NASA is turning up the heat in solar science with the launch of the Surya Heliophysics Foundational Model, an artificial intelligence (AI) model trained on 9 years of observations from NASA\u2019s Solar Dynamics Observatory. <\/p>\n\n\n\n
Developed by NASA in partnership with IBM and others, Surya uses advances in AI to analyze vast amounts of solar data, helping scientists better understand solar eruptions and predict space weather that threatens satellites, power grids, and communication systems. The model can be used to provide early warnings to satellite operators and helps scientists predict how the Sun\u2019s ultraviolet output affects Earth\u2019s upper atmosphere.<\/p>\n\n\n\n
Preliminary results show Surya is making strides in solar flare forecasting, a long-standing challenge in heliophysics. Surya, with its ability to generate visual predictions of solar flares two hours into the future, marks a major step towards the use of AI for operational space weather prediction. These initial results surpass existing benchmarks by 16%. By providing open access to the model on HuggingFace and the code on GitHub, NASA encourages the science and applications community to test and explore this AI model for innovative solutions that leverage the unique value of continuous, stable, long-duration datasets from the Solar Dynamics Observatory.<\/p>\n\n\n\n
The model\u2019s success builds directly on the Solar Dynamics Observatory\u2019s long-term database. Launched in 2010, NASA\u2019s Solar Dynamics Observatory has provided an unbroken, high-resolution record of the Sun for nearly 15 years through capturing images every 12 seconds in multiple wavelengths, plus precise magnetic field measurements. This stable, well-calibrated dataset, spanning an entire solar cycle, is uniquely suited for training AI models like Surya, enabling them to detect subtle patterns in solar behavior that shorter datasets would miss.<\/p>\n\n\n\n
Surya\u2019s strength lies in its foundation model architecture, which learns directly from raw solar data. Unlike traditional AI systems that require extensive labeling, Surya can adapt quickly to new tasks and applications. Applications include tracking active regions, forecasting flare activity, predicting solar wind speed, and integrating data from other observatories including the joint NASA-ESA Solar and Heliospheric Observatory mission and NASA\u2019s Parker Solar Probe.<\/p>\n\n\n\n
\u201cWe are advancing data-driven science by embedding NASA\u2019s deep scientific expertise into cutting-edge AI models,\u201d said Kevin Murphy, chief science data officer at NASA Headquarters in Washington. \u201cBy developing a foundation model trained on NASA\u2019s heliophysics data, we\u2019re making it easier to analyze the complexities of the Sun\u2019s 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.\u201d<\/p>\n\n\n\n
Solar storms pose significant risks to our technology-dependent society. Powerful solar events energize Earth’s ionosphere, resulting in substantial GPS errors or complete signal loss to satellite communications. They also pose risks to power grids, as geomagnetically induced currents from coronal mass ejections can overload transformers and trigger widespread outages.<\/p>\n\n\n\n
In commercial aviation, solar flares can disrupt radio communications and navigation systems while exposing high-altitude flights to increased radiation. The stakes are even higher for human spaceflight. Astronauts bound for the Moon or Mars may need to depend on precise predictions to shelter from intense radiation during solar particle events.<\/p>\n\n\n\n
The Sun\u2019s influence extends to the growing number of low Earth orbit satellites, including those that deliver global high-speed internet. As solar activity intensifies, it heats Earth\u2019s upper atmosphere, increasing drag that slows satellites, pulls them from orbit, and causes premature reentry. Satellite operators often struggle to forecast where and when solar flares might affect these satellites.<\/p>\n\n\n\n
“Our society is built on technologies that are highly susceptible to space weather,” said Joseph Westlake, Heliophysics Division director at NASA Headquarters. \u201cJust as we use meteorology to forecast Earth’s weather, space weather forecasts predict the conditions and events in the space environment that can affect Earth and our technologies. Applying AI to data from our heliophysics missions is a vital step in increasing our space weather defense to protect astronauts and spacecraft, power grids and GPS, and many other systems that power our modern world.\u201d<\/p>\n\n\n\n
While Surya is designed to study the Sun, its architecture and methodology are adaptable across scientific domains. From planetary science to Earth observation, the project lays the foundational infrastructure for similar AI efforts in diverse domains.<\/p>\n\n\n\n
Surya is part of a broader NASA push to develop open-access, AI-powered science tools. Both the model and training datasets are freely available online to researchers, educators, and students worldwide, lowering barriers to participation and sparking new discoveries.<\/p>\n\n\n\n
Surya\u2019s training was supported in part by the National Artificial Intelligence Research Resource (NAIRR) Pilot, a National Science Foundation (NSF)-led initiative that provides researchers with access to advanced computing, datasets, and AI tools. The NAIRR Pilot brings together federal and industry resources, such as computing power from NVIDIA, to expand access to the infrastructure needed for cutting-edge AI research.<\/p>\n\n\n\n
\u201cThis project shows how the NAIRR Pilot is uniting federal and industry AI resources to accelerate scientific breakthroughs,\u201d said Katie Antypas, director of NSF\u2019s Office of Advanced Cyberinfrastructure. \u201cWith support from NVIDIA and NSF, we\u2019re not only enabling today\u2019s research, we\u2019re laying the groundwork for a national AI network to drive tomorrow\u2019s discoveries.\u201d<\/p>\n\n\n\n
Surya is part of a larger effort championed and supported by NASA\u2019s Office of the Chief Science Data Officer and Heliophysics Division, the NSF , and partnering universities to advance NASA\u2019s scientific missions through innovative data science and AI models. Surya\u2019s AI architecture was jointly developed by the Interagency Implementation and Advanced Concepts Team (IMPACT) under the Office of Data Science and Informatics at NASA\u2019s Marshall Space Flight Center in Huntsville, Alabama; IBM; and a collaborative science team.<\/p>\n\n\n\n
The science team, assembled by NASA Headquarters, consisted of experts from the Southwest Research Institute in San Antonio, Texas; the University of Alabama in Huntsville in Huntsville, Alabama; the University of Colorado Boulder in Boulder, Colorado; Georgia State University in Atlanta, Georgia; Princeton University in Princeton, New Jersey; NASA\u2019s SMD\u2019s Heliophysics Division; NASA\u2019s Goddard Space Flight Center in Greenbelt, Maryland; NASA\u2019s Jet Propulsion Laboratory in Pasadena, California; and the SETI Institute in Mountain View, California.<\/p>\n","protected":false},"excerpt":{"rendered":"
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