AI Model Detects Solar Storm Warning Signs Hours in Advance
Scientists have developed an artificial intelligence system that can detect solar storm warning signs nearly nine hours before the underlying activity becomes visible on the Sun’s surface, a breakthrough that could eventually give satellite operators and power grid companies precious extra time to prepare for incoming space weather. The model, called EarlyDetect, comes from a […]
Scientists have created an artificial intelligence model called EarlyDetect capable of identifying solar storm warning signals nearly nine hours ahead of their appearance on the Sun's surface, potentially providing valuable time for satellite operators and power grid companies to prepare. The breakthrough, published in the Journal of Geophysical Research: Machine Learning and Computation, comes from a research team led by the New Jersey Institute of Technology.
Traditional observation methods struggle to detect early changes in solar activity due to their faint and subtle nature. EarlyDetect uses a Transformer architecture to analyze acoustic activity within the Sun's interior and magnetic field measurements from NASA's Solar Dynamics Observatory. By processing unfiltered data without noise reduction, the model can detect precursor patterns up to 9.24 hours before active regions become visible, outperforming other methods.
However, the model still generates false alarms and cannot guarantee a solar flare or coronal mass ejection will occur, requiring further testing before potential operational use.
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