Nonlinear Time Series Analysis of Sunspot Data

TL;DR

This study analyzes sunspot number time series using the Hurst exponent to reveal varying persistence levels over different time scales, suggesting complex underlying dynamics similar to chaotic attractors.

Contribution

It applies R/S analysis to long-term sunspot data to identify multiple Hurst exponents, indicating complex, multi-scale persistence in solar activity.

Findings

Different Hurst exponents observed at various time scales

Presence of multiple centers of rotation akin to chaotic attractors

Sunspot data exhibit complex, multi-scale persistence

Abstract

This paper deals with the analysis of sunspot number time series using the Hurst exponent. We use the rescaled range (R/S) analysis to estimate the Hurst exponent for 259-year and 11360-year sunspot data. The results show a varying degree of persistence over shorter and longer time scales corresponding to distinct values of the Hurst exponent. We explain the presence of these multiple Hurst exponents by their resemblance to the deterministic chaotic attractors having multiple centers of rotation.