Automatic Recognition of Solar Active Regions Based on Real-time SDO/HMI Full-disk Magnetograms

Abstract

Solar Active Regions (ARs) are the main source regions of solar activities. The morphology, structure, and characteristic of ARs are important factors in determining solar eruptions. Therefore, the recognition of ARs is the precondition to predict solar eruptions. SDO/HMI can continuously provide full-disk photospheric images with high temporal and spatial resolution. Referring to the method of Zhang et al.[1], we performed a study of fast automatic recognition of ARs from full-disk HMI magnetograms, which involves the intensity-based thresholding, mathematical morphological analysis and region growing. Through comparing the automatic recognition ARs with the ARs compiled by NOAA/SWPC from 2010 May to 2018 December, it is found that the number of ARs recognized automatically and the number of SWPC ARs are basically consistent in the trend of variation, and their correlation coefficient is 0.87. The total number of ARs automatically recognized is slightly less than the number of SWPC ARs. Most of the unidentified ARs are small areas, weak magnetic fields and simple magnetic structures, which are highly impossible to produce powerful eruptions to affect the space environment. This method of the automatic AR recognition from real-time HMI full-disk magnetograms can directly provide the real-time AR data for forecasting solar eruptions, and accelerate the operational application of solar eruption prediction models.