Neutral thermospheric density is an essential quantity required for precise orbit determination of satellites, collision avoidance of satellites, re-entry prediction of satellites or space debris, and satellite lifetime assessments. Empirical models of the thermosphere fail to provide sufficient estimates of neutral thermospheric density along the orbits of satellites by reason of approximations, assumptions and a limited temporal resolution. At high solar activity these estimates can be off by 70% when comparing to observations at 12 hourly averages. Nowadays, neutral density is regularly observed with satellite accelerometers on board of low Earth orbiting satellites like CHAMP, GOCE, GRACE, GRACE-FO, or Swarm. When assimilating such along-track information into global models of thermosphere-ionosphere dynamics, it has been often observed that only a very local subdomain of the model grid around the satellite’s position is updated. To extend the impact to the entire model domain we suggest a new two-step approach: We use accelerometer derived neutral densities from the CHAMP mission in a first step to calibrate an empirical thermosphere density model (NRLMSIS 2.0). In a second step, we assimilate—for the first time—densities predicted for a regular three dimensional grid into the TIE-GCM (Thermosphere Ionosphere Electrodynamics General Circulation Model). Data assimilation is performed using the Local Error-Subspace Transform Kalman Filter provided by the Parallel Data Assimilation Framework (PDAF). We test the new approach using a two week long period containing the 5 April 2010 Geomagnetic storm. Accelerometer derived neutral densities from the GRACE mission are used for additional evaluation. We demonstrate that the two-step approach globally improves the simulation of thermospheric density. We were not able to improve the density prediction at altitudes higher than about 350 km, but we could significantly improve the predication at the altitude of CHAMP. In fact, the offset between the accelerometer derived densities and the model prediction is reduced by two orders of magnitude when applying the two-step approach. The implication is that our approach allows one to much better ’transplant’ the precise CHAMP thermospheric density measurements to satellites flying at a similar altitude.
