IBM and NASA are unveiling the most advanced open-source foundation model designed to understand high resolution solar observation data and predict how solar activity affects Earth and space-based technology.
Surya, named for the Sanskrit word for the Sun, represents a significant advancement in applying AI to solar image interpretation and space weather forecasting research, providing a novel tool to help protect everything from GPS navigation to power grids to telecommunications.
The Sun may be 93 million miles away, but its impact on modern life is immediate and growing. Solar flares and coronal mass ejections can knock out satellites, disrupt airline navigation, trigger power blackouts, and pose serious radiation risks to astronauts. With humanity's increasing dependence on space-based technology and plans for deeper space exploration, accurate solar weather prediction has become critical.
The effects of solar storms can cause:
- Damage to satellites, spacecraft and/or astronauts that are stationed beyond Earth
- Loss of satellite hardware, damaging solar panels and circuits
- Impact to airline travel, due to navigational errors and potential risk of radiation for airline crew and passengers
- Lowered food production as agriculture can be impacted by disrupted GPS navigation
The implications include both academic research and operational preparedness. The new model will provide tools to help experts plan for solar storms, which can disrupt the Earth's technological infrastructure, according to IBM.
"Think of this as a weather forecast for space," said Juan Bernabe-Moreno, director of IBM Research Europe, U.K. and Ireland. "Just as we work to prepare for hazardous weather events, we need to do the same for solar storms. Surya gives us unprecedented capability to anticipate what's coming and is not just a technological achievement, but a critical step toward protecting our technological civilization from the star that sustains us."
Traditional solar weather prediction relies on partial satellite views of the Sun's surface, historically making accurate forecasting extremely difficult. Surya addresses this typical limitation by training on the largest curated high resolution heliophysics dataset.
This dataset is designed to help researchers better study and evaluate critical space weather prediction tasks.
In addition to the binary solar flare classification task, Surya is built to visually predict solar flares for the first time, providing a high resolution image of where the flare is predicted to occur up to two hours out.
Surya is part of a broader effort at IBM to embrace generative and automated approaches that empower algorithms to be discovered, tested, and evolved at scale. Surya is one example of how IBM is positioning AI not just as a tool, but as a driver of scientific discovery.
By releasing Surya on Hugging Face, IBM and NASA are democratizing access to advanced tools for understanding and forecasting solar weather and scientific exploration. Researchers worldwide can now build upon this foundation to develop specialized applications for their regions and industries, according to IBM and NASA.
This model is part of a larger collaboration between IBM and NASA to use AI technology to explore the planet and solar system. It joins the Prithvi family of foundation models, which includes a geospatial model and a weather model.
Last year, IBM and NASA released the Prithvi weather model on Hugging Face for scientists and the broader community to develop short- and long-term weather and climate projections.
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