Speaker
Description
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 surface flux transport maps to model the evolution of magnetic concentrations such as Active Regions in 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 (AFT) 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 (e.g. 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. Concentrate on forecasts for limb- and beyond-limb regions that were nonetheless predicted to produce Earth-visible events, we demonstrate an enhanced capability for correct forecasts and fewer False Negatives (misses). As such, this 4pi framework mitigates a known shortcoming in operational flare forecasting, and establishes a framework for full-heliosphere forecasts of solar energetic events.
This project was funded NASA/SWR2O2R grant #80NSSC22K0273; the related paper is "under review" at the AGU journal Space Weather.
