Estimation of Neutral Densities in the Thermosphere
Ionospheric energy balance is studied with incoherent scatter radar measurements that allow the estimation of neutral density and temperature from a statistical inversion problem. This method has been successfully studied at low latitudes using data over several years to make a robust model.
openaire +1 more source
We report thermospheric exospheric temperature and composition responses on the 15 January 2022 Tonga volcanic eruption. The temperature and composition profiles are inversed from three ionosonde (MHJ45, EG931, FF051) observed electron density profiles (∼
Tingting Yu +4 more
doaj +1 more source
Unveiling the combined effects of neutral dynamics and electrodynamic forcing on dayside ionosphere during the 3-4 February 2022 "SpaceX" geomagnetic storms. [PDF]
Kakoti G, Bagiya MS, Laskar FI, Lin D.
europepmc +1 more source
Applying Energy Dissipation Rate GNSS Accelerometry to a Non‐Circular Orbiting Satellite
The increase in the number of objects in Low‐Earth Orbit has heightened the demand for high‐accuracy orbital prediction models driven by dependable measurements of thermospheric mass density (TMD).
D. J. Fitzpatrick +3 more
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High‐Latitude Electrodynamics and Thermospheric Density Variations During the 2024 Gannon Storm
This study investigates high‐latitude electrodynamics and thermospheric density variations during the 2024 Gannon's storm. First, the auroral precipitation module of Auroral Spectra and High‐Latitude Electric field variabilitY, ASHLEY‐A, is improved to ...
Qingyu Zhu +6 more
doaj +1 more source
Predicting global thermospheric neutral density during periods with high geomagnetic activity. [PDF]
Forootan E +5 more
europepmc +1 more source
Mesospheric pressure source from the 2022 Hunga, Tonga eruption excites 3.6-mHz air-sea coupled waves. [PDF]
Tonegawa T, Fukao Y.
europepmc +1 more source
The Ionospheric Connection Explorer - Prime Mission Review. [PDF]
Immel TJ +25 more
europepmc +1 more source
Thermospheric parameters contribution to the formation of Yakutsk F2-layer diurnal summer time anomaly. [PDF]
Mikhailov AV, Perrone L.
europepmc +1 more source
Machine Learning Based Modeling of Thermospheric Mass Density
In this study, we propose a machine learning based approach to construct an empirical model of thermospheric mass densities, based on the MultiLayer Perceptron and bi‐directional Long Short‐Term Memory for ensemble learning model (MBiLE). The MBiLE model
Qian Pan +8 more
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