NASA and IBM Unveil Surya: An AI Model for Predicting Solar Weather

NASA and IBM built an AI to predict solar flares before they hit Earth

An AI model trained on years of data from NASA's Solar Dynamics Observatory can predict the sun's future appearance and potentially flag dangerous solar flares An artificial intelligence model trained on NASA satellite imagery can forecast what the sun will look like hours into the future - even predicting the appearance of solar flares that may warn of dangerous space weather for Earth. "I love to think of this model as an AI telescope where you can look at the sun and you can understand the moods," says Juan Bernabé-Moreno at IBM Research Europe. The sun's moods matter because outbursts of solar activity can bombard Earth with high-energy particles, X-rays and extreme ultraviolet radiation. These can disrupt GPS and communications satellites, and potentially harm astronauts and even people on commercial airlines. Solar flares can be followed by coronal mass ejections, which may disrupt Earth's own magnetic field and create geomagnetic storms capable of knocking out power grids. Bernabé-Moreno and his colleagues at IBM and NASA trained an AI model called Surya, after the Sanskrit word for sun, on nine years of data from NASA's Solar Dynamics Observatory. The satellite captures ultra-high-resolution images of the sun in 13 different wavelengths. The AI model learned to identify patterns in the visual data and generate images of what the sun would look like from the observatory's point of view in the future. When tested on historical solar flare data, the Surya model predicted the occurrence of a solar flare within the next day with 16 per cent better accuracy than a standard machine learning model. It could also generate the visual image of a flare the observatory would see up to two hours in the future. "The power of AI is that it has the ability to learn the physics in a more roundabout way - it kind of develops an intuition for how the physics works," says Lisa Upton at Southwest Research Institute in Colorado. Upton says she is especially interested in whether the Surya model can help predict solar activity on the far side of the sun and at the poles, where NASA's scientific instruments can't make direct observations. Surya does not explicitly attempt to model the far side of the sun, but it has still proven successful in predicting how the sun will look several hours in the future, when part of the far side has rotated into view, says Bernabé-Moreno. But it is unclear if the AI model can address existing challenges in predicting exactly how solar activity may impact Earth, says Bernard Jackson at the University of California, San Diego. That is because there is currently no way to directly observe the magnetic field configurations between the sun and Earth, which is what determines the paths of the high-energy particles travelling outward from our star. Bernabé-Moreno says the model is currently intended for use by scientists, but future integrations with other AI systems that can harness Surya's capabilities to answer basic questions about future solar activity might make it more accessible to power grid operators or satellite constellation owners as part of an early warning system.

IBM and NASA made an open-source AI model for predicting solar weather

Last year, the most powerful geomagnetic storm in 20 years . It produced stunning aurora displays in parts of the US that are normally too far south to see them. Normally, such storms are a headache for energy providers. In 1989, for example, the Canadian province of blackout following a series of plasma ejections from the Sun. This time around, power companies were better prepared, and in the US and Canada, there weren't significant service disruptions. The episode highlighted the value of proper preparation against geomagnetic storms, and for the past couple of years, NASA and IBM have been working to give the scientific community and others a better way to predict solar weather. Today, they're releasing the result of their work, an open-source foundation model called Surya. Named after the Sanskrit word for the Sun, Juan Bernabe-Moreno, director of IBM Research Europe, UK and Ireland, describes the system as an "AI telescope for the Sun." IBM trained the model on nine years of high-resolution images from the (SDO), a satellite NASA has been using to study the Sun since 2010. Effectively, Surya applies machine learning to solar image interpretation and forecasting, and the results are promising. In early testing, Bernabe-Moreno says IBM found the model was 16 percent more accurate at answering the question "will there be a solar flare in the next 24 hours?" than past systems. Additionally, the model can generate visual predictions of what the SDO might see ahead of time. So far, using data from the most , IBM has found Surya can accurately predict what the sun will look like two hours ahead of time. "We're exploring the accuracy of even longer lead time predictions," Bernabe-Moreno told me. Two hours might not seem like a lot, but according to Bernabe-Moreno, who previously worked at one of Europe's largest energy companies, it could be a game changer for infrastructure providers, which have spent the last few decades building more responsive power grids. Moreover, Surya is a 366 million parameter model, meaning it's light enough to run on less powerful hardware. The irony of today's announcement is that it demonstrates the value of NASA's science team exactly at a time when its very existence is threatened. If you haven't been following what's been going on at the agency, President Trump plans to . The Solar Dynamics Observatory would be among the missions affected by the proposed cuts. It won't be cancelled like New Horizons and OSIRIS-APEX, but according to an , the mission would have its operating budget slashed from $14 million annually to $8 million per year. Policymakers from both parties have pushed back on the proposal, but with the Senate and House not yet in agreement on the agency's 2026 operating budget, and the appropriations deadline quickly approaching, NASA's fate is uncertain. Even if the cuts don't go through, the agency is on track to , or about 20 percent of its workforce, as part of the Trump administration's broader efforts to trim the number of workers across the federal government. Bernabe-Moreno says Surya wouldn't have come together without NASA's help. "From the very beginning, the science team at NASA have been informing us what the model should do, how to validate the model, and how to ensure it's robust," he said. If there's a silver lining to the funding situation, it's that the science team's work will live on. "The beauty of this model is that we created a capability -- an AI platform, if you want," said Bernabe-Moreno. "And this capability has applications beyond NASA." If you want to check out Surya for yourself, you can download the model from .

