Ensemble Modeling of CMEs Using the WSA-ENLIL+Cone Model.

Ensemble modeling of coronal mass ejections (CMEs) provides a probabilistic forecast of CME arrival time that includes an estimation of arrival-time uncertainty from the spread and distribution of predictions and forecast confidence in the likelihood of CME arrival. The real-time ensemble modeling of CME propagation uses the Wang-Sheeley-Arge (WSA)-ENLIL+Cone model installed at the Community Coordinated Modeling Center (CCMC) and executed in real-time at the CCMC/Space Weather Research Center. The current implementation of this ensemble-modeling method evaluates the sensitivity of WSA-ENLIL+Cone model simulations of CME propagation to initial CME parameters. We discuss the results of real-time ensemble simulations for a total of 35 CME events that occurred between January 2013 - July 2014. For the 17 events where the CME was predicted to arrive at Earth, the mean absolute arrival-time prediction error was 12.3 hours, which is comparable to the errors reported in other studies. For predictions of CME arrival at Earth, the correct-rejection rate is 62 %, the false-alarm rate is 38 %, the correct-alarm ratio is 77 %, and the false-alarm ratio is 23 %. The arrival time was within the range of the ensemble arrival predictions for 8 out of 17 events. The Brier Score for CME arrival-predictions is 0.15 (where a score of 0 on a range of 0 to 1 is a perfect forecast), which indicates that on average, the predicted probability, or likelihood, of CME arrival is fairly accurate. The reliability of ensemble CME-arrival predictions is heavily dependent on the initial distribution of CME input parameters ( e.g. speed, direction, and width), particularly the median and spread. Preliminary analysis of the probabilistic forecasts suggests undervariability, indicating that these ensembles do not sample a wide-enough spread in CME input parameters. Prediction errors can also arise from ambient-model parameters, the accuracy of the solar-wind background derived from coronal maps, or other model limitations. Finally, predictions of the K geomagnetic index differ from observed values by less than one for 11 out of 17 of the ensembles and K prediction errors computed from the mean predicted K show a mean absolute error of 1.3. [ABSTRACT FROM AUTHOR]