This study focuses on utilizing the increasing availability of satellite trajectory data from global navigation satellite system-enabled low-Earth orbiting satellites and their precision orbit determination (POD) solutions to expand and refine thermospheric model validation capabilities. The research introduces an updated interface for the GEODYN-II POD software, leveraging high-precision space geodetic POD to investigate satellite drag and assess density models. This work presents a case study to examine five models (NRLMSIS2.0, DTM2020, JB2008, TIEGCM, and CTIPe) using precise science orbit (PSO) solutions of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). The PSO is used as tracking measurements to construct orbit fits, enabling an evaluation according to each model’s ability to redetermine the orbit. Relative in-track deviations, quantified by in-track residuals and root-mean-square errors (RMSe), are treated as proxies for model densities that differ from an unknown true density. The study investigates assumptions related to the treatment of the drag coefficient and leverages them to eliminate bias and effectively scale model density. Assessment results and interpretations are dictated by the timescale at which the scaling occurs. JB2008 requires the least scaling (~-23%) to achieve orbit fits closely matching the PSO within an in-track RMSe of 9 m when scaled over two weeks and 4 m when scaled daily. The remaining models require substantial scaling of the mean density offset (~30-75%) to construct orbit fits that meet the aforementioned RMSe criteria. All models exhibit slight over or under sensitivity to geomagnetic activity according to trends in their 24-hour scaling factors.

Upper thermosphere mass density over the declining phase of solar cycle 23 are investigated using a day-to-night ratio (DNR) of thermosphere properties as a metric to evaluate how much relative change occurs climatologically between day and night. CHAMP observations from 2002-2009, MSIS 2.0 output, and TIEGCM V2.0 simulations are analyzed to assess their relative response in DNR. The CHAMP observations demonstrate nightside densities decrease more significantly than dayside densities as solar flux decreases. This causes a steadily increasing CHAMP mass density DNR from two to four with decreasing solar flux. The MSIS 2.0 nightside densities decrease more significantly than the dayside, resulting in the same trend as CHAMP. TIEGCM V2.0 displays an opposing trend in density DNR with decreasing solar flux due to dayside densities decreasing more significantly than nightside densities. A sensitivity analysis of the two models reveals the TIEGCM V2.0 to have greater sensitivity in temperature to levels of solar flux, while MSIS 2.0 displayed a greater sensitivity in mean molecular weight. The pressure DNR from both models contributed the most to the density DNR value at 400 km. As solar flux decreases, the two models’ estimate of pressure DNR deviate appreciably and trend in opposite directions. The TIEGCM V2.0 dayside temperatures during middle-to-low solar flux are too cold relative to MSIS 2.0. Increasing the dayside temperature values by about 50 – 100 K and decreasing the nightside temperature slightly would bring the TIEGCM V2.0 into better agreement with MSIS 2.0 and CHAMP observations.