Identification of large-scale cellular structures on the Sun based on the SDO and PSPT data

TL;DR

This study analyzes multi-instrument solar data to identify and characterize large-scale cellular structures on the Sun's photosphere, bridging the scale gap between supergranules and giant cells.

Contribution

It introduces a method combining 2D power spectra, Fourier analysis, and wavelet transforms to reliably detect cellular structures at ~300 arcsec scale.

Findings

Identified cellular structures at ~300 arcsec scale on the solar photosphere.

Demonstrated the effectiveness of combined spectral and wavelet analysis.

Provided insights into the spatial organization of solar surface features.

Abstract

Three independent sets of data: i). series of filtergrams obtained in line CaII K (393.416 nm) with the ground-based telescope Precision Solar Photometric Telescope (PSPT) of Mauna Loa Solar Observatory; ii). series of filtergrams of Atmospheric Imaging Assembly (AIA) of the Solar Dynamics Observatory (SDO) in {\lambda}160 nm and iii). series of magnetograms of Helioseismic and Magnetic Imager (HMI) of SDO have been processed to reveal reliably the existence of spatial cellular structures on the solar photosphere at scale about of 300 arcsec. This scale is intermediate between supergranules and giant cells (~30,000 and ~300,000 kilometers across, respectively). To identify the different spatial structures the tens of two-dimensional power spectra (2DFFT) have been averaged. For one-dimensional photometric cross sections of frames, the Fourier power spectra (FFT) and wavelet transforms (Morlet 5-th order) have been calculated.