Researchers have developed a new tool that could be the first step toward predicting space weather weeks in advance rather than hours.
A space weather advance warning system developed by the National Science Foundation National Center for Atmospheric Research (NSF NCAR) and Southwest Research Institute (SwRI) could help government agencies and industry reduce impacts to GPS, power grids, astronaut safety, and more.
The tool, known as PINNBADS, advances a new generation of physics-based, AI-enabled prediction tools to better understand and predict extreme weather in space.
The growing threat of space weather
Space weather caused by solar flares and coronal mass ejections (CMEs) poses significant risks to our technology-dependent modern way of life.
When the sun explodes, it releases a large amount of charged particles and radiation. Once they reach Earth, they can cause geomagnetic storms and interfere with infrastructure in three main ways:
Power grid failures: Rapid changes in magnetic fields can induce excess current on long distance power lines, potentially blowing transformers and causing widespread and prolonged power outages. Satellite disruption: High-energy particles can destroy sensitive electronics on satellites, disrupting everything from GPS navigation to global telecommunications and weather forecasts. Radiation Hazards: Outside the protection of Earth’s atmosphere, astronauts are exposed to lethal doses of radiation. Even passengers on high-altitude polar flights can be exposed to increased radiation levels during severe solar events.
Early space weather warnings are important to protect infrastructure
PINNBADS bridges surface observations of solar active regions with deep solar magnetic dynamics to accurately deliver space weather forecasts in advance.
This can result in significantly longer expected lead times, which is important for protecting satellites, communications infrastructure, and future human space exploration.
“The subsurface conditions reconstructed from Pinbirds provide initial conditions for forward simulations of the solar magnetic evolution, opening the door to predicting weeks in advance when and where active regions producing large flares are likely to emerge,” said Mausmi Dikpati, NSF NCAR senior scientist who led the study.
Test tool accuracy with supercomputer simulations
The Derecho supercomputer at the NSF NCAR-Wyoming Supercomputer Center was used for simulations for the study, including code development, testing, and production execution.
Predict the sun’s next flare
This research was funded by NASA’s Heliophysics Guest Investigator Open (HGIO) program and the Consequences of Magnetic Fields and Flows in and Outside the Sun (COFFIES) DRIVE Center, a NASA-funded initiative.
“One of the goals of COFFIES is to predict when and where the sun will produce the next active region that will generate the largest flares,” said Todd Hoeksema, a professor at Stanford University and director of the COFFIES DRIVE Center.
“By combining physics-based modeling and AI, this research allows us to peer beneath the surface of the Sun and reconstruct the magnetic conditions that give rise to those regions.”
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