Permutation entropy analysis of magnetic field turbulence at 1AU revisited

Abstract

Permutation entropy analysis is a relatively recent addition to the palette of techniques used to study spacecraft observations of heliospheric magnetic field fluctuations at Earth, allowing one to characterize the underlying processes driving the observed fluctuations. This study investigates the effects of data averaging, data gaps, and underlying periodicities on the results of such an analysis, utilizing synthetic data sets and thereby developing efficient treatments for each of these effects. Furthermore, WIND spacecraft observations are employed to validate the results of an earlier permutation entropy analysis by Weck et al. (2015, https://doi.org/10.1103/PhysRevE.91.023101), confirming the results of that study and showing how dat averaging effects can significantly affect the results so acquired. Lastly, as a novel application of this technique, Advanced Composition Explorer spacecraft data taken from 1998 to 2008 are analyzed to investigate whether the permutation entropy so calculated displays a solar cycle dependence. It is shown that although solar cycle dependencies have been reported for observed turbulence quantities such as the magnetic variance, there is no significant dependence discernible in the permutation entropy, and therefore in the underlying processes driving the turbulence