Swarm is the European Space Agency (ESA)'s first Earth observation constellation mission, which was launched in 2013 to study the geomagnetic field and its temporal evolution. Two Langmuir probes aboard each of the three Swarm satellites provide in situ measurements of plasma parameters, which contribute to the study of the ionospheric plasma dynamics. To maintain a high data quality for scientific and technical applications, the Swarm products are continuously monitored and validated via science-oriented diagnostics. This paper presents an overview of the data quality of the Swarm Langmuir probes' measurements. The data quality is assessed by analysing short and long data segments, where the latter are selected to be sufficiently long enough to consider the impact of the solar activity. Langmuir probe data have been validated through comparison with numerical models, other satellite missions, and ground observations. Based on the outcomes from quality control and validation activities conducted by ESA, as well as scientific analysis and feedback provided by the user community, the Swarm products are regularly upgraded. In this paper, we discuss the data quality improvements introduced with the latest baseline, and how the data quality is influenced by the solar cycle. In particular, plasma measurements are more accurate in day-side regions during high solar activity, while electron temperature measurements are more reliable during night side at middle and low latitudes during low solar activity. The main anomalies affecting the Langmuir probe measurements are described, as well as possible improvements in the derived plasma parameters to be implemented in future baselines.

The Swarm satellites were launched on November 22, 2013, and carry accelerometers and GPS receivers as part of their scientific payload. The GPS receivers do not only provide the position and time for the magnetic field measurements, but are also used 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 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. In this paper, we describe the new, improved four-stage processing that is applied 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 manually removed using a dedicated software tool. The second stage is the calibration of the accelerometer measurements against the non-gravitational 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 are merged with the non-gravitational accelerations derived from the observations of 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 present the first results of the processing of Swarm C acceleration measurements from June 2014 to May 2015. We started with Swarm C because its acceleration measurements contain much less disturbances than those of Swarm A and have a higher signal-to-noise ratio than those of Swarm B. The latter is caused by the higher altitude of Swarm B as well as larger noise in the acceleration measurements of Swarm B. We show the results of each processing stage, highlight the difficulties encountered, and comment on the quality of the thermospheric neutral density data set.