Thermosphere densities derived from Swarm GPS observations. Issue 7 (1st April 2020)

• Record Type: Journal Article
• Authors: van den IJssel, Jose; Doornbos, Eelco; Iorfida, Elisabetta; March, Günther; Siemes, Christian; Montenbruck, Oliver
• Is Part Of: Advances in space research. Volume 65:Issue 7(2020)
• Page Start: 1758
• Page End: 1771
• Publication Date: 2020-04-01
• Subjects: Swarm -- GPS -- Thermosphere density; Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2020.01.004
• Languages: English
• ISSNs: 0273-1177

Abstract

Highlights: GPS-derived thermosphere densities are available for all Swarm satellites. These densities have a temporal resolution of about 20 min. Two recent processing modifications improve the density retrieval accuracy. Abstract: After the detection of many anomalies in the Swarm accelerometer data, an alternative method has been developed to determine thermospheric densities for the three-satellite mission. Using a precise orbit determination approach, non-gravitational and aerodynamic-only accelerations are estimated from the high-quality Swarm GPS data. The GPS-derived non-gravitational accelerations serve as a baseline for the correction of the Swarm-C along-track accelerometer data. The aerodynamic accelerations are converted directly into thermospheric densities for all Swarm satellites, albeit at a much lower temporal resolution than the accelerometers would have been able to deliver. The resulting density and acceleration data sets are part of the European Space Agency Level 2 Swarm products. To improve the Swarm densities, two modifications have recently been added to our original processing scheme. They consist of a more refined handling of radiation pressure accelerations and the use of a high-fidelity satellite geometry and improved aerodynamic model. These modifications lead to a better agreement between estimated Swarm densities and NRLMSISE-00 model densities. The GPS-derived Swarm densities show variations due to solar and geomagnetic activity, as well as seasonal, latitudinal and diurnal variations. For low solar activity, however, the aerodynamic signal experienced by the Swarm satellites is very small, and therefore it is more difficult to accurately resolve latitudinal density variability using GPS data, especially for the higher-flying Swarm-B satellite. Therefore, mean orbit densities are also included in the Swarm density product.