The sun is now being asked to file its own weather report
the sun is now being asked to file its own weather report: a machine learning model predicts the emergence of storm causing active regions up to 12 hours before they appear, an open source foundation model trained on 9 years of solar observatory data forecasts flares and winds, and an explainable language model now beats nasa's operational forecasting system.
the sun now files its own flare log.
Context
Space weather forecasting has long meant reacting to flares after they start. The three results move earlier in the chain. NASA's COFFIES team uses AI to predict where storm-causing active regions will emerge, up to 12 hours before they appear on the Sun's surface.
Surya is an open source foundation model for heliophysics from NASA and IBM, trained on years of Solar Dynamics Observatory data, with weights and code public. The third paper builds an operational flare forecasting system around an explainable large language model, which matters because forecasters need to see why a flare warning was issued.
Emergence prediction looks at what has not happened yet; a foundation model supports many tasks from one base; an explainable operational system targets trust and use. The sources describe three layers of the same problem, from physics to practice.
Related work
- NASA-IMPACT/Surya ↗Open code for the heliophysics foundation model.
- Surya-1.0 on Hugging Face ↗Public model weights.
- Solar Active Regions Emergence Prediction Using Long Short-Term Memory Networks (arXiv) ↗Earlier work on the emergence problem.
Watch next
- Independent scoring against operational forecasts over a full solar cycle phase, not a few months.
- Whether explainable outputs are accepted in real warning workflows.
Sources
Provenance
The note above is reproduced unedited from the original post, first published on Threads on 4 October 2026 at 15:57 IST. Sources are the papers and datasets the note draws on.
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