Electron Energization With Bursty Bulk Flows: MHD With Embedded Particle-In-Cell Simulation

Using a two-way coupled magnetohydrodynamics with embedded kinetic physics model, we perform a substorm event simulation to study electron velocity distribution functions (VDFs) evolution associated with Bursty Bulk Flows (BBFs). The substorm was observed by Magnetospheric Multiscale satellite on 16 May 2017. The simulated BBF macroscopic characteristics and electron VDFs agree well with observations. The VDFs from the BBF tail to its dipolarization front (DF) during its earthward propagation are revealed and they show clear energization and heating. The electron pitch angle distributions (PADs) at the DF are also tracked, which show interesting energy dependent features. Lower energy electrons develop a "two-hump" PAD while the higher energy ones show persist "pancake" distribution. Our study reveals for the first time the evolution of electron VDFs as a BBF moves earthward using a two-way coupled global and kinetic model, and provides valuable contextual understanding for the interpretation of satellite observations. Bursty bulk flows (BBFs) are identified as the fast earthward-propagating flows from magnetic reconnection in the Earth's magnetotail. BBFs are related to particle energization and heating processes as reported by satellite observations. For the first time, we use a novel numerical model that simulates kinetic physics directly in a global model. The electron velocity distribution functions extracted from multiple locations associated with BBF show good agreements with the satellite in situ observations. The energization and heating of the electrons associated with BBF and their energy-dependent pitch angle distributions are revealed. For the first time, we simulate the bursty bulk flow (BBF) events with kinetic physics embedded in a global magnetosphere model The electron velocity distribution functions exhibit different anisotropy features at different locations of the BBF Energy dependent electron pitch angle distribution evolutions are identified in the simulation