Issue |
J. Space Weather Space Clim.
Volume 8, 2018
|
|
---|---|---|
Article Number | A59 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/swsc/2018047 | |
Published online | 11 December 2018 |
Research Article
A single-station empirical TEC model based on long-time recorded GPS data for estimating ionospheric delay
1
School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255000, PR China
2
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, PR China
* Corresponding author: jdfeng@whu.edu.cn
Received:
4
July
2018
Accepted:
26
November
2018
Globally distributed GPS (global positioning system) stations have been continuously running for nearly 20 years, thereby accumulating numerous observations. These long-time recorded GPS data can be used to calculate continuous total electron content (TEC) values at single stations and provide an effective modeling dataset to establish single-station empirical TEC models. In this paper, a new empirical TEC model called SSM-T1 for single stations is proposed on the basis of GPS data calculated by IONOLAB-TEC application from 2004 to 2015. The SSM-T1 model consists of three parts: diurnal, seasonal, and solar dependency variations, with 18 coefficients fitted by the nonlinear least-squares method. The SSM-T1 model is tested at four stations: Paris (opmt), France; Bangalore (iisc), India; Ceduna (cedu), Australia; and O’Higgins (ohi3) over the Antarctic Peninsula. The RMS values of the model residuals at these four stations are 3.22, 4.46, 3.28, and 3.83 TECU. Assessment results show that the SSM-T1 model is in good agreement with the observed GPS-TEC data and exhibits good prediction ability at the Paris, Bangalore, and Ceduna stations. However, at the O’Higgins station, the SSM-T1 model seriously deviates from the observed GPS-TEC data and cannot effectively describe the variation of mid-latitude summer night anomaly.
Key words: empirical TEC models / ionospheric delay / single station / GPS data
© Z. Zhao et al., Published by EDP Sciences 2018
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