Data Constrained Models for Solar Activity Predictions

Bhowmik, Prantika (2019) Data Constrained Models for Solar Activity Predictions. PhD thesis, Indian Institute of Science Education and Research Kolkata.

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Though our planet is 149.6 million kilometers away from the Sun, its input is sensed through countless aspects. The Sun’s influence goes beyond Earth and extends to the far end of heliosphere. Solar output in terms of particle flux, electromagnetic and thermal radiation defines the environment in the heliosphere. Variation in the Sun’s activity modulates the condition in outer space creating space weather. Solar variability has both long-term cyclic nature of decadal periodicity and a sporadic, eruptive component which can change within days. Eruptive events such as coronal mass ejections (CMEs), solar flares directed towards Earth result in hazardous geomagnetic disturbances affecting space-based satellites to groundbased electric power grids. A typical event can eject energy of 10²⁶ joules into the heliosphere. The frequency of such highly energetic events are closely related with the cycle of sunspots. The amplitude of the sunspot cycle varies from one cycle to another without any apparent uniformity. The unpredictability of solar activities originates from the significant complexity and chaotic nature of the Sun as a physical system. Much of the solar activities are directly linked with the Sun’s magnetic field. With increasing dependency of modern society on space-reliant technologies, the importance of predicting upcoming solar activities is undeniable. This thesis research primarily aims to develop and advance our predicting capabilities of solar activities utilizing physicsbased numerical simulations. Apart from this, other fundamental characteristics of the Sun’s large-scale magnetic fields are also explored as a part of this thesis. In the introduction (Chapter 1), we begin with providing an overview of solar magnetic field observations. This is followed by outlining the essential theoretical concepts underlying the creation and evolution of the magnetic field. Finally, we give a short account of the current status of the research targeted to predicting solar variabilities of magnetic origin. In this thesis, three computational models have been utilized to study the magnetic field evolution and distribution within the solar convection zone on the surface and in the solar corona. Among these three, the model simulating the evolution of the surface magnetic field is newly developed. It is an observational data-driven model which mimics the physical mechanism involving the decay and dispersal of magnetic flux associated with sunspots in the presence of plasma motions. This type of model is known as the surface flux transport model. The other two: a solar dynamo model and a potential field source surface extrapolation model were already developed by others. These are modified and utilized according to the research problems. Chapter 2 gives a detailed description of the mathematical foundation and computational particulars relevant for developing the surface flux transport model. This newly developed code is validated through a parameter-space study. Additionally, a brief discussion on the other two numerical models is also provided in this chapter. Using the observational data-driven surface flux transport model we simulate the evolution of surface magnetic fields during the last 100 years starting from 1913. The simulated polar flux shows satisfactory resemblance with the observed polar flux time-series. This gives us the confidence for using this model for predictive purposes. Producing a physics-based longterm prediction (4-5 years in advance) of the upcoming sunspot cycle requires a solar dynamo model and an accurate knowledge of the polar field during the minimum of the previous cycle. Currently, we are in the descending phase of solar cycle 24 and a few years away from the solar minimum. Here, we present a methodology to predict the succeeding solar cycle 25 even before reaching the end of cycle 24. Using the newly developed data-driven surface flux transport model, we first predict the polar field during cycle 24 minimum and subsequently use it in dynamo simulation to predict the toroidal field of cycle 25 which will eventually produce the next cycle’s sunspots. Using this scheme of assimilating surface flux transport model-generated magnetic fields in a dynamo simulation, we successfully reproduce the solar activity cycles in the last 100 years. Chapter 3 includes the results associated with the century-scale simulations and our prediction of solar cycle 25. The dynamical memory and predictability associated with solar dynamos substantially depend on the parameters assisting the transport of the poloidal component of the magnetic field from the solar surface to the base of the convection zone. These transport parameters are meridional circulation, magnetic diffusivity, and turbulent pumping. We study the extent of cycle memory by performing multiple dynamo simulations while introducing several variations in these parameters. Additionally, we re-evaluate how such modifications incorporated in the dynamo part of the scheme described in Chapter 3 affect our ability to reproduce the past solar activity cycles. The analysis and results are presented in Chapter 4. In Chapter 5, we present a short-term prediction of the Sun’s large-scale magnetic field distribution in the corona during the August 21, 2017, Great American solar eclipse, five days in advance. The forecast is achieved by performing a potential field source surface extrapolation on the photospheric magnetic field obtained from the surface flux transport model. Further analysis reveals that this methodology is capable of predicting the large-scale structures of the coronal magnetic field about one month in advance. Finally, in the last chapter (Chapter 6) we explore one of the significant characteristics of solar magnetism: hemispheric asymmetry. This study consists of three segments. Firstly, we analyze the hemispheric asymmetry present in the time-series of the observed polar flux and sunspot area data. Secondly, using surface flux transport model, we investigate what factors cause asymmetry in the polar flux in the framework of the Babcock-Leighton mechanism. In the final part, through dynamo simulations we study how the north-south asymmetry present in the poloidal field at the solar minimum translates to the succeeding sunspot cycle. Finally, we explore whether assimilating the hemispheric asymmetry (at cycle minima) in the Babcock-Leighton source of the dynamo simulations is sufficient for reproducing the asymmetry observed during the past solar cycles.

Item Type: Thesis (PhD)
Additional Information: Supervisor: Prof. Dibyendu Nandi
Uncontrolled Keywords: Data Constrained Models; Global Coronal Magnetic Field; Hemispheric Asymmetry; Solar Activity; Solar Cycle 25; Solar Cycle Memory; Solar Dynamo Model; Solar Magnetic Cycles; Space Weather; Surface Flux Transport Model
Subjects: Q Science > QC Physics
Divisions: Center of Excellence in Space Sciences, India
Depositing User: IISER Kolkata Librarian
Date Deposited: 09 Jul 2019 10:42
Last Modified: 09 Jul 2019 10:43

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