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Researchers at Predictive Science have developed a model that uses measurements of the Sun’s changing magnetic field to predict solar eruptions in near real-time. By creating an automated process that converts raw data from the Solar Dynamics Observatory (SDO), they are able to show how magnetic flux and energy are injected into the corona over time. This dynamic element allows the corona to evolve and ultimately lead to solar eruptions.

In earlier iterations of the model, researchers had to manually analyze extreme ultraviolet activity to determine which areas of the Sun needed to be energized. However, this approach was not ideal for keeping up with the Sun’s ever-changing activity. By continuously updating the magnetic field, the team hopes to improve the accuracy of their predictions.

The team developed a software pipeline that identifies areas of the Sun that should be energized and fine-tunes the amount of energy to add to those areas. This updated approach allows for a more dynamic representation of the Sun’s activity, which is crucial during periods of heightened solar activity like the one currently being experienced. The team is optimistic about the results that this year’s model will provide and is confident in its ability to accurately predict solar eruptions.

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