Ensemble CME Modeling Constrained by Heliospheric Imager Observations

Abstract

Predicting the arrival of coronal mass ejections (CMEs) is one key objective of space weather forecasting. In operational space weather forecasting, solar wind numerical models are used for this task and ensemble techniques are being increasingly explored as a means to improve these forecasts. Currently, these forecasts are not constrained by the available in situ and remote sensing observations, such as those from the heliospheric imagers (HIs) on the National Aeronautics and Space Administration's (NASA's) STEREO spacecraft, which record white‐light images of solar wind and CMEs. We report case studies of four CMEs and show how HI observations can be used to improve the skill and reduce the uncertainty of ensemble hindcasts of these events. Using a computationally efficient solar wind model, we produce 200‐member ensemble hindcasts, perturbing the modeled CME parameters within uniform distributions about the best estimates. By comparing the trajectory of the modeled CME flanks with HI observations, we compute a weight for each ensemble member. Weighting the ensemble distribution of CME arrival times improves the skill and reduces the hindcast uncertainty of each event. For these four events, the weighted ensembles show a mean reduction in arrival time error of 20.1 ± 4.1%, and a mean reduction in arrival time uncertainty of 15.0 ± 7.2%, relative to the unweighted ensembles. This technique could be applied in operational space weather forecasting, if real‐time HI observations were available. Therefore, as NASA and the European Space Agency are currently planning the next space weather monitoring missions, our proof‐of‐concept study provides some evidence of the potential value of including HIs on these missions.