An All-Clear Space Weather Forecasting System Based on Near Real Time Magnetograms

Large solar flares and coronal mass ejections (CMEs),drivers of severe space weather, are particularly difficult to forecast. NOAA presently uses the McIntosh Active region category system, a qualitativepredictive system... [ view full abstract ]

Large solar flares and coronal mass ejections (CMEs),drivers of severe space weather, are particularly difficult to forecast. NOAA presently uses the McIntosh Active region category system, a qualitativepredictive system largely based on historical data but adjustable by theuser.  Marshall Space Flight Center (MSFC) has developed a forecastingtool called MAG4 (Magnetogram Forecast) that provides more quantitativemeasurements of CMEs that could potentially be used as a complement to currentoperational products.  MAG4 assumes that flares and CMEs are explosivereleases of energy stored in the solar coronal magnetic field, and thus activeregions that have more free energy are more likely to produce flares andCMEs.  Since free energy cannot be directly measured, MAG4 uses a proxy ofthe active region magnetic free energy, and forecasts an event ratebased on this proxy.  Forecasts are given as probability measures orexpected rates for a given event (flares, CMEs, or Solar Proton Events(SPEs)).   No time or magnitude predictions are given; such dataremain beyond present capabilities.

MAG4 is being transitioned to use vector magnetograms forwhich the free-energy proxy can be measured more accurately, and further fromdisk center.  MAG4 forecasts are further refined using recent flareactivity.  We are investigating other ways to improve forecasting by usingadditional parameters and are engaging with a research-to-operations groupwithin the MSFC Science Research and Projects Division to encourage partnershipwith operational forecasters.

Acknowledgements:  MAG4 development at Marshall iscurrently being supported by NASA’s Game Changing DevelopmentProgram.   Part of this work is supported by the National ScienceFoundation under Grant No. AGS-1601926.