NASA’s COFFIES Uses AI to Predict Storm-Causing Active Regions on Sun

As humanity looks to the Moon and stars for future exploration, predicting space weather, conditions in space primarily driven by the Sun, is more important than ever. The institutional report frames the development in practical terms and ties it to the broader mission or observing effort.

This matters because Earth science becomes stronger when local observations can be placed inside a broader physical pattern that spans time and geography. The planet operates as a coupled system in which atmospheric, oceanic, cryospheric and solid-Earth processes interact across timescales from days to millions of years. A measurement that captures one variable at one location and one moment has limited interpretive value until it is embedded in the longer series and wider spatial coverage that allow natural variability to be separated from forced change. 5 min read NASA’s COFFIES Uses AI to Predict Storm-Causing Active Regions on Sun As humanity looks to the Moon and stars for future exploration, predicting space weather. NASA’s Solar Dynamics Observatory captured this image of a solar flare, seen as the bright flash in the upper right, on June 30, 2026.

NASA’s Goddard Space Flight Center/SDO By bridging expertise across different scientific institutions, COFFIES, a NASA DRIVE (Diversify, Realize, Integrate, Venture, Educate). The first column of blocks shows targeted areas at original resolution, the middle column displays data as 2D maps, and the right column plots changes in magnetic polarity over.

NASA’s real-time space weather monitoring As NASA focuses on sending humans to explore the Moon with the Artemis missions and sending the first crewed missions to Mars, monitoring. To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video NASA’s Moon to Mars Space Weather Analysis Office monitors space.

NASA/Lacey Young Teams across NASA and NOAA collaborate to transition research capabilities into actual 360-degree space weather monitoring operational tools, including NASA’s. About the Author Desiree Apodaca NASA’s Heliophysics Missions Communications Lead Share Details Last Updated Aug 14.

The broader interest lies in linking the observation to climatic, geophysical or environmental dynamics that extend well beyond the immediate event or location. Earth science is unusual in that its most important questions operate on timescales that no single research career can observe directly, making the archival record, whether in ice, sediment, rock or satellite data, as important as any new measurement. Results that can be embedded in that record, and that either confirm or challenge the patterns it reveals, carry disproportionate scientific weight.

A team with NASA’s COFFIES has developed a novel machine-learning model capable of predicting the emergence of active regions on the Sun up to 12 hours before they appear. Now, a team of astrophysicists and data scientists with NASA’s COFFIES (Consequence Of Fields and Flows in the Interior and Exterior of the Sun) has developed a novel.

Because the account originates with NASA News Releases, it functions best as a primary institutional report that is close to the data and operations, not as independent scientific validation. Institutional communications are produced by organizations with legitimate interests in presenting their work in a favorable light, which does not make them unreliable but does make them partial. Details that complicate the narrative, including instrument limitations, unexpected failures and results below projections, tend to be minimized relative to progress messages. Technical documentation and peer-reviewed publications, where they exist, provide the complementary layer that institutional releases cannot substitute.

The next step is to place the result inside longer time series and to compare it with independent instruments and independent sites. Earth system observations gain most of their interpretive power from network density and temporal depth, not from any single measurement however precise. Model simulations that assimilate the new data will help clarify whether the observation fits comfortably within known natural variability or represents a shift that existing models do not reproduce.

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