TEC measurements and modelling over Southern Africa during magnetic storms; a comparative analysis

• Published in: Journal of atmospheric and solar-terrestrial physics Vol. 72; no. 5; pp. 509 - 520
• Main Authors: Habarulema, John Bosco, McKinnell, Lee-Anne, Opperman, Ben D.L.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.04.2010; Elsevier
• Subjects: Earth, ocean, space; Exact sciences and technology; External geophysics; Magnetic storms; Neural networks; Physics of the ionosphere; Physics of the magnetosphere; Statistical validation; TEC models; Southern Africa; Africa; South Africa; Statistical validation; TEC models; Neural networks; Magnetic storms; Validation; models; dynamics; magnetic storms; neural networks; statistical analysis; Total electron content; variability; storms; Global Positioning System
• ISSN: 1364-6826; 1879-1824
• DOI: 10.1016/j.jastp.2010.01.012

This paper presents the results from a study designed to investigate the ability of a newly developed neural network (NN) based model to follow total electron content (TEC) dynamics over the Southern African region. The investigation is carried out by comparing results from the NN model with actual TEC data derived from Global Positioning System (GPS) observations and TEC values predicted by the International Reference Ionosphere (IRI-2007) model during magnetic storm periods over Southern Africa. The magnetic storm conditions chosen for the study presented in this paper occurred during the periods 16–21 April 2002, 1–6 October 2002, and 28 October–01 November 2003. A total of six South African GPS stations were used for the validation of the two models during these periods. A statistical analysis of the comparison between the actual TEC behaviour and that predicted by the two models is shown. In addition, ionosonde measurements from the South African Louisvale (28.5°S, 21.2°E) station, located close to one of the validation GPS stations used, are also considered during the Halloween storm period of 28–31 October 2003. The generalisation of TEC behaviour by the NN model is demonstrated by producing predicted TEC maps during magnetic storm periods over South Africa. Presented results demonstrate the ability of NNs in predicting TEC variability over South Africa during magnetically disturbed conditions, and highlight areas for improvement.