Real-time automated detection of coronal mass ejections using ground-based coronagraph instruments
Coronal mass ejections (CMEs) are dynamic events that eject magnetized plasma from the Sun’s corona into interplanetary space. CMEs are a major driver of solar energetic particle (SEP) events and geomagnetic storms. SEP events and geomagnetic storms pose hazards to astronauts, satellites, communication systems, and power grids. Understanding CME formation and predicting their impacts at Earth are primary goals of the National Space Weather program. St. Cyr et al. (2017) reported on the use of near real-time white light observations of the low corona from the COSMO K-Coronagraph (K- Cor) to provide an early warning of possible SEP events driven by fast CMEs. Following that work, one of us (Thompson) created a new CME detection algorithm adapted from the Solar Eruptive Event Detection System (SEEDS) code for use with K-Cor observations from the Mauna Loa Solar Observatory (MLSO) in Hawaii. We develop performance metrics and report on the success of the algorithm to detect CMEs in the 2017 K-Cor observations. Measures of success include the ability of the algorithm to detect an event and the amount of time between the event onset and its detection. The algorithm successfully detected 20 of the 35 CMEs identified between 1 Jan and 31 August, 2017 in the K-Cor data. There were 10 false positive events during this time period. The threshold for CME detection is discussed as a function of CME visibility, instrument background, and sky noise. The code has been modified to run in an automated mode and is in the process of being integrated into the real-time data processing pipeline at Mauna Loa. We report on current status, real-time alerts, and future upgrades.