  The first systematic comparison between Swarm-C accelerometer-derived
thermospheric density and both empirical and physics-based model results using
multiple model performance metrics is presented. This comparison is performed
at the satellite's high temporal 10-s resolution, which provides a meaningful
evaluation of the models' fidelity for orbit prediction and other space weather
forecasting applications. The comparison against the physical model is
influenced by the specification of the lower atmospheric forcing, the
high-latitude ionospheric plasma convection, and solar activity. Some insights
into the model response to thermosphere-driving mechanisms are obtained through
a machine learning exercise. The results of this analysis show that the
short-timescale variations observed by Swarm-C during periods of high solar and
geomagnetic activity were better captured by the physics-based model than the
empirical models. It is concluded that Swarm-C data agree well with the
climatologies inherent within the models and are, therefore, a useful data set
for further model validation and scientific research.
