Data Constrained Coronal Mass Ejections in A Global Magnetohydrodynamics Model

TL;DR

This paper introduces a data-constrained, first-principles MHD model for simulating and forecasting coronal mass ejections (CMEs) by integrating observational data to accurately predict CME propagation and magnetic impact at 1 AU.

Contribution

It develops a novel data-driven CME model that combines a global MHD solar wind simulation with an automated flux rope initialization based on observational data.

Findings

Successfully simulates realistic CMEs with high fidelity.

Demonstrates capability to predict CME arrival time and magnetic field at 1 AU.

Automates CME initiation process reducing manual intervention.

Abstract

We present a first-principles-based coronal mass ejection (CME) model suitable for both scientific and operational purposes by combining a global magnetohydrodynamics (MHD) solar wind model with a flux rope-driven CME model. Realistic CME events are simulated self-consistently with high fidelity and forecasting capability by constraining initial flux rope parameters with observational data from GONG, SOHO/LASCO, and STEREO/COR. We automate this process so that minimum manual intervention is required in specifying the CME initial state. With the newly developed data-driven Eruptive Event Generator Gibson-Low (EEGGL), we present a method to derive Gibson-Low (GL) flux rope parameters through a handful of observational quantities so that the modeled CMEs can propagate with the desired CME speeds near the Sun. A test result with CMEs launched with different Carrington rotation magnetograms are shown. Our study shows a promising result for using the first-principles-based MHD global model as a forecasting tool, which is capable of predicting the CME direction of propagation, arrival time, and ICME magnetic field at 1 AU (see companion paper by Jin et al. 2016b).