Quantifying the uncertainty in CME kinematics derived from geometric modelling of Heliospheric Imager data
Luke Barnard, Mathew Owens, Christopher J. Scott, Mike Lockwood, Curt, A. de Koning, Tanja Amerstorfer, J\"urgen Hinterreiter, Christian M\"ostl,, Jackie Davies, Pete Riley

TL;DR
This study quantifies how solar wind structure affects geometric CME models and ELEvoHI forecast accuracy, revealing biases and optimal observer locations for minimizing errors in space weather prediction.
Contribution
It provides a comprehensive analysis of uncertainties in CME kinematic modeling caused by solar wind variability using extensive simulations and synthetic observations.
Findings
Errors depend on observer location, not CME scenario.
Bias towards overestimating CME apex distances.
L5 region minimizes modeling and arrival time errors.
Abstract
Geometric modelling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modelling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind structure does not affect the evolution of the CME, which is an unquantified source of uncertainty. We use a large number of Cone CME simulations with the HUXt solar wind model to quantify the scale of uncertainty introduced into geometric modelling and the ELEvoHI CME arrival times by solar wind structure. We produce a database of simulations, representing an average, a fast, and an extreme CME scenario, each independently propagating through 100 different ambient solar wind environments. Synthetic heliospheric imager observations of these simulations are then used with a range of geometric models…
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