Investigating the Reliability of the AfriTEC Model During the Descending Phase of Solar Cycle 24 Across East Africa

TL;DR

This study evaluates the AfriTEC ionospheric model's accuracy during Solar Cycle 24's descending phase in East Africa, highlighting its strengths in capturing diurnal and seasonal TEC variations and identifying areas for improvement.

Contribution

It provides a comprehensive assessment of the AfriTEC model's performance across East Africa and benchmarks it against the NeQuick model, revealing its regional advantages and limitations.

Findings

AfriTEC accurately models diurnal and seasonal TEC behavior with MAE below 1.5 TECU.

The model shows high correlation coefficients (>0.80) during equinoxes.

Discrepancies occur during solstices and post-sunset hours, especially near the EIA.

Abstract

This study investigates the reliability of the African Regional Ionospheric Total Electron Content (AfriTEC) model during the descending phase of Solar Cycle 24 (2016-2017) across East Africa. Using GNSS-derived TEC data from five equatorial and low-latitude stations MOIU, MAL2, ZAMB, ADIS, and MBAR the model's performance is assessed through statistical metrics, including Mean Absolute Error (MAE) and correlation coefficient r. Results indicate that the AfriTEC model effectively captures the diurnal and seasonal behavior of TEC, particularly during equinoxes, with MAE values generally below 1.5 TECU and correlation coefficients exceeding 0.80. However, discrepancies emerge during solstice periods and post-sunset hours, reflecting the model's limitations in representing complex ionospheric processes such as the Equatorial Ionization Anomaly (EIA). To benchmark its performance, AfriTEC is also compared against the widely used NeQuick model. AfriTEC demonstrates superior regional adaptability and reduced error under most conditions, though it remains sensitive to localized ionospheric disturbances. These findings suggest that while AfriTEC is a valuable tool for ionospheric modeling in whole Africa especially at East African sector, enhancements incorporating real-time solar and geomagnetic indices could further improve its predictive capabilities.