A local-scale data assimilation approach for reconstructing boundary conditions to drive physics-based simulations of auroral events

The high-latitude auroral ionosphere and its dynamics play a crucial role in our understanding of space weather phenomena. The auroral system is incredibly complicated in that it involves exchange of mass, momentum, and energy with both the magnetosphere and thermosphere, exemplifying the concept of a complex “system of interacting systems” often used to describe the geospace environment. Ground- and space-based instruments offer crucial insights into specific ionospheric parameters but cannot provide a complete picture of the ionospheric dynamics at play for any given event due to limited fields of view and sampling. This necessitates the use of physics-based models for developing detailed understanding of various processes at play in the overarching system. However, local-scale models of auroral dynamics require accurate boundary conditions to preserve realism. This study adopts a data assimilation approach for producing two-dimensional reconstructions of ionospheric potential and precipitation boundary conditions that are then used as input to a physics-based model to simulate the ionospheric dynamics near auroral features. We present multiple auroral events occurring during a campaign that included measurements from the Poker Flat Incoherent Scatter Radar (PFISR), co-located digital all-sky camera (DASC), magnetometers, and additional high frequency radar instrumentation, which were operated in conjunction with nightly overpasses of the Swarm satellite constellation. These data are used to produce 2D ionospheric potential reconstructions via the inversion method of Local Mapping of Polar Ionospheric Electrodynamics (LOMPE), extracting quantities such as convection velocities, electric potential, field-aligned currents, and electric fields. These inverted data are then used to drive the Geospace Environment Model of Ion-Neutral Interactions (GEMINI) to generate volumetric and time-dependent simulations of the events, including the plasma’s thermal and electrodynamic quantities. Event dates are chosen based on data availability, distinct event types, and favorable conjunctions between PFISR and Swarm — our main diagnostics for plasma flow. The demonstrated process of data analysis, reconstruction, and modeling has the potential to deepen our understanding of auroral physics and its implications both at local and global scales in terms of ionospheric density and temperature structure, preconditioning for instabilities in the ionospheric plasma, and coupling to neutral atmospheric heating and acceleration.