Is there long-range memory in solar activity on time scales shorter than the sunspot period?
Martin Rypdal, Kristoffer Rypdal

TL;DR
This study investigates long-range memory in solar activity indicators like sunspot number and solar irradiance, finding strong persistence with a Hurst exponent around 0.7, but less persistence in solar flare activity.
Contribution
It introduces a stochastic model accounting for non-stationarity and biases in estimating long-range persistence in solar activity data.
Findings
Sunspot number and irradiance are likely long-range persistent with H~0.7.
Solar flare index shows weak or no persistence.
Bias correction improves Hurst exponent estimates.
Abstract
The sunspot number (SSN), the total solar irradiance (TSI), a TSI reconstruction, and the solar flare index (SFI), are analyzed for long-range persistence (LRP). Standard Hurst analysis yields , which suggests strong LRP. However, solar activity time series are non-stationary due to the almost periodic 11 year smooth component, and the analysis does not give the correct for the stochastic component. Better estimates are obtained by detrended fluctuations analysis (DFA), but estimates are biased and errors are large due to the short time records. These time series can be modeled as a stochastic process of the form , where is the smooth component, and is a stationary fractional noise with Hurst exponent . From ensembles of numerical solutions to the stochastic model, and application of Bayes' theorem, we can…
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