Uncertainty of thermosphere mass density observations derived from accelerometer and GNSS tracking data.

Thermosphere mass density and crosswind can be derived from accelerometer and GNSS tracking data. However, present datasets are often provided without comprehensive uncertainty specifications. We present a newly developed method that propagates measurement noise and errors in the satellite specification, thermosphere models, and radiation flux data to density observations to quantify their uncertainty. We focus specifically on density observations derived only from GNSS tracking data, which are limited in resolution along the orbit due to unavoidable smoothing. While the method can be applied to simulated and real data, making it useful for existing datasets and mission design, we demonstrated it using data from the GRACE B satellite. First, we compare the aerodynamic acceleration derived separately from the accelerometer and GNSS tracking data, highlighting the role of two significant noise sources: noise due to the differentiation of the positions and noise from the evaluation of the gravity vector at a noisy position. Averaging substantially reduces the noise in the aerodynamic acceleration as long as the differentiation noise dominates, which is the case at frequencies higher than the orbital frequency. Below, gravity vector evaluation noise becomes the dominating noise source, and consequently, averaging over longer periods leads to only marginal uncertainty reduction. Further, we investigate the uncertainty in the radiation pressure acceleration and demonstrate that averaging over one orbit substantially reduces the uncertainty in the along-track radiation pressure acceleration. We show that the uncertainty of density observations derived from the accelerometer data is about 4% of the density for data from 2003 when the GRACE B satellite was at 490 km altitude during high solar activity. In 2008, solar activity was very low, and the altitude was still 476 km, resulting in an uncertainty of 5%–20% because GNSS tracking noise and radiation pressure modeling errors play a much larger role as the aerodynamic acceleration becomes smaller. In the case of density observations derived only from GNSS tracking data, the uncertainty is about 5% in 2003 and 20%–50% in 2008 when averaging over one-third orbit. In 2008, GNSS tracking noise explains nearly all uncertainty in the density observation. Averaging over one orbit reduces the uncertainty to 4% and 5% in 2003 and 2008, respectively. [ABSTRACT FROM AUTHOR]