How IBM & NASA Predict Solar Weather & Protect Tech with AI

Space-based technologies can help to observe Earth, monitor energy use and provide early warnings for natural disasters. 

Solar flares and coronal mass ejections can knock out satellites, disrupt airline navigation and even trigger power blackouts.

IBM and NASA have created an open-source AI foundation model designed to understand high resolution solar observation data and predict how solar activity affects technologies. 

Named Surya, this tool aims to protect technologies from GPS navigation to power grids.

"Think of this as a weather forecast for space," explains Juan Bernabe-Moreno, Director of IBM Research Europe, UK 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 civilisation from the star that sustains us."

The Sun’s impact on Earth

Despite being 93 million miles away from Earth, the Sun’s flares and coronal mass ejections can have a big impact on technologies used daily. 

According to a systemic risk scenario created by Lloyd's, the global economy could be exposed to losses of US$2.4tn over a five year period, with the expected loss of US$17bn from the threat of a hypothetical solar storm.

A solar flare is a sudden, intense burst of electromagnetic radiation from the Sun’s atmosphere, typically triggered by the rapid release of magnetic energy near sunspots.

Intense X-rays and extreme ultraviolet radiation from flares can ionise Earth’s upper atmosphere, leading to radio communication blackouts and, sometimes, radiation storms that may affect satellites and astronauts.

Larger flares are sometimes associated with coronal mass ejections, large expulsions of plasma from the Sun’s outer atmosphere, which can trigger geomagnetic storms on Earth. 

Both solar flares and coronal mass ejections can cause severe disruptions to technologies both on Earth and in orbit, including damaging satellites with energetic particles and radiation or harming power grids with geomagnetic storms. 

Justina Nixon-Saintil, Vice President and Global Chief Impact Officer at IBM, said on LinkedIn: “Surya is part of the Prithvi family of models, which also includes geospatial and weather models, both of which we use in our IBM Impact Accelerator projects, supporting solutions in community resilience, agriculture and water management.

“These technologies depend on satellites, and those satellites depend on stable conditions in space.”

“Surya reflects our deep belief in open innovation and shared progress. 

“As environmental challenges grow more complex, we need tools that are accessible and grounded in science. 

“By anticipating the impact of solar activity, we help protect critical systems and build more resilient futures.”

How can Surya help?

Traditionally, solar weather prediction relies on partial satellite views of the Sun’s surface, making accurate forecasting difficult. 

NASA and IBM’s model is trained on the largest curated high resolution heliophysics dataset, designed to help researchers better study and evaluate space weather prediction tasks. 

Examples of these tasks, which Surya has been tested on, include predicting solar flares, the speed of solar winds, solar EUV spectra prediction and the emergence of active regions on the Sun.

IBM says that early testing has found a 16% improvement in solar flare classification accuracy and the ability to visually predict solar flares up to two hours ahead of them occurring. 

The model was trained on nine years of high-resolution solar observation data from NASA's Solar Dynamics Observatory with images that are 10 times larger than typical AI training data. 

A custom multi-architecture solution was created to handle this scale while maintaining efficiency. 

"We are advancing data-driven science by embedding NASA's deep scientific expertise into cutting-edge AI models," says Kevin Murphy, Chief Science Data Officer at NASA Headquarters in Washington. 

"By developing a foundation model trained on NASA's heliophysics data, we're making it easier to analyse the complexities of the Sun's behavior with unprecedented speed and precision. 

“This model empowers broader understanding of how solar activity impacts critical systems and technologies that we all rely on here on Earth."

IBM and NASA have released Surya on Hugging Face to democratise access to advanced tools and allow researchers to build on this foundation.