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

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 features in the solar magnetosphere, chromosphere, and corona.  We studied the variability of solar irradiance for a period of 10 years (May 2010–January 2020) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, the Atmospheric Imaging Assembly (AIA), and the Helioseismic and Magnetic Imager (HMI) of on board the Solar Dynamics Observatory (SDO), and applied a linear model between the identified features and the measured solar irradiance by LYRA.

We used the spatial possibilistic clustering algorithm (SPoCA) to identify coronal holes, and a morphological feature detection algorithm to identify active regions (AR), coronal bright points (BPS), and the quite sun (QS) and segment coronal features from the EUV observations of AIA. The AIA segmentation maps were then applied on SWAP images, images of all AIA wavelengths, HMI line-of-sight (LOS) magnetograms, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/BPs/QS features were computed and compared with LYRA irradiance measurements as a proxy for ultraviolet irradiation incident to the Earth atmosphere.

We modelled the relation between the solar disk features (ARs, CHs, BPs, and QS) applied to magnetrogram and EUV images against the solar irradiance as measured by LYRA and the F10.7 radio flux. To avoid correlation between different the segmented features, a principal component analysis (PCM) was done. Using the independent component, a straightforward linear model was used and corresponding coefficients computed using the Bayesian framework. The model selected is stable and coefficients converge well.

The application of the model to data from 2010 to 2020 indicates that both at solar cycle timeframes as well as shorter timeframes, the active region influence the EUV irradiance as measured at Earth. Our model replicates the LYRA measured irradiance well.