Data-driven Modeling of the Global Equatorial Electrojet Variability Using Ground-based Magnetometer Data

The equatorial electrojet (EEJ) is a manifestation of ionospheric electrodynamics. Day-to-day changes of the EEJ resulting from E region dynamo processes are primarily driven by highly variable atmospheric tides propagating up from the lower and middle atmosphere. Observational studies with ground-based data can provide high-cadence temporal variations locally but fall short of providing a global perspective. On the other hand, analysis of global satellite data provides increased spatial coverage but does often require aggregation of data over months to reach temporal/spatial statistics, but they provide a global view. Current numerical models are still limited in their ability to fully capture the spectrum and all mechanisms influencing vertical propagation of tides. In this study, we present a new data-driven approach to modeling the day-to-day EEJ variability from ground-based magnetometer data. The approach is based on an ensemble transform adjustment method and is applied to the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) lower boundary conditions (LBCs) at about 97 km altitude to make the model’s tidal characteristics consistent with observed ground-level magnetic perturbations. Our case study shows hourly EEJ variations which can be estimated globally from several, globally distributed ground-based magnetometers data. This approach yields a good agreement between modeled and observed magnetic perturbations at Low Earth orbit altitudes and even over the Pacific Ocean where the ground-based data coverage is sparse. The analysis results further confirm the past findings that the day-to-day variation of SW2 wind fields plays a key role in generating the variation of the EEJ. The use of continuously available ground-based magnetometer data to constrain the TIE-GCM LBCs is expected to provide an opportunity to investigate how day-to-day tidal variability drives equatorial electrodynamics variability on global scales.