Inference of Hidden States by Coupled Thermosphere-Ionosphere Data Assimilation: Applications to Observability and Predictability of Neutral Mass Density

The ionosphere and thermosphere are a tightly coupled system, thus the predictability and observability of one subsystem affects that of the other. In contrast to the ionosphere, which is relatively well monitored by diverse instrumentation techniques, monitoring of the thermosphere's state is limited. This asymmetric observing capability of the upper atmosphere impedes our ability to predict the dynamic behaviors of this coupled system as a whole. This chapter demonstrates how state-of-the-art dynamical data assimilation approaches facilitate inference of hidden thermospheric states from abundant ionospheric observations, by systematically incorporating coupling between neutral and plasma species into the process of data assimilation as well as forecasting. Observing system simulation experiments and observing system experiments presented in this chapter suggest that neutral temperature as well as neutral compositions and winds can be well inferred from abundant GNSS radio occultation ionospheric observations. A comparison to independent CHAMP mass density measurements shows that assimilation experiments of actual COSMIC electron density profiles into the NCAR Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) can reduce the bias existing in the TIEGCM control simulation up to 50%. Ensemble forecast simulations suggest that initialization of TIEGCM by the coupled thermosphere-ionosphere data assimilation significantly improves the mass density forecasting, with its impact lasting longer than 3 days under geomagnetic quiet conditions.