NASA and IBM Unveil AI That Helps Scientists Forecast Solar Storms

Experts recently identified major gaps in their ability to forecast space weather. Surya aims to fill them. Earlier this year, local and national officials gathered for a first-of-its-kind tabletop exercise to test their readiness for a severe solar storm. The simulation exposed major gaps in scientists’ ability to forecast space weather, which threatens critical infrastructure on Earth and in orbit. On Wednesday, August 20, IBM and NASA unveiled Surya: an open-source AI model that could begin to fill those gaps. Heliophysicists currently rely on complex computer models to monitor and predict the Sun’s activity. Surya improves upon the lead time and accuracy of existing solar forecasting technologies, allowing scientists to not only predict a solar flare two hours out but also visually pinpoint where it should occur on the Sun’s surface, according to IBM. “It’s very important to have a mechanism to look into the Sun and understand how these events [are going to happen], when they’re going to happen, why they're going to happen, and start predicting the occurrence so that we can be prepared,†Juan Bernabé-Moreno, director of IBM Research Europe for Ireland and the U.K., told Gizmodo. The surface of the Sun is a violent place. Our host star is constantly emitting bursts of energy such as solar flares, high-speed solar winds, and coronal mass ejections. When Earth is in the line of fire during one of these events, the onslaught of high-energy particles can trigger a geomagnetic storm in the upper atmosphere. Such storms result from disturbances in Earth’s magnetic field and can damage or disrupt satellites, power grids, and radio communication systems, according to NASA. Being able to anticipate these outbursts gives decision-makers critical lead time to protect vulnerable infrastructure, potentially avoiding billions of dollars in damage. According to a systemic risk analysis by Lloyd’s, a severe solar storm could result in losses to the global economy of $2.4 trillion over a five-year period. Bernabé-Moreno thinks of Surya as a powerful AI telescope that also lets you look into the future. Whereas traditional solar weather prediction relies on partial satellite views of the Sun’s surface, Surya trained on nine years of high-resolution solar observation data gathered by NASA’s Solar Dynamics Observatory. This telescope launched in 2010 and has been continuously observing the Sun for the past 15 years, capturing images every 12 seconds at various wavelengths to take the temperature of its layers and map magnetic activity. Heliophysicists will be able to use Surya in a variety of ways, but its most novel application is solar flare prediction, IBM senior research scientist and technical project lead Johannes Schmude told Gizmodo in an email. The model does this by generating an image of an event that the SDO satellite is likely to see, essentially predicting what the surface of the Sun will look like hours ahead. Testing showed that Surya can predict a solar flare two hours in advance with a 16% improvement in flare classification accuracy, but IBM is exploring the accuracy of even longer lead time predictions, according to Schmude. It’s important to note, however, that Surya trained on data from the previous solar cycle. “Testing the model’s applicability to Solar cycle 25 is one of the post-release tasks on our list, but we plan to explore continuous training and other fine-tuning with data from Solar Cycle 25,†Schmude said. Following the release of this open-source AI model, Bernabé-Moreno is excited for the scientific community to begin using it on a wider scale, identifying new applications and challenging its capabilities. “That is going to create utility,†he said. “That, for us, is the most important thing.â€

You might see prettier skies, thanks to new tech from NASA and IBM

What if scientists could predict northern and southern lights like they could an eclipse? What if they could tell you where and when to be outside, within a narrow window, to see these vibrant displays? A new AI might make that possible. Today, IBM introduced Surya, an open-source foundational AI model that was developed in partnership with heliophysics scientists at NASA. "Surya is like an AI telescope for the sun that can also look into the future," explained Juan Bernabe Moreno, director of IBM research in Europe, the U.K., and Ireland. Not only can Surya model what the sun looks like now, but it can also predict our star's future behavior. This is key for understanding solar flares, and whether they will produce coronal mass ejections (CMEs) and subsequent geomagnetic storms, which cause northern lights. That's also important, as these can significantly disrupt life on Earth; a severe space weather risk scenario published by the London-based Lloyd's insurance marketplace presented possible global economic losses of up to $9.1 trillion over a five-year period.

