Study on the Temporal Evolution of the Radial Differential Rotation of Solar Corona Using Radio Emissions

TL;DR

This study analyzes 30 years of solar radio flux data to investigate the long-term radial differential rotation of the solar corona, revealing an increase in rotation rates with frequency and complex temporal variations with altitude.

Contribution

It applies Ensemble Empirical Mode Decomposition and wavelet analysis to long-term radio flux data to characterize the solar corona's differential rotation over multiple solar cycles.

Findings

Rotation rates increase with radio frequency.

Coronal rotation becomes gradually slower with increasing altitude.

EEMD effectively extracts rotation signals from noisy radio data.

Abstract

The daily measurements of the disc-integrated solar radio flux, observed by the Radio Solar Telescope Network (RSTN), at 245, 410, 610, 1415, 2695, 4995, and 8800 MHz during the time interval of 1989 January 1 to 2019 December 17, are used to investigate the temporal evolution of radial differential rotation of solar corona using the methods of Ensemble Empirical Mode Decomposition and wavelet analysis. Overall, the results reveal that over the 30-year period, the rotation rates for the observed solar radio flux within the frequency range of 245\textendash8800 MHz show an increase with frequency. This verifies the existence of the radial differential rotation of the solar corona over long timescales of nearly 3 solar cycles. Based on the radio emission mechanism, to some extent, the results can also serve as an indicator of how the rotation of the solar upper atmosphere varies with altitude within a specific range. From the temporal variation of rotation cycle lengths of radio flux, the coronal rotation at different altitudes from the low corona to approximately 1.3 $R_{\odot}$ exhibits complex temporal variations with the progression of the solar cycle. However, in this altitude range, over the past 30 years from 1989 to 2019, the coronal rotation consistently becomes gradually slower as the altitude increases. Finally, the EEMD method can extract rotation cycle signals from these highly randomized radio emissions, and so it can be used to investigate the rotation periods for the radio emissions at higher or lower frequencies.