Fractality and singularity in CME linear speed signal: Cycle 23

A Chattopadhyay, MH Khondekar… - Chaos, Solitons & …, 2018 - Elsevier
Chaos, Solitons & Fractals, 2018Elsevier
In the recent past, coronal mass ejection (CME) has received much research attention for its
geo-effectiveness. In this paper, an investigation has been made to identify the scaling
pattern of the CME linear speed time series data (February 1999 to December 2007 of solar
cycle 23) collected from the Solar and Heliospheric Observatory (SOHO) using Multi-Fractal
Detrended Fluctuation Analysis (MFDFA) and Multi-Fractal Detrended Moving Average
(MFDMA) method. The scaling exponent, generalized Hurst exponent, singularity strength …
Abstract
In the recent past, coronal mass ejection (CME) has received much research attention for its geo-effectiveness. In this paper, an investigation has been made to identify the scaling pattern of the CME linear speed time series data (February 1999 to December 2007 of solar cycle 23) collected from the Solar and Heliospheric Observatory (SOHO) using Multi-Fractal Detrended Fluctuation Analysis (MFDFA) and Multi-Fractal Detrended Moving Average (MFDMA) method. The scaling exponent, generalized Hurst exponent, singularity strength and also the singularity spectrum have been computed to quantify the multifractality and to identify the singularities of the time series data. An effort has also been made to find out the possible sources which are responsible for the multifractality in the signal by studying the scaling patterns of the shuffled and surrogate version of the original data. It has been revealed in this paper that CME linear speed signal exhibit multifractal behaviour with long-term persistence. Both the long-range temporal correlation and the broad probability density function (pdf) are found to be the primary source of multifractality in the signal. The singularities or abruptness present in the signal are found to vary with time, and this fluctuation follows an AR (2) model.
Elsevier
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