Solar Cycle Variability and Surface Differential Rotation from Ca II K-Line Time Series Data

TL;DR

This study analyzes over 36 years of solar Ca II K-line data to identify and characterize various components of solar variability, including the solar cycle, quasi-periodicities, stochastic processes, and differential rotation, revealing complex harmonic structures.

Contribution

It introduces a comprehensive analysis of long-term solar chromospheric data to detect differential rotation and complex periodicities, demonstrating potential applications to stellar light-curve analysis.

Findings

Identification of five components of solar variability.

Detection of differential rotation signatures.

Complex harmonic structures in solar activity signals.

Abstract

Analysis of over 36 years of time series data from the NSO/AFRL/Sac Peak K-line monitoring program elucidates five components of the variation of the seven measured chromospheric parameters: (a) the solar cycle (period ~ 11 years), (b) quasi-periodic variations (periods ~100 days), (c) a broad band stochastic process (wide range of periods), (d) rotational modulation, and (e) random observational errors, independent of (a)-(d). Correlation and power spectrum analyses elucidate periodic and aperiodic variation of these parameters. Time-frequency analysis illuminates periodic and quasi periodic signals, details of frequency modulation due to differential rotation, and in particular elucidates the rather complex harmonic structure (a) and (b) at time scales in the range ~0.1 - 10 years. These results using only full-disk data suggest that similar analyses will be useful at detecting and characterizing differential rotation in stars from stellar light-curves such as thosebeing produced by NASA's Kepler observatory. Component (c) consists of variations over a range of timescales, in the manner of a 1/f random process with a power-law slope index that varies in a systematic way. A time-dependent Wilson-Bappu effect appears to be present in the solar cycle variations (a), but not in the more rapid variations of the stochastic process (c). Component (d) characterizes differential rotation of the active regions. Component (e) is of course not characteristic of solar variability, but the fact that the observational errors are quite small greatly facilitates the analysis of the other components. The data analyzed in this paper can be found at the National Solar Observatory web site http://nsosp.nso.edu/cak_mon/, or by file transfer protocol at ftp://ftp.nso.edu/idl/cak.parameters