Evolution of coronal mass ejection longitudinal structure through interplanetary space

James, L. A. ORCID: https://orcid.org/0000-0002-7712-2837 (2024) Evolution of coronal mass ejection longitudinal structure through interplanetary space. PhD thesis, University of Reading. doi: 10.48683/1926.00115818

Abstract/Summary

Accurately forecasting the arrival of Coronal Mass Ejections (CME) at Earth is important to enable the mitigation of the associated space weather risks to society. This is only possible with accurate modelling of the event. To do so, we must understand the propagation of a CME through the heliosphere and quantify the performance of models through comparison with spacecraft observations. For the 12 December 2008 Earth-directed CME event, we compute ensembles using the Heliospheric Upwind eXtrapolation with Time dependencies (HUXt) solar wind model to analyse CME distortion with a structured solar wind and explore hindcast Arrival Time Error (ATE). By highlighting the impact CME shape has on Root-Mean-Square-Error (RMSE) values, we show that time-elongation profiles of fronts captured by the Heliospheric Imager (HI)-1 instrument onboard Solar-TErrestrial RElations Observatory (STEREO) mission matches those of the modelled CME nose and flank and can therefore be used to infer details of the longitudinal extent of the CME. We then show that accounting for CME distortion is important in enabling accurate estimates of the CME arrival at Earth. This can be achieved by either using observations of multiple features in HI data to infer CME evolution or mapping the solar wind back to a lower inner boundary to allow CMEs to be distorted close to the Sun. For the event studied, we show that these two approaches resulted in a reduced RMSE by at least 19% compared to tracking the flank only or when compared to the CME deterministic run the RMSEs fell by 12% and 22% respectively, and obtain ATE values of less than three hours. By these approaches, the lead time value is assessed as a function of HI observation quantity.

Item Type	Thesis (PhD)
URI	https://reading-clone.eprints-hosting.org/id/eprint/115818
Item Type	Thesis
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Date on Title Page	May 2023
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