Regional Assessment of the Applicability of IRI-2016, IRI-2020, and AfriTEC Models over East Africa during the Ascending Phase of Solar Cycle 25

Abstract

Abstract Reliable estimation of ionospheric Total Electron Content (TEC) is essential for mitigating signal delays and positioning errors in satellite-based communication and navigation systems. In low-latitude regions such as East Africa, TEC variability is strongly influenced by equatorial electrodynamics, seasonal asymmetry, and solar-cycle evolution, posing persistent challenges for both global and regional ionospheric models. This study presents a regional assessment of the IRI-2016, IRI-2020, and AfriTEC models in reproducing TEC variability over East Africa during the ascending phase of Solar Cycle 25 (2021–2022), a period marked by increasing solar and geomagnetic activity. Model outputs are systematically evaluated against GNSS-derived vertical TEC observations from selected International GNSS Service (IGS) stations, with analyses conducted across four representative seasons corresponding to the March and September equinoxes and the June and December solstices. Model performance is quantified using root mean square error (RMSE), Pearson correlation coefficients, and residual distribution analysis to examine error magnitude and bias under varying geophysical conditions. Results reveal pronounced seasonal dependence, with all models showing larger errors during solstice periods, particularly December. AfriTEC demonstrates improved agreement during equinoxes, with reduced variance and near-zero mean residuals, indicating balanced performance under moderate geomagnetic activity. However, its tendency to overestimate TEC during solstices and underestimate peak values during disturbed intervals highlights limitations in representing thermospheric winds and pre-reversal enhancement variability. IRI-2020 shows modest improvements over IRI-2016 in stability and correlation, yet both global models struggle to capture equinoctial and storm-time TEC extremes during the ascending solar cycle. These findings confirm that model performance over East Africa is strongly modulated by seasonal forcing and solar-cycle phase, underscoring the importance of region-specific validation. Integrating regional GNSS observations with enhanced electrodynamic parameterizations is crucial for improving ionospheric predictions and supporting reliable GNSS-based applications across the African sector.