The Swarm mission flies a constellation of three identical satellites, which carry not only technologically advanced magnetometers but also other important and fundamental instruments, such as GPS receivers and accelerometers. The GPS data are mainly used for precise orbit determination (POD). In addition, a POD approach developed at TU Delft, converts Swarm GPS information into accelerations: the gravitational accelerations are modelled with high fidelity, whereas the non-gravitational accelerations are estimated with a Kalman filter strategy. The resulting GPSderived accelerations for all three Swarm satellites are converted directly into thermosphere neutral density data. The GPS-derived products also supplement the accelerometer-derived data of Swarm C. Furthermore, a combination of the non-gravitational acceleration derived from the GPS receiver and the measurements of the accelerometer for Swarm C resulted in the recently released accelerometer products. The latest improvements of the processing associated to the new high-fidelity geometry and the comparison between the GPS-only and accelerometer-derived data are presented in this work. Moreover, the most recent thermospheric neutral density data show signs of a very deep solar minimum, similar to the one in 2008. These data, together with their comparisons with several thermosphere models, are also included in the presentation. @en

The Swarm satellites carry accelerometers and GPS receivers as part of their scientific payload. The GPS receivers are not only used for locating the position and time of the magnetic measurements, but also for determining non-gravitational forces like drag and radiation pressure acting on the spacecraft. The accelerometers measure these forces directly, at much finer resolution than the GPS receivers, from which thermospheric neutral densities and potentially winds can be derived. Unfortunately, the acceleration measurements suffer from a variety of disturbances, the most prominent being slow temperature-induced bias variations and sudden bias changes. These disturbances required significant changes to the processing algorithms, which as a side effect caused a significant delay of the accelerometer data release. In this presentation, we describe the new processing that is required for transforming the disturbed acceleration measurements into scientifically valuable thermospheric neutral densities. In the first stage, the sudden bias changes in the acceleration measurements are removed using a dedicated software tools. We present a new option of automated step detection and correction, which should speed up the accelerometer data release. The second stage is the calibration of the accelerometer measurements against the nongravitational accelerations derived from the GPS receiver, which includes the correction for the slow temperature-induced bias variations. The identification of validity periods for calibration and correction parameters is part of the second stage. In the third stage, the calibrated and corrected accelerations a merged with the non-gravitational accelerations derived from the GPS receiver by a weighted average in the spectral domain, where the weights depend on the frequency. The fourth stage consists of transforming the corrected and calibrated accelerations into thermospheric neutral densities. We describe the methods used in each stage, highlight the difficulties encountered, and comment on the quality of the thermospheric neutral density data set. @en

The Swarm satellites carry accelerometers as part of their scientific payload. These instruments measure the non-gravitational acceleration due to forces like drag or radiation pressure acting on the spacecraft, from which thermospheric neutral densities and potentially winds can be derived. Unfortunately, the acceleration measurements suffer from a variety of perturbations, the most prominent being slow temperature-induced bias variations and sudden bias changes. Other less prominent perturbation includes spikes and artificial periodic signals. Though all perturbation are visible in the measurements of all Swarm accelerometers, their severity is much different for the three Swarm satellites. In this presentation, we illustrate all known disturbances and assess their severity for scientific exploitation of the accelerometer data separately for each Swarm satellite. @en