Visualisation of Multivariate Dynamics in the Ionosphere-Thermosphere Using High-Resolution TIE-GCM OTHITACS Numerical Simulations

Abstract

This thesis focus on demonstrating the ionosphere-thermosphere system’s response to space weather. A visualisation tool was developed using Python’s Tkinter and Python Interface for Generic Mapping Tools (PyGMT) to explore data from physics-based TIEGCM (Thermosphere ionosphere electrodynamics general circulation model) model and the GRACE-FO satellite. The tool enables users to interactively explore complex datasets, including key variables like neutral density and crosswinds, through features like 3D viewing, time and altitude controls, and variable selection. A case study on the geomagnetic storm of 3-4 February 2022, demonstrates the tool’s application, comparing model data with real observations from GRACE-FO. The findings show that TIE-GCM accurately captures large-scale atmospheric patterns but misses finer details during intense geomagnetic activity, highlighting the importance of integrating model data with satellite observations for a comprehensive understanding of space weather impacts. This work underscores TIE-GCM’s value for studying the ionosphere-thermosphere system and the role of visualisation in improving space weather predictions.