Segmentation of photospheric magnetic elements corresponding to coronal features to understand the EUV and UV irradiance variability^⋆

¹ European Space Research and Technology Center (ESTEC), 2200 AG Noordwijk, The Netherlands
e-mail: Joe.Zender@esa.int
² Department of Physics and R&D Division, Vemana Institute of Technology, 560034 Bangalore, India
³ Department of Space and Plasma Physics, School of Electrical Engineering, Royal Institute of Technology KTH, 10044 Stockholm, Sweden
⁴ Julius-Maximilians-Universität Würzburg, Institut für Informatik, 97074 Würzburg, Germany
⁵ Royal Observatory of Belgium, Circular Avenue 3, 1180 Brussels, Belgium
⁶ LATMOS (Laboratoire Atmosphères, Milieux, Observations Spatiales), 11 boulevard d’Alembert, 78280 Guyancourt, France
⁷ Department of Physics, APS College of Engineering, 560082 Bangalore, India

Received: 18 October 2016
Accepted: 27 May 2017

Abstract

Context. The magnetic field plays a dominant role in the solar irradiance variability. Determining the contribution of various magnetic features to this variability is important in the context of heliospheric studies and Sun-Earth connection.

Aims. We studied the solar irradiance variability and its association with the underlying magnetic field for a period of five years (January 2011–January 2016). We used observations from the Large Yield Radiometer (LYRA), the Sun Watcher with Active Pixel System detector and Image Processing (SWAP) on board PROBA2, the Atmospheric Imaging Assembly (AIA), and the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO).

Methods. The Spatial Possibilistic Clustering Algorithm (SPoCA) is applied to the extreme ultraviolet (EUV) observations obtained from the AIA to segregate coronal features by creating segmentation maps of active regions (ARs), coronal holes (CHs) and the quiet sun (QS). Further, these maps are applied to the full-disk SWAP intensity images and the full-disk (FD) HMI line-of-sight (LOS) magnetograms to isolate the SWAP coronal features and photospheric magnetic counterparts, respectively. We then computed full-disk and feature-wise averages of EUV intensity and line of sight (LOS) magnetic flux density over ARs/CHs/QS/FD. The variability in these quantities is compared with that of LYRA irradiance values.

Results. Variations in the quantities resulting from the segmentation, namely the integrated intensity and the total magnetic flux density of ARs/CHs/QS/FD regions, are compared with the LYRA irradiance variations. We find that the EUV intensity over ARs/CHs/QS/FD is well correlated with the underlying magnetic field. In addition, variations in the full-disk integrated intensity and magnetic flux density values are correlated with the LYRA irradiance variations.

Conclusions. Using the segmented coronal features observed in the EUV wavelengths as proxies to isolate the underlying magnetic structures is demonstrated in this study. Sophisticated feature identification and segmentation tools are important in providing more insights into the role of various magnetic features in both the short- and long-term changes in the solar irradiance.