Authors: KD Leka (NWRA), Eric Wagner (NWRA), Sara Petty (NWRA), Kiran Jain (National Solar Observatories), Lisa Upton, Bibhuti Kumar Jha (SouthWest Research Institute), Kathryn Whitman (NASA/Space Radiation Analysis Group)

We present a 4-pi solar flare forecasting system developed under the NASA “Research-2-Operations” program.  We incorporate far-side helioseismic results (mapping the solar seismic signals to magnetic flux concentrations and their characteristics) as input to magnetic flux transport maps which model the evolution of magnetic concentrations such as Active Regions in the areas where data are not available for assimilation otherwise, e.g. the “unseen” (or un-seeable with today’s instruments) far-side hemisphere.  Specifically, for this proof-of-concept demonstration, we utilized an operationally-running improved helioseismic data pipeline from the Global Oscillations Network Group (GONG) and the Advective Flux Transport model, augmented with a new Active-Region identification and tracking system.  Significant infrastructure was needed to develop the ability to first evaluate and then ingest the far-side data, including addressing such mundane issues of active-region numbering (to which we suggest the need for a new system based not on assigned incremental numbering, but rather by Carrington-coordinates and time-of-detection).  Flare forecasts are then produced using the characteristics of the AFT-generated magnetic field of the identified active regions.

We utilize quantitative performance metrics from the NWRA Classification Infrastructure (NCI), the research arm of the Discriminant Analysis Flare Forecasting System [DAFFS, Leka+2018], to gauge any improvement gained by including this additional information.  Given the data available for validation, we concentrate on forecasts for limb- and beyond-limb regions that were nonetheless predicted to produce Earth-visible events.

Industry participation from NASA Johnson’s Space Radiation Analysis Group is guiding the effort.  NASA ROSES 21-SWR2O2R grant #80NSSC22K0273 funded this work; the related paper is “in submission” to the AGU journal Space Weather.