2015
DOI: 10.1016/j.asr.2015.05.038
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Thermospheric mass density: A review

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Cited by 210 publications
(235 citation statements)
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References 364 publications
(461 reference statements)
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“…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.…”
Section: Resultsmentioning
confidence: 99%
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“…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.…”
Section: Resultsmentioning
confidence: 99%
“…Wang et al (2014) investigated the seasonal variations of globally averaged thermospheric mass density at 400 km during 1996-2006 using an artificial neural network (ANN), and concluded that there exist strong linear relations between the annual/semiannual amplitudes and the solar activity. Emmert (2015) reviewed the studies of the thermosphere between 2000 and 2014, summarized several possible mechanisms to explain the seasonal variations, and demonstrated that further investigations are required to understand the seasonal variations of the thermosphere. Recently, Calabia et al (2016) investigated the thermospheric mass density variations from GRACE data for the period 2003-2016 by using the principal component analysis (PCA) method, and discussed the annual variation for different local solar times (LSTs) and solar activities.…”
Section: Introductionmentioning
confidence: 99%
“…Many authors have evaluated the efficacy of these proxies for thermospheric modelling, see the review by Emmert (2015b). While the EUV flux from SEM and the MgII index perform slightly better at time scales of a few months and below, F10.7 is still preferred by most for its good overall results and for its long-term stability.…”
Section: Comparison With Solar Proxiesmentioning
confidence: 99%
“…The relationship between average solar forcing and average density is nonlinear but monotonic (Emmert 2015b), which allows us again to rely on the convenient framework of the cross-coherence. The true picture, however, is blurred by the contribution of geomagnetic activity, which also strongly affects the density, but does so more intermittently and mostly independently of the UV flux.…”
Section: Comparison With the Thermospheric Densitymentioning
confidence: 99%
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