Understanding Magnetic Field Evolution from the Solar Interior to the Heliosphere

Pal, Shaonwita (2026) Understanding Magnetic Field Evolution from the Solar Interior to the Heliosphere. PhD thesis, Indian Institute of Science Education and Research Kolkata.

Text (PhD thesis of Shaonwita Pal (19RS038)) 19RS038.pdf - Submitted Version Restricted to Repository staff only Download (60MB)

Abstract

In the modern era, our understanding of solar and stellar physics has evolved dramatically, driven by both observational advances and sophisticated modelling techniques. One of the most dynamic and consequential aspects of solar and stellar behavior is their magnetic activity, which manifests through various energetic phenomena such as flares, coronal mass ejections (CMEs), and high-speed solar wind streams. These events have a profound impact on the upper atmospheres of planets, including Earth, and shape the radiation environment of the heliosphere. Collectively, their influence is recognized as space weather, which can disrupt satellite operations, navigation systems, communication infrastructure, and even power grids on Earth. Therefore, understanding the solar cycle is essential for anticipating space weather risks. Understanding the underlying mechanisms that govern solar magnetic activity also offer fundamental insights on the behaviour of the magnetized plasma in cosmos. The Sun, being the nearest star to Earth, serves as an exceptional laboratory for investigating the detailed physics of magnetic cycles that are believed to operate in other solar-like stars. Solar magnetic activity is intimately linked to the approximately 11-year sunspot cycle, a visible manifestation of the Sun’s internal magnetic dynamo. For example, solar energetic events are far more frequent and intense during solar maximum, when the Sun’s magnetic field is most dynamic and complex, and sunspot numbers peak. During this phase, the increased number of active regions and magnetic field reconfigurations enhances the likelihood of explosive energy release through reconnection processes. Conversely, during solar minimum, such energetic events become rare due to the Sun’s relatively stable and weaker magnetic configuration. Since the number of sunspots varies cyclically, accurately predicting the strength and timing of future solar cycles is crucial, as the amplitude of the sunspot cycle changes from one cycle to the next. However, despite significant progress, reliable prediction of solar cycle strength remains a long-standing challenge in solar physics. The challenge arises due to the nonlinear and stochastic nature of the solar dynamo process, which operates within the Sun’s interior and on its surface. This brings forward a fundamental question: What drives the irregularities and variability observed in the solar cycle? Understanding this would not only aid in predicting solar activity but may also shed light on how magnetic variability influences the structure and dynamics of the heliosphere – the vast bubble carved out by the solar wind in the interstellar medium. It is to be noted that variability in the solar magnetic field affects the total and open solar magnetic flux, which in turn modulates cosmic ray fluxes reaching Earth and influences long-term space weather conditions. Another important aspect of understanding the Sun’s dynamics is that the generation and evolution of the Sun’s magnetic fields are governed by complex interactions between plasma flows and magnetic fields within its convective zone and across the solar surface. Key processes such as differential rotation, meridional flow, and turbulent convective motions redistribute magnetic flux on the surface, leading to observable large-scale patterns such as the emergence of bipolar magnetic regions (BMRs) and polar field reversals. Studying these surface processes and their coupling with the solar atmosphere is critical to decoding the observed behavior of the Sun. This doctoral research focuses on understanding these magnetic processes through a combination of observational data analysis, analytical theory, and advanced numerical modelling techniques. In particular, we have developed and employed a data-driven Surface Flux Transport (SFT) model, named SPhoTraM, to simulate the long-term evolution of the solar surface magnetic field. This model helps in probing the origin of solar cycle variability, predicting polar field buildup, and evaluating solar cycle precursors. Furthermore, by coupling SFT simulations with the coronal magnetic field model, such as the full Magnetohydrodynamic (MHD) model or the Potential Field Source Surface (PFSS) extrapolation technique, we have investigated how photospheric field distributions affect the global coronal structure and the heliospheric magnetic field. We begin this thesis with Chapter 1, which provides a brief introduction connecting