Barnes, D; (2017) Forecasting and Modelling the Terrestrial Effects of Space Weather using STEREO and CMAT2. Doctoral thesis , UCL (University College London).

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Abstract

The work presented in this thesis focuses on two aspects of space weather. The first of these uses NASA’s Solar TErrestrial RElations Observatory (STEREO) to measure solar wind properties. The Heliospheric Imagers (HIs) on-board each of the two STEREO spacecraft are used to infer the density distribution within two Coronal Mass Ejections (CMEs) by tomographic inversion of white light images. The resulting densities from successive images are then used to determine how the CMEs evolve through the heliosphere and to make estimates of their speed and density at Earth, which are compared with measurements from near-Earth spacecraft. The second area of research involves modelling studies of how the neutral atmosphere responds to energy transfer from the solar wind. Data from the Super Dual Auroral Radar Network (SuperDARN) provide high spatial and temporal resolution measurements of Earth’s high latitude electric field in both hemispheres. These data are used to drive the UCL Coupled Middle Atmosphere Thermosphere (CMAT2) General Circulation Model (GCM), which is used to study the effects of electric field variability and hemispheric asymmetry in ionosphere-thermosphere coupling. Results of simulations using this new version of CMAT2 are compared to ground- and space-based observations. As a means to connect these two areas of research, it was one original aim of this thesis to develop CMAT2 in such a way that STEREO observations could be used to drive its solar wind energy input. Chapter 5 shows that some limited information about geoeffective solar wind properties, such as speed and density, may be determined using HI data. However, detailed information about the interplanetary magnetic field (IMF) is required to accurately simulate energy transfer between the ionosphere and neutral atmosphere. Instead, a new electric field model has been developed, which allows CMAT2 to be driven using the IMF as an input. This model quantifies the electric field variability, as a means to accurately model Joule heating, which is a problem common to many GCMs.

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