Thermospheric Density: An Overview of Temporal and Spatial Variations

Abstract

Neutral density shows complicated temporal and spatial variations driven by external forcing of the thermosphere/ionosphere system, internal dynamics, and thermosphere and ionosphere coupling. Temporal variations include abrupt changes with a time scale of minutes to hours, diurnal variation, multi-day variation, solar-rotational variation, annual/semiannual variation, solar-cycle variation, and long-term trends with a time scale of decades. Spatial variations include latitudinal and longitudinal variations, as well as variation with altitude. Atmospheric drag on satellites varies strongly as a function of thermospheric mass density. Errors in estimating density cause orbit prediction error, and impact satellite operations including accurate catalog maintenance, collision avoidance for manned and unmanned space flight, and re-entry prediction. In this paper, we summarize and discuss these density variations, their magnitudes, and their forcing mechanisms, using neutral density data sets and modeling results. The neutral density data sets include neutral density observed by the accelerometers onboard the Challenging Mini-satellite Payload (CHAMP), neutral density at satellite perigees, and global-mean neutral density derived from thousands of orbiting objects. Modeling results are from the National Center for Atmospheric Research (NCAR) thermosphere-ionosphere-electrodynamics general circulation model (TIE-GCM), and from the NRLMSISE-00 empirical model.

Seasonal variations of thermospheric mass density at dawn/dusk from GOCE observations

“…These results illustrate that the thermospheric annual asymmetry should be associated with the varying Sun-Earth distance. Actually, previous studies suggested that the difference of solar radiation associated with the difference of Sun-Earth distance between June and December would contribute to the annual asymmetry (Qian et al, 2012;Lei et al, 2013Lei et al, , 2016Emmert, 2015;Calabia et al, 2016). Moreover, Fig.…”

On estimation and attribution of long‐term temperature trends in the thermosphere

“…Because T i is closely related to T, a corresponding trend in neutral temperature was estimated to be about dT = À5 K yr À1 , which is substantially greater than predicted by models [e.g., Roble and Dickinson, 1989;Rishbeth and Roble, 1992;Qian et al, 2011;Qian and Solomon, 2012].…”

“…[8] Second and perhaps more important, according to model simulations of trends in T, which are in good agreement with independent observational estimates [Beig et al, 2003;Marcos et al, 2005;Akmaev et al, 2006;Qian et al, 2006;Emmert et al, 2008;She et al, 2009;Qian and Solomon, 2012], it appears impossible to quantitatively reconcile them with the estimates of trends in T i regardless of what known cooling mechanisms are invoked. Even though the vertical profiles are qualitatively very similar, with positive and negative trends in the lower and upper thermosphere, respectively, the magnitudes differ tremendously.…”

Long-term orbit prediction for Tiangong-1 spacecraft using the mean atmosphere model

“…Following common conventions, the geomagnetic storm is defined corresponding to 6 6 K p 9 (Montenbruck and Gill, 2000;Rhoden et al, 2000;Qian and Solomon, 2012). The normal level of solar activity corresponds to a typical value of F 10:7 ¼ 155, while a maximum activity corresponding to F 10:7 ¼ 240 (Montenbruck and Gill, 2000).…”