Ensemble Prediction of a Halo Coronal Mass Ejection Using Heliospheric Imagers

Abstract

The Solar TErrestrial RElations Observatory (STEREO) and its heliospheric imagers (HIs) have provided us the possibility to enhance our understanding of the interplanetary propagation of coronal mass ejections (CMEs). HI‐based methods are able to forecast arrival times and speeds at any target and use the advantage of tracing a CME's path of propagation up to 1 AU and beyond. In our study, we use the ELEvoHI model for CME arrival prediction together with an ensemble approach to derive uncertainties in the modeled arrival time and impact speed. The CME from 3 November 2010 is analyzed by performing 339 model runs that are compared to in situ measurements from lined‐up spacecraft MErcury Surface, Space ENvironment, GEochemistry, and Ranging and STEREO‐B. Remote data from STEREO‐B showed the CME as halo event, which is comparable to an HI observer situated at L1 and observing an Earth‐directed CME. A promising and easy approach is found by using the frequency distributions of four ELEvoHI output parameters, drag parameter, background solar wind speed, initial distance, and speed. In this case study, the most frequent values of these outputs lead to the predictions with the smallest errors. Restricting the ensemble to those runs, we are able to reduce the mean absolute arrival time error from 3.5 ± 2.6 to 1.6 ± 1.1 hr at 1 AU. Our study suggests that L1 may provide a sufficient vantage point for an Earth‐directed CME, when observed by HI, and that ensemble modeling could be a feasible approach to use ELEvoHI operationally.

Tracking and Validating ICMEs Propagating Toward Mars Using STEREO Heliospheric Imagers Combined With Forbush Decreases Detected by MSL/RAD

“…The ElEvoHI implementation is currently still under development and has not yet been applied automatically to large data sets such as the HELCATS catalog. Amerstorfer et al () have applied ElEvoHI ensemble modeling to a case study of one event and were able to constrain the uncertainties to less than ±2 hr, which is a very promising result.…”

“…Also, the uncertainty in the elongation value of the last 10 points may be larger due to the CME appearing more faint in the HI images as it expands. This extrapolation method should thus be seen as a first step toward allowing a variation of the CME speed with HI fitting methods (elaborated by Amerstorfer et al, ; Rollett et al, ; Tucker‐Hood et al, ) but needs to be taken with a grain of salt due to the abovementioned issues.…”

Incorporation of Heliospheric Imagery Into the CME Analysis Tool for Improvement of CME Forecasting

“…In recent years, it has become increasingly clear that ensemble modeling could also improve space weather forecasting (Henley & Pope, ; Murray, ; Riley et al, ). Many studies have been conducted applying ensemble modeling to CME forecasting (e.g., Amerstorfer et al, ; Cash et al, ; Emmons et al, ; Lee et al, ; Lee et al, ), including Mays et al () who applied ensemble modeling to an operational system. Amerstorfer et al () have also applied ensemble modeling to HI observations of CMEs.…”

“…The studies previously mentioned by Howard and Tappin (), Lugaz et al (), and Colaninno et al () all employed HI data. Harrison et al () have already argued that HI can be used to improve space weather forecasting, and Amerstorfer et al () have performed ensemble runs on CMEs using the HI data.…”

Benchmarking CME Arrival Time and Impact: Progress on Metadata, Metrics, and Events

“…From this, it can provide arrival times and arrival speed for any position in the inner heliosphere. The Ellipse Evolution Heliospheric Imager (HI) model (ElEvoHI; Amerstorfer et al, ) is an updated version of this model that uses only HI observations (in combination with DBM) to determine all of the input parameters for the elliptical CME model.…”