Decent Estimate of CME Arrival time from a Data-assimilated Ensemble in
the Alfvén Wave Solar atmosphere Model (DECADE-AWSoM)
Abstract
Forecasting the arrival time of Earth-directed coronal mass ejections
(CMEs) via physics-based simulations is an essential but challenging
task in space weather research due to the complexity of the underlying
physics and limited remote and in-situ observations of these events.
Data assimilation (DA) techniques can assist in constraining free model
parameters and reduce the uncertainty in subsequent model predictions.
In this study, we show that CME simulations conducted with the Space
Weather Modeling Framework (SWMF) can be assimilated with SOHO LASCO
white-light (WL) observations and solar wind observations at L1 prior to
the CME eruption to improve the prediction of CME arrival time. The L1
observations are used to constrain the model of the solar wind
background into which the CME is launched. Average speed of CME shock
front over propagation angles are extracted from both synthetic WL
images from the Alfv\’en Wave Solar atmosphere Model
(AWSoM) and the WL observations. We observe a strong rank correlation
between the average WL speed and CME arrival time, with the Spearman’s
rank correlation coefficients larger than 0.90 for three events
occurring during different phases of the solar cycle. This enables us to
develop a Bayesian framework to filter ensemble simulations using WL
observations, which is found to reduce the mean absolute error of CME
arrival time prediction from about 13.4$\pm$3.8 hours to
5.1$\pm$3.0 hours. The results show the potential of
assimilating readily available L1 and WL observations within hours of
the CME eruption to construct optimal ensembles of Sun-to-Earth CME
simulations.