Sun’s Hidden Magnetic Fields Reconstructed Using Surface Data

The Sun’s 11-year magnetic activity cycle governs solar flares and space weather that can disrupt satellites, navigation systems, and power grids on Earth. Predicting the timing and strength of these cycles has long challenged scientists because the Sun’s deep internal magnetic fields cannot be directly observed. A new study offers a data-driven way to overcome this limitation.

Breakthrough from IIT Kanpur Researchers

In a study published on January 20 in Astrophysical Journal Letters, PhD student Soumyadeep Chatterjee and assistant professor Gopal Hazra from Indian Institute of Technology Kanpur demonstrated a method to reconstruct the Sun’s internal magnetic fields using long-term surface observations. The research draws on nearly three decades of solar magnetic field data.

Moving Beyond Simplified Dynamo Models

Solar physicists traditionally rely on dynamo models to explain how the Sun generates magnetic fields. These models often simplify sunspots as symmetrical, circular features, despite their irregular nature. Such assumptions have limited predictive accuracy. The new approach replaces idealised rules with real observational inputs, allowing the model to better reflect the Sun’s complex behaviour.

Using Three Decades of Satellite Observations

The researchers fed their three-dimensional model with surface magnetic field data recorded between 1996 and 2025 by missions such as SOHO and Solar Dynamics Observatory. By constraining the model to match surface observations, they inferred the behaviour of magnetic fields deep within the solar convection zone.

Important Facts for Exams

• The Sun follows an average 11-year magnetic activity cycle.
• The ‘butterfly diagram’ shows sunspots migrating from higher latitudes towards the equator.
• The toroidal magnetic field inside the Sun drives sunspot formation.
• Solar cycle 25 is currently underway.

Improved Forecasting of Solar Activity

The model successfully reproduced the butterfly diagram and accurately matched the strength of solar cycles 23, 24, and 25. When tested for prediction, it could forecast the peak intensity of a solar cycle up to three years in advance. According to Dr. Hazra, speaking to The Hindu, the findings enhance understanding of solar magnetism and provide early warnings of potentially dangerous solar activity for space-based technologies and communications.