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The AI system, developed by Sabrina Guastavino and her team, successfully predicted an X8.7-class solar flare and provided an accurate forecast of the storm’s impact on Earth.
The scientists analysed data from the May 2024 Solar Storm. (Photo Credit: X)
As artificial Intelligence continues to break new boundaries, a recent study has claimed the system could be used to forecast space weather more accurately than traditional methods. While analysing historical data alongside real-time sensor information, AI can assist in predicting geomagnetic storms that could affect the Earth’s satellite systems and power grids. A team of researchers, led by Sabrina Guastavino at the University of Genoa, incorporated the technology to evaluate past solar storms.
The scientists took data from the most recent phenomenon from May 2024 and the AI model successfully predicted solar flares and coronal mass ejections (CMEs) quite precisely. The AI system identified patterns in solar activity that were mostly challenging to spot with traditional equipment.
The Sun may seem calm from a distance, but its behaviour is far from predictable. Being an ever-changing sphere of plasma, its activity varies constantly. Among the most intense phenomena are solar storms, which can have significant impacts on Earth’s atmosphere while also affecting technological systems.
One such event, known as CME, involves massive eruptions that release large amounts of charged particles into space. When they reach the Earth’s surface, those particles can cause major disruptions to satellites, GPS networks and power grids, posing considerable risks to modern infrastructure. The unpredictable nature of the sun makes it challenging to prepare for these hazardous natural events.
The AI system, developed by Sabrina Guastavino and her team, successfully predicted an X8.7-class solar flare and provided an accurate forecast of the storm’s impact on Earth. Its forecasts were notably a lot more accurate than those generated by conventional methods.
“The May 2024 event also underscores the broader implications of AI-driven reverse engineering for space weather science. The ability to predict CME travel times with such precision suggests that AI can furthermore serve as a diagnostic tool for testing and refining existing models of CME propagation,” claimed the study.
This level of accuracy could greatly improve early warning systems for critical infrastructure, such as satellite operation and power grids, enabling more time to prepare for space weather disruptions. Additionally, more reliable forecasts could aid in predicting auroral displays, benefiting sky-watchers and researchers alike.
Experts further believe that AI has the potential to revolutionise space weather forecasting by offering more effective suggestions to protect the Earth’s technology and environment from the impacts of future solar storms.
