Evolution of Coronal Mass Ejections in Different Data-Driven Solar Wind Conditions

TL;DR

The paper addresses how magnetogram-derived inner boundary conditions introduce uncertainties in simulated solar wind and CME evolution, impacting space weather predictions. It compares four data-driven boundary maps driving AWSoM within the SWMF and uses the EEG GL flux rope to launch CMEs, analyzing ambient wind structure, CME propagation, and synthetic coronagraphs up to 24 $R_{\odot}$. Results show large map-dependent differences in ambient wind structure and CME evolution, with Case 3 (GONG) fastest, Case 4 (polar-enhanced GONG) exhibiting the largest deflection, and varying mass pile-up and magnetic-energy conversion across cases. The work highlights the importance of magnetogram-related uncertainties in data-driven space weather models and advocates for multi-viewpoint data assimilation and broader parameter studies.

Abstract

Numerical models of the solar wind and coronal mass ejections (CMEs) utilize photospheric magnetic field observations to prescribe the inner boundary conditions for the plasma solutions. These magnetic field data are available to the community through various observational instruments, prepared via different methodologies and/or flux-transport models. The solar wind solution driven by these maps provides the ambient plasma environment into which CMEs travel, coupling, and interacting with the surrounding plasma and governing the CME evolution and propagation in the solar corona and inner heliosphere. In this work, we use different input magnetic field maps for the same time period to drive the global Alfven Wave Solar atmosphere Model (AWSoM). We obtain the ambient solar wind conditions and compare the plasma properties and magnetic morphology in the coronal domain to study the influence of the input maps. To understand how the resulting coronal solutions impact CMEs, we launch eruptions described by analytical flux ropes into these data-driven solutions and compare their evolution in the coronal domain (up to 24 solar radii radially). The CMEs achieve varying speeds, deceleration rates, propagation directions, mass and energies while coupling with the background solar wind. We quantify these differences to show that the different input driving maps can significantly impact the simulated CME propagation in the solar wind plasma. This also highlights the importance of understanding the uncertainties associated with data-driven modeling that become increasingly important in operational models and space weather prediction.

Figures (10)

• Figure 1: ADAPT GONG, ADAPT HMI, GONG and polar enhanced GONG magnetic field maps showing the radial photospheric magnetic field observations for CR2123 in panels a, b, c and d, respectively. The $B_{r}$ field range of $\pm$ 20 G is chosen to highlight the features on the maps. The active region circled in panel (a) indicates the location of flux rope CME insertion, which is same for all the maps.
• Figure 2: Magnetic field morphology of the ambient solar wind. Results are shown for cases 1, 2, 3, 4 that correspond to solutions driven by ADAPT GONG, ADAPT HMI, GONG and polar enhanced GONG maps respectively, for CR2123. Top row: Radial magnetic field ($B_{r}$) at the source surface radius (2.5 $\rm{R}_{\odot}$) for the four cases. Middle row: Open field regions at 1.01 $\rm{R}_{\odot}$ for solar wind solutions driven by four maps in the same order as above. Deep blue regions represent the open field regions and the light blue regions depict the closed field regions. Bottom row: Heliospheric current sheet (gray) extracted from 3D solutions. The translucent equatorial slice (z=0) shows the radial magnetic field in Gauss.
• Figure 3: AWSoM synthesized line of sight EUV images corresponding to SDO/AIA 193 Å (top row) and STEREO-A EUV 195 Å (bottom row) for all four cases.
• Figure 4: Ambient solar wind solution in the meridional plane at time t=0. From top to bottom: proton temperature (K, on log scale), density (cm$^{-3}$, on log scale) and speed (km s$^{-1}$) of the solar wind plasma at time t=0 when the flux rope is inserted in the background solution. Each column shows the AWSoM solution driven by the ADAPT GONG, ADAPT HMI, GONG and polar enhanced GONG map (cases 1, 2, 3, and 4), respectively.
• Figure 5: Propagation of a CME in the meridional plane in the solar wind backgrounds driven by (1) ADAPT GONG, (2) ADAPT HMI, (3) GONG and (4) polar enhanced GONG maps. Top to bottom: The proton temperature (K, on log scale), density (cm$^{-3}$, on log scale) and speed (km/s) of the solar wind background and the CME traveling through it at time t=50 minutes after eruption. The last row shows the CME speed at time t=2 hr 00 min after eruption. The magnetic field lines are overplot to show the magnetic structure of the background and flux rope field.