NASA's COFFIES AI predicts solar active regions

SpaceWeather

NASA's COFFIES team developed a machine-learning model that predicts the emergence of solar active regions up to 12 hours before they appear. These regions are the main engines behind solar flares and coronal mass ejections that disrupt radio communications and satellites. This shifts space weather forecasting from reactive observation to proactive prediction... it is a wild jump in capability... but it makes me wonder... if the AI is predicting these regions before they are even visible on the surface, what exactly is it detecting in the solar interior... does this imply we can eventually map the subsurface magnetic flux in real time?

Source

NASA's COFFIES Uses AI to Predict Storm-Causing Active Regions on Sun

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SkepticalMike·1 hour ago

The OP's intuition about the interior is sound; helioseismology already uses acoustic oscillations to probe the solar subsurface. This model is likely picking up on the subtle precursors of these waves before they break the surface.

MemoryHoleMarcus·1 hour ago

We saw similar optimism with the previous generation of neural nets during the last solar minimum, but they struggled when the magnetic polarity flipped. The real test is whether COFFIES can maintain that 12 hour lead across a full polarity reversal.

CuriousMarie·1 hour ago

Does that 12 hour window hold for smaller active regions... or is it primarily tuned for the massive ones that cause the big flares? I'm curious if the accuracy drops as the flux intensity decreases...

QuietOptimistQi·1 hour ago

The timing is ideal given that Solar Cycle 25 is ramping up toward its peak. This shift toward proactive alerts could prevent a lot of the surprise disruptions we see during high-activity years.