ABSTRACT
Upper atmospheric mass density variations are very complex, which affect space weather and low earth orbit (LEO) satellites. Monitoring and understanding geophysical processes in the earth’s thermosphere are significant for predicting space weather variations. Unfortunately, the existing models are incapable of predicting the variability for practical operations, largely due to the limited quality and quantity of observations, and the lack of comprehensive approaches for calibrating the models. With the increasing number of LEO satellites equipped with high-precision Global Navigation Satellite System (GNSS) receivers, precise orbit products could be used to obtain comparable data sets. These new density estimates from LEO GNSS are a promising data source that can help to better characterize the upper atmosphere and to improve the existing models. In this chapter, the detailed methods and theory of extracting atmospheric mass density variations are presented and atmospheric mass density variations are estimated from GRACE and CASSIOPE GNSS precise orbits. The new GNSS-based density estimates are suitable to study long-term trends and high-frequency disturbances. Short-term density variations caused by geomagnetic storms have shown irregular and complex patterns, which vary from storm to storm. The irregular patterns seem to depend on space weather and several other factors, and the present models are unable to accurately represent the actual variability. These new data and methods are highly important for upper atmosphere research and applications, and for the improvement of the existing models.
