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

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