Thermospheric Neutral Density Specification and Forecasting via Driver Estimation and Assimilation of COSMIC Radio Occultation Data

Abstract:

The population of satellites in Earth’s orbit will continue to increase in the coming years, increasing the need to precisely manage satellite positions and space debris. The main source of error in satellite position forecasting comes from the uncertainty in the aerodynamic drag force that is predominately caused by uncertainty in thermospheric neutral densities. While a global monitoring system does not exist for neutral density, total electron content (TEC) measurements from radio occultation by the COSMIC and the recently launched COSMIC-2 can be used for neutral density specification and forecasting. This can be achieved using data assimilation methods such as the ensemble Kalman filter and with help from the strong coupling of the thermosphere and ionosphere that is modeled through NCAR’s Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM). In addition to estimating thermospheric states, solar and geomagnetic drivers F10.7 and Kp index can be estimated through linearized least-squares minimalization between TIEGCM neutral densities and in-situ neutral density data provided by satellites such as CHAMP and Swarm. Performing this minimalization allows for the reduction of model bias. This presentation will present initial results from Observing System Experiments with COSMIC observations to compare estimated neutral densities against high quality neutral densities provided by in-situ satellite observations. Satellite position error mapping and uncertainty quantification are being performed via Monte-Carlo simulations propagating the satellite state through the estimated neutral density field and its uncertainty to compare true and estimated satellite position.