SM041-0001
An Information-Theoretical Approach to Analyzing Magnetosphere-Ionosphere Coupling Processes in Hybrid Simulations

Tuesday, 15 December 2020
Poster
Wesley Martin1, Jay Johnson2, Lei Cheng3, Yu Lin4, Simon Wing5, Xueyi Wang4, J D Perez4 and Xu Zhang6, (1)Andrews University, Physics Department, Berrien Springs, MI, United States, (2)Andrews University, Department of Engineering, Berrien Springs, MI, United States, (3)Florida Institute of Technology, Physics Department, Melbourne, FL, United States, (4)Auburn University, Physics Department, Auburn, AL, United States, (5)Johns Hopkins University, Baltimore, MD, United States, (6)University of California Los Angeles, Institute of Geophysics and Planetary Physics, Los Angeles, CA, United States
Abstract:
Recent simulations of tail dynamics using the Auburn Global Hybrid Code in 3-D (ANGIE3D) suggest that tail flows are closely related to the dynamics of Alfven waves propagating from the magnetotail to the ionosphere. To understand the dynamical coupling process described by the simulation, we consider the simulated time series of plasma sheet structures associated with tail flows and the Poynting flux into the ionosphere. We present 2-D animations showing how the ionospheric Poynting flux responds to plasma sheet parameters (such as velocity, Bz, entropy, etc.) identifying linear and nonlinear signatures in the response, including the timescale at different locations in the plasma sheet. We utilize transfer entropy [Schrieber, 2001] to identify causal relationships among reconnection events, tail flows, and Poynting flux into the ionosphere. Results suggest that flows in the plasma sheet are the primary driver of the Poynting flux, which is consistent with expectations. The plots can also be used to infer the radial location where the Alfven waves are generated. This work demonstrates how system science tools can be used in conjunction with complex simulations to describe the underlying system dynamics and provide a framework for understanding the interrelated components, functions, and causalities in the system.