Predicting the Time-of-Arrival of Coronal Mass Ejections at Earth From Heliospheric Imaging Observations

TL;DR

This study develops a new method to predict the arrival time of coronal mass ejections at Earth using heliospheric imaging, achieving errors comparable to traditional coronagraph-based methods.

Contribution

The paper introduces the Elliptical Conversion (ElCon) technique combined with a physical drag model to improve CME ToA predictions from heliospheric images.

Findings

Mean ToA error of 1.6 hours with a standard deviation of 8 hours.

Achieved a mean absolute error of 6.9 hours.

Heliospheric imagers provide ToA estimates similar in accuracy to coronagraphs.

Abstract

The Time-of-Arrival (ToA) of coronal mass ejections (CME) at Earth is a key parameter due to the space weather phenomena associated with the CME arrival, such as intense geomagnetic storms. Despite the incremental use of new instrumentation and the development of novel methodologies, ToA estimated errors remain above 10 hours on average. Here, we investigate the prediction of the ToA of CMEs using observations from heliospheric imagers, i.e., from heliocentric distances higher than those covered by the existent coronagraphs. In order to perform this work we analyse 14 CMEs observed by the heliospheric imagers HI-1 onboard the twin STEREO spacecraft to determine their front location and speed. The kinematic parameters are derived with a new technique based on the Elliptical Conversion (ElCon) method, which uses simultaneous observations from the two viewpoints from STEREO. Outside the field of view of the instruments, we assume that the dynamics of the CME evolution is controlled by aerodynamic drag, i.e., a force resulting from the interaction with particles from the background solar wind. To model the drag force we use a physical model that allows us to derive its parameters without the need to rely on drag coefficients derived empirically. We found a CME ToA mean error of $1.6\pm8.0$ hours ToA and a mean absolute error of $6.9\pm3.9$ hours for a set of 14 events. The results suggest that observations from HI-1 lead to estimates with similar errors to observations from coronagraphs.