GEM: Self-consistent Modeling of the Near-Earth Magnetosphere with Induced Electric Fields

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This project is directed towards the central goal of the NSF Geospace Environment Modeling (GEM) Program, which is to support basic research into the dynamical and structural properties of geospace, leading to the construction of a global Geospace General Circulation Model (GGCM) with predictive capability. An important part in the development of the future GGCM, and the modeling emphasis of the new "Near-Earth Magnetosphere: Plasma, Fields and Coupling" Focus Group, is the creation of inner/middle magnetosphere module(s) that faithfully describe the physics of the plasma transport, as well as the self-consistent interaction between plasma and fields. This project will lead to such a module; it will develop a realistic, 3-D, near-Earth, magnetosphere model of plasma and fields that will include self-consistent magnetic and induced electric fields, the Earth's dipole tilt and an expanded boundary into the plasma sheet at 10 Earth radii from Earth. The numerical model will be verified by comparisons with observed field and plasma data, including in situ data/model comparison and phase space density analysis using model fields. These comparisons will elucidate the influence of the various model features on the resulting magnetospheric structure and dynamics and will also constrain model parameters. The model will accept various magnetic field and plasma boundary conditions (including from global numerical MHD (magnetohydrodynamics) models), and will thus be ready for integration into a GGCM. The research will also result in global maps of computed, self-consistent, inner-magnetospheric plasma distributions, magnetic and electric fields and plasma waves during selected events. These maps will be made available to the community for use in other observational and theoretical space physics applications. A substantial portion of the funding for this project will be used young scientist (the Principal Investigator (PI)), as well as a postdoc and a summer student at Los Alamos National Laboratory (LANL). Ultimately, the project, by contributing to a GGCM with predictive capabilities, will be of value to the National Space Weather Program.