Periodicity of the solar radius revisited by using empirical mode decomposition and the Lomb–Scargle method

Abstract

Using the Hilbert-Huang transform and the Lomb-Scargle method, we investigate periodicities in the daily solar radius data during the time interval from February 1978 to October 1999 derived from Calern Observatory. The following prominent periods are found: (1) the rotation cycle signal; (2) several mid-term periods including 122, 162.9 and 225 days, annual-variation periodicities (319 and 359 days), quasi-triennial oscillations (3.46 and 3.94 years); (3) the 11-year Schwabe cycle, which is in anti-phase with solar activity. This result indicates that the strong magnetic field associated with the Sun has a greater inhibitive effect on the radius variation.

Empirical mode decomposition analysis of random processes in the solar atmosphere

“…This technique has already been successfully applied to solar signals. For example, anharmonic and multi-modal structures of solar QPP were revealed with EMD in Nakariakov et al (2010), Kolotkov et al (2015b), detailed two-dimensional information about a propagating and a standing wave in a coronal loop was obtained with EMD in Terradas et al (2004), periodicities associated with the 11 yr solar cycle were investigated with EMD in Kolotkov et al (2015a), Vecchio et al (2012), Zolotova & Ponyavin (2007), including revealing the periodicities in the variation of the solar radius (Qu et al 2015). Also, periodicity in the monthly occurrence numbers and monthly mean energy of coronal mass ejections was studied with EMD by Gao et al (2012).…”

Novel Data Analysis Techniques in Coronal Seismology

“…The use of EMD has also allowed for an advancement of our understanding of MHD waves and oscillations in solar coronal loops (Terradas et al, 2004) and at chromospheric and transition region heights (Narang et al, 2019) with typical periods of a few minutes, and for identification of quasi-periodic oscillatory modes in long-lived solar facular regions with periods ranging from several minutes to a few hours (Kolotkov et al, 2017;Strekalova et al, 2018). Oscillatory variabilities in the longer-term solar proxies with periods from about a month up to the entire solar cycle were found with EMD in 10.7 cm solar radio flux and sunspot records (Zolotova and Ponyavin, 2007;Mei et al, 2018), coronal Fe XIV emission (Deng et al, 2015), flare activity index and occurrence rate of coronal mass ejections (Deng et al, 2019;Gao et al, 2012), total and surface solar irradiance (Li et al, 2012;Lee et al, 2015;Bengulescu et al, 2018), helioseismic frequency shift (Kolotkov et al, 2015a), spatio-temporal dynamics of the solar magnetic field (Vecchio et al, 2012) and in the Sun-as-a-star observations of the solar mean magnetic field (Xiang and Qu, 2016), solar radius data (Qu et al, 2015), and also in direct numerical simulations of convection-driven dynamos (Käpylä et al, 2016).…”

Feature Extraction Algorithm Using a Correlation Coefficient Combined With the VMD and Its Application to the GPS and GRACE

“…The seasonal and trend-items can be obtained according to the above decomposition method. Then the Lomb Scargle (L-S) spectral analysis and energy density are used to obtain the trend-, seasonal, and residual items [38]- [39]. The extraction results are as follows:…”