
Abstract Thermospheric mass density (TMD) measurements are invaluable to accurately estimate and predict the position and velocity of orbiting objects in Low Earth Orbit (LEO). Existing observational methods and predictive models have some problems (e.g., accuracy, resolution, coverage, cost, etc.) to describe and forecast the actual air drag variations as required for practical applications. With the increasing number of LEO satellites equipped with high‐precision Global Navigation Satellite System (GNSS) receivers, the precise orbits can be used to obtain non‐gravitational accelerations, and therefore estimate TMD variations. In this study, TMD is estimated from the precise orbits of CAScade SmallSat and IOnospheric Polar Explorer (CASSIOPE) at one‐second time step, and the TMD variations following the February 2014 geomagnetic storm are investigated. Using this method, a more detailed description than previous methods and empirical models is given with short‐term TMD variations during geomagnetic storm conditions. The empirical model NRLMSISE‐00 shows less pronounced and more averaged variations, while CASSIOPE‐derived TMD can reflect the abrupt disturbances triggered by the geomagnetic storm. CASSIOPE TMD shows a correlation of 72.4% to the merging electric field E m index, while the NRLMSISE‐00 model shows a correlation of 42.1%.
Global Navigation Satellite System, upper‐atmosphere, CASSIOPE, Astrophysics, QB460-466, low earth orbit, Meteorology. Climatology, QC851-999, thermospheric mass density
Global Navigation Satellite System, upper‐atmosphere, CASSIOPE, Astrophysics, QB460-466, low earth orbit, Meteorology. Climatology, QC851-999, thermospheric mass density
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
