Day 4

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Paper title Precise orbits and thermospheric densities for the Swarm satellite mission
  1. Jose van den IJssel Delft University of Technology Speaker
  2. Christian Siemes TU Delft
  3. Pieter Visser TU Delft/Faculty of Aerospace Engineering
Form of presentation Poster
  • B2. Earth Explorer missions
    • B2.05 Swarm - ESA's Extremely Versatile Magnetic Field and Geospace Explorer
Abstract text In the framework of the Swarm Data, Innovation, and Science Cluster, precise science orbits (PSO) are computed for the Swarm satellites from on board GPS observations. These PSO consist of a reduced-dynamic orbit to precisely geotag the magnetic and electric field observations, and a kinematic solution with covariance information, which can be used to determine the Earth’s gravity field. In addition, high resolution thermospheric densities are computed from on board accelerometer data. Due to accelerometer instrument issues, these data are currently only available for Swarm-C. For Swarm-A, a first data set will also become available soon, which is limited to the early mission phase. Therefore, also GPS-derived thermospheric densities are computed. These densities have a lower temporal resolution of about 20 minutes, but are available for all Swarm satellites during the entire mission. The Swarm density data can be used to study the influence of solar and geomagnetic activity on the thermosphere.

We will present the current status of the processing strategy that is used to derive the Swarm PSO and thermospheric densities and show recent results. For the PSO, our processing strategy has recently been updated and now includes a more realistic satellite panel model for solar and Earth radiation pressure modelling, integer ambiguity fixing and a screening procedure to reduce the impact of ionospheric scintillation induced errors. Validation by independent Satellite Laser Ranging data shows the Swarm PSO have a high accuracy, with an RMS of the laser residuals of about 1 cm for the reduced-dynamic orbits, and slightly higher values for the kinematic orbits. For the thermospheric densities, our processing strategy includes a high-fidelity satellite geometry model and the SPARTA gas-dynamics simulator for gas-surface interaction modelling. Comparisons between Swarm densities and NRLMSIS model densities show noticeable scaling differences, which indicates the potential of the Swarm densities to contribute to thermosphere model improvement. The accuracy of the Swarm densities is dependent on the aerodynamic signal size. For low solar activity, the error in the radiation pressure modelling becomes significant, especially for the higher-flying Swarm-B satellite. In a next step, we plan to further improve the Swarm densities by including a more sophisticated radiation pressure modelling.