the Sun’s interior to the outer heliosphere, highlighting the physical processes behind the Sun’s variability as reflected in observations. In Chapter 2, we present the numerical models employed to address the various scientific questions explored in this thesis. The chapter primarily focuses on the development of the data-driven surface flux transport model, SPhoTraM, along with an extensive parameter space study to investigate the underlying physics captured by the SFT framework. Additionally, we provide an overview of coronal magnetic field extrapolation techniques, including the Potential Field Source Surface (PFSS) model and the Alfv´en Wave Solar Model (AWSoM), as well as a brief introduction to solar dynamo models, discussing key parameters and boundary condition implementations. These models are important tools for studying the Sun’s interior, surface and atmosphere as well. Chapter 3 introduces an algebraic method for estimating the Sun’s axial dipole moment using historical sunspot observations. Using this approach, we reconstruct the dipole moment over the past century and demonstrate its potential for forecasting future solar cycle strength, which we apply in the case of Solar Cycle 25. Notably, this simplified analytic framework reinforces the significance of the Babcock–Leighton mechanism, offering a more efficient and less parameter-dependent alternative to complex numerical simulations. In Chapter 4, we demonstrate that even a small fraction of anomalous sunspots – particularly anti-Hale regions, which exhibit polarity orientations opposite to the standard Hale’s law, and anti-Joy regions, which possess abnormal tilt angles – can significantly influence the evolution of the polar flux and the solar axial dipole moment, thereby affecting the amplitude of the subsequent solar cycle. We also investigate various emergence statistics by altering the spatio-temporal distribution of these anomalous active regions to identify which types exert the greatest impact on solar cycle variability. Chapter 5 investigates the physical basis behind the sharp fall from Solar Cycle 19 to 20 and finds that stochastic variations in tilt and polarity of sunspot emergences can explain extreme cycle-to-cycle variability. It also establishes that the stochasticity is the primary driver of solar cycle irregularities over the centennial timescales. In Chapter 6, we address the question, which polar precursor – hemispheric polar flux or the global axial dipole moment – better predicts the solar cycle. Using century-scale solar cycle simulations and observational data, we find that the axial dipole moment consistently serves as a more reliable candidate for solar cycle forecasting (both in amplitude and peak timing) over the polar flux. Chapter 7 demonstrates that polar filaments, which trace the evolution of the Sun’s large-scale magnetic field, can serve as reliable precursors to polar flux and thereby the strength of future solar cycles. This study also establishes a clear connection between the temporal variations of polar filaments and the Babcock–Leighton (BL) process, highlighting their role in the surface field evolution that governs solar cycle modulation. Chapter 8 investigates whether the large-scale coronal magnetic field retains memory during the period of solar maximum, when solar activity is at its peak. To examine this, we utilize the event of the total solar eclipse on April 8, 2024, to validate our magnetic field predictions obtained from the Surface Flux Transport Model (SPhoTraM) coupled with the coronal magnetic field model (AWSoM). The comparison reveals that the large-scale coronal structure preserves its magnetic memory even near the solar maximum. Finally, in Chapter 9, we reconstruct a century-long time series of the open solar flux by coupling SPhoTraM with the PFSS extrapolation model and dynamically adjusting the source surface height to optimize the interplanetary magnetic field variations with in situ data. We formulate an empirical relationship between the source surface height and different phases of solar activity, which provides a novel technique for coronal magnetic field reconstruction. This work addresses the open solar flux problem directly and reveals the decline of open flux after Cycle 21 and the end of the Modern Grand Maximum. In a nutshell, in this thesis, we primarily explore the physical basis of the variations in the Sun’s magnetic output and how these variations influence interplanetary space. Together, these efforts contribute to the development of tools for solar cycle prediction, deepen our understanding of the physical processes driving the solar dynamo, improve our ability to model and understand the Sun’s corona, improve the reconstruction of open solar flux, and ultimately strengthen our capacity to forecast space weather events.

Actions (login required)

View Item