Uses SDO/HMI vector magnetograms to measure free energy proxies for each AR on the solar disk. The free energy proxies include the gradient of the magnetic field across the neutral line, the magnetic shear angle across the neutral line, and others. These free energy proxies are used to relate to historically derived event rates, and with Poisson statistics, probabilities of the occurrence of >M-class flares, >X-class flare, CMEs, Fast CMEs, and SPEs within the next 24 hours. To determine the optimal function relating solar eruption event rate and total non-potentiality of active regions, extensive data mining process was performed during MagPy training sessions to thousands of magnetic field threshold configurations in order to compare skill scores across the validation results to determine the best set of magnetic field thresholds for operational use.
MagPy utilizes a 45-heliocenteric degree cone filter to discard magnetograms on the limbs of the solar disk. These magnetograms, distorted by effects like foreshortening, engender high degrees of error in free-energy proxy calculations and spawn false neutral-lines. As these types of magnetograms can severely skew the correlation between the free energy proxies and event-rates, they are left out of the training dataset. MagPy is most accurate within a 45 degree cone from disk center.
HMI Line of sight (hmi.m_720s_nrt) HMI vector magnetograms (NRT CEA SHARP [hmi.sharp_cea_720s_nrt] and NRT CCD SHARP [hmi.sharp_720s_nrt]) NOAA SRS (solar region summery)
Full disk flare probabilities, full disk SEP probability, CME probability, and fast CME probability
Space Weather Impacts
- Ionosphere variability (navigation, communications)
- Solar energetic particles - SEPs (human exploration, aviation safety, aerospace assets functionality)
- Coronal Mass Ejections
- Solar Energetic Particles
- Solar Flares
- Prior Flaring as a Complement to Free Magnetic Energy for Forecasting Solar Eruptions
- MAG4 versus alternative techniques for forecasting active region flare productivity
- A tool for empirical forecasting of major flares, coronal mass ejections, and solar particle events from a proxy of active‐region free magnetic energy
Code Languages: Python
- Tilaye Tadesse, NASA JSC SRAG (Model Developer)
- Ian Fernandes, Princeton University (Model Developer)
- Sandro Taktakishvili, NASA GSFC CCMC (CCMC Model Host)
In addition to any model-specific policy, please refer to the General Publication Policy.