Improved Basis Functions for Dynamic Calibration of Semi-Empirical Thermospheric Models

Abstract : State-of-the-art satellite drag models require upgrades to meet operational Precision Orbit Determination requirements for collision avoidance, reentry predictions and catalog maintenance. Accurate model representations of the upper atmosphere are not currently possible without the use of data assimilation, or model calibration. Due to incomplete global data sampling in the thermosphere, such calibration has only been successfully demonstrated by fitting the available data to a low-dimensional model. The High Accuracy Satellite Drag Model (HASDM), used by the Space Surveillance Network to track low-earth orbiting satellites, fits recent data to a truncated set of spherical harmonics. In our study, the goal is to replace this low-order spherical harmonic expansion with a set of basis functions better suited to capture the spatial variability and response of the thermosphere. By comparing the base model of HASDM with the Thermosphere-Ionosphere-Electrodynamic General Circulation Model (TIEGCM), we create a new set of orthogonal basis functions that can be used to calibrate semi-empirical models such as HASDM with increased accuracy in the presence of sparse data. We present initial comparisons between the conventional and new approaches.