ALBERT

Description: Summary Improving Thermospheric Neutral Density (TND) estimates is important for computing drag forces acting on Low-Earth-Orbit (LEO) satellites and debris. Empirical thermospheric models are often used to compute TNDs for the precise orbit determination experiments. However, it is known that simulating TNDs are of limited accuracy due to simplification of model structure, coarse sampling of model inputs, and dependencies to the calibration period. Here, we apply TND estimates from accelerometer measurements of the Challenging Minisatellite Payload (CHAMP) and the Gravity Recovery and Climate Experiment (GRACE) missions as observations to improve the NRLMSISE-00 model, which belongs to the Mass Spectrometer and Incoherent Scatter (MSIS) family of models. For this, a novel simultaneous Calibration and Data Assimilation (C/DA) technique is implemented that uses the Ensemble Kalman Filter (EnKF) and the Ensemble Square-Root Kalman Filter (EnSRF) as merger. The application of C/DA is unique because it modifies both model-derived TNDs, as well as the selected model parameters. The calibrated parameters derived from C/DA are then used to predict TNDs in locations that are not covered by CHAMP and GRACE orbits, and forecasting TNDs of the next day. The C/DA is implemented using daily CHAMP- and/or GRACE-TNDs, for which compared to the original model, we find 27% and 62% reduction of misfit between model and observations in terms of Root Mean Square Error (RMSE) and Nash Coefficient, respectively. These validations are performed using the observations along the orbital track of the other satellite that is not used in the C/DA during 2003 with various solar activity. Comparisons with another empirical model, i.e., Jacchia-Bowman 2008, indicate that the C/DA results improve these quality measurements on an average range of 50% and 60%, respectively.