For the first time, scientists have successfully created a three-dimensional map of the sun’s internal magnetic field, utilizing nearly three decades of data from solar satellites. This groundbreaking study allows researchers to better understand the dynamic processes occurring beneath the sun’s surface, which have long remained a mystery.
The sun exhibits various behaviors, from the emergence of dark spots to energetic bursts that can disrupt satellite communications and power systems on Earth. While the underlying cause of these phenomena has been attributed to magnetic activity, the specific dynamics have been elusive until now.
Traditionally, methods such as helioseismology have failed to provide accurate measurements of the sun’s magnetic field beneath its surface. The new research, published in The Astrophysical Journal Letters, marks a significant advancement in solar physics. The authors explain, “We reconstruct, for the first time, the dynamics of the interior large-scale magnetic fields.”
To create this model, researchers collected daily magnetic field maps recorded by solar satellites from 1996 to 2025. These maps detail the appearance and evolution of magnetic fields on the sun’s surface. The team then integrated this extensive data into a sophisticated three-dimensional computer model designed to simulate the sun’s internal magnetic mechanisms.
As fresh surface data was fed into the model, it continuously adjusted to ensure physical consistency. This innovative approach allowed scientists to infer the probable magnetic structures and flows hidden beneath the surface that could generate the observed patterns.
To validate their method, the researchers tasked the model with reconstructing past solar cycles, which typically last around 11 years. The model accurately mirrored multiple solar cycles observed during the satellite era, including the notable migration of sunspots from higher latitudes toward the solar equator, a critical indicator of solar cycle progression.
The study authors noted, “Our data-driven model successfully reproduces key observational features, such as the surface butterfly diagram, accurate polar field evolution, and axial dipole moment.”
A crucial aspect of the research involved predicting future solar activity. By halting the addition of new data at specific points, the model was allowed to run independently. Remarkably, it successfully forecasted major features of solar activity up to three to four years ahead. The researchers stated, “A strong correlation between the simulated toroidal field and sunspot number establishes our 3D magnetogram-driven model as a robust predictive model of the solar cycle.”
This advancement represents a pivotal shift in the study of solar phenomena. Researchers can now indirectly monitor the sun’s interior, enhancing the reliability of forecasts related to solar activity. Improved predictions could lead to better protection for satellites, reduced risks for navigation systems, and timely alerts for power grid operators regarding potential geomagnetic disturbances.
Despite this progress, the model’s effectiveness hinges on the continuity of long-term satellite missions. Future efforts will focus on refining the technique to predict not only when solar activity will peak but also where on the sun’s surface active regions are likely to form.
The implications of this study extend beyond academia, as enhanced solar activity forecasts could significantly impact technological systems on Earth, making this work vital for various sectors reliant on satellite and electrical infrastructure.
