Using the Coronal Evolution to Successfully Forward Model CMEs' In Situ Magnetic Profiles

TL;DR

This study links CME deflections and rotations to their magnetic profiles at 1 AU, using coronal modeling and in situ data to improve space weather prediction accuracy.

Contribution

It introduces a method combining ForeCAT and FIDO models to predict CME magnetic profiles based on coronal evolution, enhancing understanding of CME impacts.

Findings

FIDO reproduces magnetic field components with 35% error when scaled.

Best fits reduce average error to 30%.

Predictions are sensitive to CME position and orientation accuracy.

Abstract

Predicting the effects of a coronal mass ejection (CME) impact requires knowing if impact will occur, which part of the CME impacts, and its magnetic properties. We explore the relation between CME deflections and rotations, which change the position and orientation of a CME, and the resulting magnetic profiles at 1 AU. For 45 STEREO-era, Earth-impacting CMEs, we determine the solar source of each CME, reconstruct its coronal position and orientation, and perform a ForeCAT (Kay et al. 2015a) simulation of the coronal deflection and rotation. From the reconstructed and modeled CME deflections and rotations we determine the solar cycle variation and correlations with CME properties. We assume no evolution between the outer corona and 1 AU and use the ForeCAT results to drive the FIDO in situ magnetic field model (Kay et al. 2017a), allowing for comparisons with ACE and Wind observations. We do not attempt to reproduce the arrival time. On average FIDO reproduces the in situ magnetic field for each vector component with an error equivalent to 35% of the average total magnetic field strength when the total modeled magnetic field is scaled to match the average observed value. Random walk best fits distinguish between ForeCAT's ability to determine FIDO's input parameters and the limitations of the simple flux rope model. These best fits reduce the average error to 30%. The FIDO results are sensitive to changes of order a degree in the CME latitude, longitude, and tilt, suggesting that accurate space weather predictions require accurate measurements of a CME's position and orientation.