Rayta Pradata

Date of Award

2023

First Advisor

Mike Bergman

Second Advisor

Eric Kramer

Third Advisor

Gangkai Poh

Abstract

The solar wind is a stream of charged particles flowing radially outwards from the Sun. It interacts with a planet’s magnetic field to form a region of magnetic cavity called the magnetosphere. Moreover, it determines conditions in space weather, which affects satellites in outer space and even technology in Earth. Therefore, models that aim to predict solar wind conditions have been developed over time. They are created to simulate space weather at Earth, hence validated at its orbit (i.e., 1 A.U.). However, in order to improve the model’s validity, we would need multiple points of validation outside of Earth’s orbit around the sun, as the solar wind traverses to the end of the heliosphere beyond the solar system. One way we could achieve this is to validate the predictions at other planets. In addition, previous observations from MESSENGER, a satellite orbiting Mercury sent by NASA, have shown that plasma dynamical processes within Mercury’s magnetosphere are strongly driven by its solar wind conditions, especially due to its small size. This is also a similar case for Mars, especially with the absence of a global magnetic field, leading to its induced magnetosphere resulting from the solar wind interactions with the planet’s ionosphere and crustal magnetism. Hence, accurate prediction of solar wind conditions in these planets would help us understand the plasma processes governing these environments too. This project looks at a solar wind model under development that hopes to achieve this goal: the Alfvén Wave Solar Atmosphere Model (AWSoM), developed at the University of Michigan. This model has been validated with Earth-based satellite observations. Therefore, I worked alongside my mentor at NASA GSFC, Dr. Gang Kai Poh, as well as collaborators from the University of Michigan, Dr. Nishtha Sachdeva and Dr. Zhenguang Huang, to assess the model’s capability in predicting space weather conditions beyond Earth, particularly at Mercury and Mars, by comparing the model’s simulated outputs to spacecraft data, i.e., from MESSENGER on Mercury, and MAVEN on Mars as future work. We collected solar wind data during certain periods of time and categorized them by Carrington rotation (CR), which is the period of Sun’s rotation around its own axis. Each run of the simulation in a Carrington rotation produces 12 “realizations”, which were compared with measurements and assessed on how well they agreed with the spacecraft observations. Because there is a variable time-lag between fluctuations observed in the solar wind and the subsequent variations in planetary magnetic field data, we use a specialized technique called Dynamic Time Warping (DTW) and implemented it on all 12 realizations of each run to determine the “best-fit” comparison accounting for such time shift. The comparison methods presented in this study will contribute to future studies related to solar activity and solar wind magnetic field, and applied towards future spacecraft missions (e.g. Bepi-Colombo, which is will orbit Mercury.

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