Assessment of IRI and IRI-Plas models over the African equatorial and low-latitude region

Adebiyi, S.J. and Adimula, I.A. and Oladipo, O.A. and Joshua, B.W. Assessment of IRI and IRI-Plas models over the African equatorial and low-latitude region. Journal of Geophysical Research: Space Physics.

Text full/10.1002/2016JA022697 - Published Version Download (314kB)

Abstract

A reliable ionospheric specification by empirical models is important to mitigate the effects of the ionosphere on the operations of satellite-based positioning and navigation systems. This study evaluates the capability of the International Reference Ionosphere (IRI) and IRI extended to the plasmasphere (IRI-Plas) models in predicting the total electron content (TEC) over stations located in the southern hemisphere of the African equatorial and low-latitude region. TEC derived from Global Positioning System (GPS) measurements were compared with TEC predicted by both the IRI-Plas 2015 model and the three topside options of the IRI 2012 model (i.e., NeQuick (NeQ), IRI 2001 corrected factor (IRI-01 Corr), and the IRI 2001(IRI-01)). Generally, the diurnal and the seasonal structures of modeled TEC follow quite well with the observed TEC in all the stations, although with some upward and downward offsets observed during the daytime and nighttime. The prediction errors of both models exhibit latitudinal variation and these showed seasonal trends. The values generally decrease with increase in latitude. The TEC data-model divergence of both models is most significant at stations in the equatorial region during the daytime and nighttime. Conversely, both models demonstrate most pronounced convergence during the nighttime at stations outside the equatorial region. The IRI-Plas model, in general, performed better in months and seasons when the three options of the IRI model underestimate TEC. Factors such as the height limitation of the IRI model, the inaccurate predictions of the bottomside and topside electron density profiles were used to explain the data-model discrepancies.

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