Speaker
Description
Geomagnetic substorms are major phenomena in the magnetosphere-ionosphere system that intensify the aurora and often pose a threat to technology on Earth and in geospace. Substorms are identifiable through a strong westward electrojet that forms to close the substorm current wedge, which creates a recognizable peak in the AL index. Global magnetohydrodynamics (MHD)-based models struggle to reproduce key features of substorms largely due to how they handle auroral precipitation, the primary driver of conductance in the ionosphere. Ionospheric conductance directs the current channels that form in the ionosphere, controlling the location and strength of ground magnetic disturbances. The usage of ideal MHD models necessitates multiple assumptions when calculating electron precipitation into the ionosphere, as there is no separate information for ions and electrons. The Space Weather Modeling Framework (SWMF) has the ability to calculate auroral precipitation using the Magnetosphere Ionosphere Thermosphere (MAGNIT) Auroral Precipitation Model, but the limitations of ideal MHD impede accuracy.
In this poster, we describe a new method for overcoming these impediments to create more accurate, physics-driven precipitation and conductance and produce better substorm simulations. The MAGNIT model has been expanded to couple directly to separately calculated electron temperatures in the Block Adaptive Tree Solar-wind Roe Upwind Scheme (BATS-R-US) MHD model. This removes one of the major assumptions made when calculating electron precipitation from ideal MHD. Using the new capabilities from MAGNIT, the SWMF is able to reproduce auroral substorm features more accurately than with previous conductance models or prototypical versions of MAGNIT. These improvements in conductance have global effects on the simulation, improving the accuracy of strong westward electrojets and the ground disturbances measured by virtual magnetometers. This poster demonstrates the new capabilities of the SWMF, compares results of conductance and ground magnetic disturbances to previously available conductance models, and shows data-model comparisons to validate electrojet signatures measured in auroral indices.