IBM's and NASA's Surya AI model is designed to predict the next 'Carrington-class' solar storm - SiliconANGLE

IBM's and NASA's Surya AI model is designed to predict the next 'Carrington-class' solar storm IBM Corp. said today it's teaming up with experts from the National Aeronautics and Space Administration to create an artificial intelligence model that can provide an early warning about solar flares and coronal mass ejections that could cause serious disruption to life on Earth. The new open-source model, called Surya, named after the Sanskrit word for "sun," is available to download on Hugging Face. IBM said it's designed to interpret high-resolution solar images so it can forecast space weather conditions and help protect satellites in low-Earth orbit, power grids, telecommunications systems and other infrastructure that could be severely affected by strong solar flares. Scientists know only too well how damaging solar flares can be. Although the sun is about 93 million miles away, such events can knock out satellites, disrupt airline navigation and take energy grids offline, and they also pose major radiation risks to any astronauts who happen to be in orbit. Although these incidents are rare, they do happen. A case in point is the so-called "Carrington Event" in September 1859, which was a massive solar storm caused by a powerful coronal mass ejection from the Sun, directed at Earth. The flare was observed by the British Astronomer Richard Carrington 17 hours before the event, and resulted in spectacular auroras visible as far south as the Caribbean. It led to severe disruption of telegraph systems worldwide, causing operators to receive electric shocks and equipment to catch fire. There was even a report of two telegraph operators who shut down their systems, but were still able to communicate with one another given the electrical current in the atmosphere caused by the aurora. One study by Lloyd's suggests that if a similar event occurred today, it would likely cause extensive damage to electrical grids, satellites and communication systems, with economic losses estimated at about $2.4 trillion. There have been plenty of close calls in recent years. Less severe solar storms hit Earth in 1921 and 1938, causing massive radio disruption, while the March 1989 geomagnetic storms took down power grids in large parts of Quebec, Canada. Another "Carrington-class" solar storm occurred in July 2012, but its trajectory missed the Earth by a margin of just nine days. With humanity becoming increasingly dependent on space-based technology and focused on further exploration of the solar system, it's essential to be able to predict the behavior of the sun, and that's exactly what Surya has been designed to do. If experts can accurately forecast a solar flare, they might be able to shut down at-risk infrastructure systems and prevent damage from being done to them. Current solar weather prediction relies on partial satellite views of the Sun's surface, but Surya significantly improves on this. It's trained on the world's largest and highest-resolution heliophysics dataset, which was created to help researchers study and evaluate space weather prediction tasks. Some example tasks, which Surya was trained on, include solar flare prediction, solar EUV spectra forecasting, the speed of solar winds and the emergence of active regions on the Sun's surface. IBM's and NASA's researchers say early tests show that Surya has achieved a 16% improvement in the accuracy of solar flare classifications. They intend to continue training the model to visually predict solar flares for the first time, with the aim being to provide a two-hour warning before such events take place. IBM Research Europe Director Juan Bernabe-Moreno said Surya will provide weather forecasts for the sun. "Just as we work to prepare for hazardous weather events, we need to do the same for solar storms," he explained. "Surya gives us the 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." Surya was reportedly trained on more than nine years' worth of high-resolution solar observation data from the NASA Solar Dynamics Observatory. The images are about 10 times larger than typical images used for AI training, so IBM had to develop a customized multi-architecture system to handle the increased spatial resolution. That's needed to resolve solar features with enough detail and context to try and understand what's happening. NASA Chief Science Officer Kevin Murphy said the combination of its deep scientific expertise and powerful AI is extremely promising for data-driven science. "By developing a foundation model trained on NASA's heliophysics data, we're making it easier to analyze the complexities of the Sun's behavior with unprecedented speed and precision," he said. "This model empowers broader understanding of how solar activity impacts critical systems and technologies that we all rely on here on Earth." Holger Mueller of Constellation Research Inc. said the model is a good example of where AI doesn't just replace humans, but does jobs that most humans cannot do. "Very few people in the world have the skills to even attempt to forecast solar weather, so AI changes the dynamic," the analyst said. Additionally, Mueller said the partnership between IBM and NASA shows how organizations can work together to continuously advance AI. "We have one partner with all of the data, and the other has the know-how and systems in place to build the models, and we will see many more of these kinds of partnerships in all areas." Surya is just the latest initiative in a long-running collaboration between IBM and NASA. Two years ago, they teamed up to create an AI model that's designed to analyze geospatial satellite imagery at unprecedented scale. It's one of the most powerful models within the Prithvi family, and is all about forecasting Earth-based risks, such as flooding and wildfires. Like Surya, it was open-sourced and made available on Hugging Face for the benefit of the broader research community. Last year, IBM and NASA released a second Prithvi model designed to provide short- and long-term weather projections and forecast climate change.