectrum (WPS) analysis assists in breaking down the time series of Bz, Vx, Dst and AE parameters into different scales. It was noted that there is a greater concentration of power between the 512 and 1024 months bands across the Bz, Vx, Dst and AE parameters. We also applied non-linear time series modelling methods to examine the Bz, Vx, Dst and AE parameters. We utilised both the time delay and embedded dimension in computing average mutual information (AMI) and false nearest neighbors (FNN), respectively. The Lyapunov exponent (LE) is used to express the complexity of the nonlinear dynamics based on embedding parameters. The Lyapunov exponents depict positive values which confirm that the complex solar wind parameters and the geomagnetic indices are deterministic chaotic systems. The results show noticeable chaotic characteristics in the Bz, Vx, Dst and AE parameters.