Alex Zhang
Pronouns: he/him
Research Mentor(s): Zhenguang Huang
Research Mentor School/College/Department: Climate and Space Sciences and Engineering / Engineering
Program:
Authors: Alex Zhang, Zhenguang Huang, Nishtha Sachdeva
Session: Session 7: 4:40 pm – 5:30 pm
Poster: 76
Abstract
The solar wind plays a crucial role in space weather prediction as it can cause or influence various space weather events. This project aims to better understand historical variations in the solar wind to improve space weather prediction models. 180 numerical simulations of the Alfvén Wave Solar Model (AWSoM), the current state-of-the-art model developed at the University of Michigan for solar activity, were conducted to investigate the model performance in the last solar cycle, with one Carrington rotation per year between 2011 and 2019. The model’s predicted output was then compared with the OMNI observed solar wind, using a variety of methods to determine the optimal model run for each Carrington rotation. It was determined that the current model is less accurate during periods of high solar activity near 2013. Further analysis was conducted to determine the optimal model parameters for different phases of the solar cycle. Python tools were developed to visualize and analyze trends in the data to better understand the physics behind solar wind variations. We have determined the optimal Poynting flux parameter for modeling historical Carrington rotations in the last solar cycle. The Python tool developed in this project can be used to better prescribe model parameters, most notably the Poynting flux value, for real-time solar wind simulations. It can also be used to validate the AWSoM model and demonstrate its advantages in accurately predicting the solar wind. Improving this model and its usage will be a significant step towards the future of space weather forecasting.
