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Correlations Between the Thermosphere's Semiannual Density Variations and Infrared Emissions Measured With the SABER Instrument.

D R WeimerMartin G MlynczakJohn T EmmertE DoornbosE K SuttonLinda A Hunt
Published in: Journal of geophysical research. Space physics (2018)
This paper presents measurements of the amplitudes and timings of the combined, annual, and semiannual variations of thermospheric neutral density, and a comparison of these density variations with measurements of the infrared emissions from carbon dioxide and nitric oxide in the thermosphere. The density values were obtained from measurements of the atmospheric drag experienced by the Challenging Minisatellite Payload, Gravity Recovery and Climate Experiment A, Gravity field and Ocean Circulation Explorer, and three Swarm satellites, while the optical emissions were measured with the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. These data span a time period of 16 years. A database containing global average densities that were derived from the orbits of about 5,000 objects (Emmert, 2009, https://doi.org/10.1029/2009JA014102, 2015b, https://doi.org/10.1002/2015JA021047) was employed for calibrating these density data. A comparison with the NRLMSISE-00 model was used to derive measurements of how much the density changes over time due to these seasonal variations. It is found that the seasonal density oscillations have significant variations in amplitude and timing. In order to test the practicality of using optical emissions as a monitoring tool, the SABER data were fit to the measured variations. Even the most simple fit that used only filtered carbon dioxide emissions had good correlations with the measured oscillations. However, the density oscillations were also well predicted by a simple Fourier series, contrary to original expectations. Nevertheless, measurements of the optical emissions from the thermosphere are expected to have a role in future understanding and prediction of the semiannual variations.
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