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Daily Plasmaspheric TEC Variations From COSMIC GPS Observations Based on RBF Neural Network‐Kriging Method

Authors :
Qiqi Shi
Shuanggen Jin
Linlin Li
Source :
Space Weather, Vol 21, Iss 7, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract The low Earth orbit (LEO) satellite provides valuable direct observations for scientific investigation of the plasmasphere, while the plasmaspheric total electron content (PTEC) with a high temporal resolution cannot be precisely estimated due to fewer LEO satellites. In this paper, a novel joint method of radial basis function neural network—Kriging (RBF‐Kr) method is designed to construct the daily PTEC model using the Constellation Observing System for Meteorology, Ionosphere and Climate Global Positioning System observations during the low (2009) and high (2013) solar activity years. Compared with the original RBF method, the RBF‐Kr method reduces the mean absolute error and root mean square error from 0.77 to 0.60 TEC unit (TECU) and 0.99 to 0.80 TECU, respectively. The correlation coefficient (Corr) increased from 0.90 to 0.94. Furthermore, daily PTEC variations show that the PTEC at low latitudes is evenly distributed during equinox periods. The South American‐Atlantic Ocean sector has a peak and trough in PTEC during the December and June solstices. A certain symmetrical distribution of PTEC is observed in the latitudinal direction, and the symcenter moves toward the summer hemisphere. The duration of extremal PTEC at 60°W is observed, which lasted up to more than 80 days around the December solstice. An obvious correlation between the solar flux and PTEC is found with up to 0.86, indicating that daily PTEC variations are mainly related to solar activities.

Details

Language :
English
ISSN :
15427390
Volume :
21
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Space Weather
Publication Type :
Academic Journal
Accession number :
edsdoj.67d85bd27a47948045a56145d4ea2e
Document Type :
article
Full Text :
https://doi.org/10.1029/2022SW003347