The first comparison between Swarm-C accelerometer-derived thermospheric densities and physical and empirical model estimates

Kodikara, N, Carter, B and Zhang, K 2018, 'The first comparison between Swarm-C accelerometer-derived thermospheric densities and physical and empirical model estimates', Journal of Geophysical Research Space Physics, vol. 123, no. 6, pp. 5068-5086.


Document type: Journal Article
Collection: Journal Articles

Attached Files
Name Description MIMEType Size
n2006083466.pdf Published Version application/pdf 3.24MB
Title The first comparison between Swarm-C accelerometer-derived thermospheric densities and physical and empirical model estimates
Author(s) Kodikara, N
Carter, B
Zhang, K
Year 2018
Journal name Journal of Geophysical Research Space Physics
Volume number 123
Issue number 6
Start page 5068
End page 5086
Total pages 19
Publisher Wiley-Blackwell
Abstract The first systematic comparison between Swarm-C accelerometer-derived thermosphericdensity and both empirical and physics-based model results using multiple model performance metricsis presented. This comparison is performed at the satellites high temporal 10-s resolution, which providesa meaningful evaluation of the models fidelity for orbit prediction and other space weather forecastingapplications. The comparison against the physical model is influenced by the specification of the loweratmospheric forcing, the high-latitude ionospheric plasma convection, and solar activity. Some insightsinto the model response to thermosphere-driving mechanisms are obtained through a machine learningexercise. The results of this analysis show that the short-timescale variations observed by Swarm-C duringperiods of high solar and geomagnetic activity were better captured by the physics-based model thanthe empirical models. It is concluded that Swarm-C data agree well with the climatologies inherent withinthe models and are, therefore, a useful data set for further model validation and scientific researc
Subject Space and Solar Physics
Atmospheric Sciences not elsewhere classified
Geophysical Fluid Dynamics
Keyword(s) Swarm-C accelerometer-derived density
Physics-based thermospheric density
TIE-GCM NRLMSISE-00 DTM-2013
Thermosphere machine learning
Taylor diagram
Thermosphere upper atmosphere
DOI - identifier 10.1029/2017ja025118
Copyright notice © 2018. The Authors. Open access article, Creative Commons Attribution-NonCommercial-NoDerivs License, permits use and distribution in any medium, provided original work is properly cited, use is non-commercial and no modifications or adaptatios are made.
ISSN 2169-9380
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 0 times in Scopus Article
Altmetric details:
Access Statistics: 11 Abstract Views, 8 File Downloads  -  Detailed Statistics
Created: Thu, 21 Feb 2019, 12:10:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us