Global magnetohydrodynamic simulation of the 15 March 2013 coronal mass ejection event-Interpretation of the 30-80 MeV proton flux

Abstract

The coronal mass ejection (CME) event on 15 March 2013 is one of the few solar events in Cycle 24 that produced a large solar energetic particle (SEP) event and severe geomagnetic activity. Observations of SEP from the ACE spacecraft show a complex time-intensity SEP profile that is not easily understood with current empirical SEP models. In this study, we employ a global three-dimensional (3-D) magnetohydrodynamic (MHD) simulation to help interpret the observations. The simulation is based on the H3DMHD code and incorporates extrapolations of photospheric magnetic field as the inner boundary condition at a solar radial distance (r) of 2.5 solar radii. A Gaussian-shaped velocity pulse is imposed at the inner boundary as a proxy for the complex physical conditions that initiated the CME. It is found that the time-intensity profile of the high-energy (>10 MeV) SEPs can be explained by the evolution of the CME-driven shock and its interaction with the heliospheric current sheet and the nonuniform solar wind. We also demonstrate in more detail that the simulated fast-mode shock Mach number at the magnetically connected shock location is well correlated (r_(cc) ≥ 0.7) with the concurrent 30–80 MeV proton flux. A better correlation occurs when the 30–80 MeV proton flux is scaled by r^(−1.4)(r_(cc) = 0.87). When scaled by r^(−2.8), the correlation for 10–30 MeV proton flux improves significantly from r_(cc) = 0.12 to r_(cc) = 0.73, with 1 h delay. The present study suggests that (1) sector boundary can act as an obstacle to the propagation of SEPs; (2) the background solar wind is an important factor in the variation of IP shock strength and thus plays an important role in manipulation of SEP flux; (3) at least 50% of the variance in SEP flux can be explained by the fast-mode shock Mach number. This study demonstrates that global MHD simulation, despite the limitation implied by its physics-based ideal fluid continuum assumption, can be a viable tool for SEP data analysis.

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