Comparing the Performance of IRI-2020 and AfriTEC Ionospheric Models Over East Africa In Case Of Ethiopia During Disturbed Time

This study evaluates the performance of IRI-2020 and AfriTEC ionospheric models in predicting Total Electron Content (TEC) variations during geomagnetically disturbed time over East Africa in the 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 and timing data in satellite navigation and communication systems. For Ethiopian sectoral radio long-distance transmission, it is significant that the electron density can fluctuate diurnally, monthly and seasonally due to variations in the height and peak density of the F-region. To minimize this problem, we use the IRI-2020 model, the AfriTEC model, and GPS-TEC data. The IRI-2020 model data predicted from the instant run version, the AfriTEC model data predicated MatLab toolbox, and GPS-derived TEC data were obtained from the IGS network of ground-based dual-frequency GPS receivers from five Ethiopian sectors. By using geomagnetic parameters from Omniweb data sources, 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 GPS-TEC, with notable seasonal variations. While the models demonstrated 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 3 to 50 TECU in April, yet having a lower root mean square error (RMSE) of 0.36 compared to IRI-2020. Finally, the diurnal, monthly, seasonal statistical RMSE values indicate that the IRI-2020 RMSE is a maximum error and the AfriTEC RMSE is the minimum error value. Therefore, the evidence shows that the AfriTEC ionospheric model gives a better prediction of the TEC at Ethiopian sectors and shows its superior performance in capturing ionospheric behavior during disturbed periods.