Segmentation of coronal features to understand the solar EUV and UV irradiance variability

Abstract

Context. The study of solar irradiance variability is of great importance in heliophysics, the Earth's climate, and space weather applications. These studies require careful identifying, tracking and monitoring of active regions (ARs), coronal holes (CHs), and the quiet Sun (QS). Aims. We studied the variability of solar irradiance for a period of two years (January 2011-December 2012) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). Methods. We used the spatial possibilistic clustering algorithm (SPoCA) to identify and segment coronal features from the EUV observations of AIA. The AIA segmentation maps were then applied on SWAP images, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/QS features were computed and compared with the full-disk integrated intensity and LYRA irradiance measurements. Results. We report the results obtained from SDO/AIA and PROBA2/SWAP images taken from January 2011 to December 2012 and compare the resulting integrated full-disk intensity with PROBA2/LYRA irradiance. We determine the contributions of the segmented features to EUV and UV irradiance variations. The variations of the parameters resulting from the segmentation, namely the area, integrated intensity, and relative contribution to the solar irradiance, are compared with LYRA irradiance. We find that the active regions have a great impact on the irradiance fluctuations. In the EUV passbands considered in this study, the QS is the greatest contributor to the solar irradiance, with up to 63% of total intensity values. Active regions, on the other hand, contribute to about 10%, and off-limb structures to about 24%. We also find that the area of the features is highly variable suggesting that their area has to be taken into account in irradiance models, in addition to their intensity variations. Conclusions. We successfully show that the feature extraction allows us to use EUV telescopes to measure irradiance fluctuations and to quantify the contribution of each part to the EUV spectral solar irradiance observed with a calibrated radiometer. This study also shows that SPoCA is viable, and that the segmentation of images can be a useful tool. We also provide the measurement correlation between SWAP and AIA during this analysis.

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

“…In our previous paper, Kumara et al (2014), we described the details of all the instruments, calibration of data, degradation of instruments, and the SPoCA. We also explained the observational details and procedure applied to segment the coronal features (ARs/CHs/QS/FD) for the period January 2011 to December 2012.…”

“…Our objective in this study is the practical conversion of solar intensity and magnetic field images into physically interpretable quantities describing the solar magnetic cycle and its consequences on the radiative output of the Sun. We have used the Spatial Possibilistic Clustering Algorithm (SPoCA; Barra et al 2008Barra et al , 2009Verbeeck et al 2014;Kumara et al 2014), which is an image segmentation algorithm that allows the separation of solar intensity images and magnetograms into three characteristic structures on the Sun: active regions (ARs), coronal holes (CHs), and quiet sun (QS) (Kumara et al 2014). Understanding the EUV and UV irradiance variability from spatially resolved intensity and magnetic field observations is an important issue in space weather and climate applications.…”

Temporal Variation of Ca–K Line Profile of the Sun during the Solar Cycle 22 and 23

“…The boundaries of networks coincide with the boundaries of large convective cells seen in Dopplar-grams (Leighton 1959;Leighton et al 1962) and the contribution to the solar irradiance due to networks vary by few percent with the solar cycle phase (Worden et al 1998). Quiet Sun (QS) identified by Kumara et al (2014) represents solar corona and is the greatest contributor to solar irradiance with up to 63% in the EUV spectral irradiance in terms of intensity. The active regions contribute by about 10% and off-limb features about 24%.…”

“…Kariyappa and Pap (1996) reported that the variation in spatial index and full width half maximum (FWHM) of the intensity distribution of the chromospheric features such as plages and networks as observed from Ca-K spectroheliograms representing the activity agrees with the UV irradiance measured in MgII h and K lines. Further, Verbeeck et al (2014) and Kumara et al (2014) used segmentation method to identify the active regions, coronal holes and Quiescent Sun (QS) to study the UV and EUV variability of the Sun. Identified active regions are likely to have resemblance with Ca-K plages.…”

“…The Ca-K index varies by about 18% during the solar cycle (White & Livingston 1981) and the amplitude of total irradiance variation measured radiometrically between minimum and maximum is only ∼0.1% (Fröhlich & Lean 1998). The observations made during the period of 1981 to 1985 shows that the contribution of the UV part of the spectrum to the total solar irradiance (TSI) is 19% (Lean 1989). The large variations in solar irradiance observed during maximum phase could be caused by the faculae brightness over large areas, which compensates the less radiation emitted from sunspot areas (Froehlich et al 1991;Pap et al 1997).…”