Observational analysis shows AfriTEC outperforms IRI-2020 in predicting TEC variations during geomagnetic disturbances.
This paper evaluates the comparision of IRI-2020 and AfriTEC ionospheric models in predicting TEC variations during geomagnetically disturbed time over East Africa in case of Ethiopia. In equatorial places like Ethiopia, the geomagnetic disturbance of the ionosphere can cause significant changes during disturbed time, which could lead to inaccurate position, timing data in satellite navigation and communication systems. For Ethiopian sectoral long-distance radio transmission, it is significant that the electron density can fluctuate diurnally, monthly and seasonally because of variations in the height and peak density of the F-region. To minimize this problem, we use the IRI-2020, the AfriTEC, and GNSS data. The IRI-2020 data predicted from the instant run version, the AfriTEC data predicted using the Matlab toolbox, and GNSS data were collected from the IGS network of ground-based dual-frequency GPS receivers across five Ethiopian sectors. By using geomagnetic parameters from omniweb data explorer, particularly the Dst index ranging from -70 to 20 nT for 2016. The results show a consistent daily and monthly correlation between the estimated TEC from both models and the GNSS, with notable seasonal variations. While the models showed good agreement across all seasons, discrepancies were observed in December and June. Seasonal equinox and solstice periods were particularly analyzed, with AfriTEC showing an overestimation of TEC by 2 to 5 TECU in April, yet having a lower root-mean-square error (RMSE) of 0.36 compared to IRI-2020. Finally, the diurnal, monthly, and seasonal statistical RMSE values indicate that the IRI-2020 model has the highest error, while the AfriTEC model has the lowest error. Therefore, the evidence shows that the AfriTEC ionospheric model gives a better prediction of the TEC and shows its superior performance in capturing ionospheric behavior during disturbed periods in Ethiopia. Accurate modeling of TEC is therefore essential for reliable long-distance radio communication in this region.
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Bagaje et al. (2025) studied this question.
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