Assessing Potential Radio Occultation Constellations for Specifying Neutral Mass Density

The largest obstacle to managing satellites in low Earth orbit (LEO) is accurately forecasting the neutral mass densities that appreciably impact atmospheric drag. Empirical thermospheric models are often used to estimate neutral densities but they struggle to forecast neutral densities during geomagnetic storms when they are highly variable. Physics-based models are thus increasingly turned to for their ability to describe the dynamical evolution of neutral densities. However, these models require observations to constrain dynamical state variables to be able to forecast mass densities with adequate fidelity. The LEO environment has scarce neutral state observations. Here we demonstrate in simulated experiments the estimation of neutral densities using a physics-based, data assimilation approach with ionospheric observations. Using a coupled thermosphere-ionosphere (T-I) model, the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM), we assimilate electron density profiles (EDPs) derived from radio occultation (RO) observations. Assimilation is done with an Ensemble Adjustment Kalman Filter (EAKF) to perform direct-updates to neutral states using EDPs. These direct-updates use a linear regression fit obtained from ensemble statistics of T-I states. Four potential RO constellations with varying altitude and inclination angle are assessed for their impact on improving neutral density estimation. The simulation period focuses on the St. Patrick’s day storm in 2015, covering both quiet and geomagnetic storm conditions. We build on earlier work in utilizing a vast and growing data source in RO, with physics-based modeling, to overcome our limited number of neutral observations.