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MagPy (v2)Model DescriptionUses 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. Model Figure(s) :Model Inputs DescriptionHMI 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) Model Outputs DescriptionFull disk flare probabilities, full disk SEP probability, CME probability, and fast CME probability Model CaveatsMagPy 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. Change LogModel Acknowledgement/Publication Policy (if any)Model Domains:SolarSpace Weather Impacts:Ionosphere variability (navigation, communications)Solar energetic particles - SEPs (human exploration, aviation safety, aerospace assets functionality) Phenomena :Coronal_Mass_EjectionsSolar_Energetic_Particles Solar_Flares Simulation Type(s):EmpiricalTemporal Dependence Possible? (whether the code results depend on physical time?)falseModel is available at?CCMCSource code of the model is publicly available?falseCCMC Model Status (e.g. onboarding, use in production, retired, only hosting output, only source is available):productionCode Language:PythonRegions (this is automatically mapped based on model domain):SunContacts :Tilaye.Tadesse, ModelDeveloperIan.Fernandes, ModelDeveloper Sandro.Taktakishvili, ModelHostContact Acknowledgement/Institution :Princeton UniversityRelevant Links :Publications :Model Access Information :Access URL: https://sep.ccmc.gsfc.nasa.gov/probability/Access URL Name: Continuous/RT Run (SEP Scoreboard Probability) Repository ID: spase://CCMC/Repository/NASA/GSFC/CCMC Availability: online AccessRights: OPEN Format: HTML Encoding: None Access URL: https://iswa.gsfc.nasa.gov/iswa_data_tree/model/solar/MagPy/2.X/ Access URL Name: Continuous/RT Run (ISWA data tree) Repository ID: spase://CCMC/Repository/NASA/GSFC/CCMC Availability: online AccessRights: OPEN Format: HTML Encoding: None Linked to Other Spase Resource(s) (example: another SimulationModel) :spase://CCMC/SimulationModel/MAG4/v20190904 |
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