Comparative Analysis of TEC Estimation Models over Ethiopia: Case Study during 2015 St. Patrick’s Day Storm

Abstract

Abstract The ionosphere, a vital layer of Earth’s atmosphere, undergoes dynamic changes influenced by solar and geomagnetic activities. This study evaluates the Multi-Instrument Data Analysis System (MIDAS) for estimating ionospheric total electron content (TEC) in the data-scarce East African longitude sector, focusing on the 2015 St. Patrick’s Day geomagnetic storm. TEC maps from MIDAS are compared with those from the Global Ionospheric Map (GIM) and the AfriTEC neural network-based model, revealing temporal and spatial TEC variations during both quiet and storm conditions. Validation is performed using ground GPS station data. MIDAS and GIM successfully captured TEC enhancements during the storm, while AfriTEC, relying on quiet-condition data, showed limited responsiveness. GIM showed a high correlation coefficient (R = 0.99) with observational data, while MIDAS (R = 0.97) better captured transient diurnal variations. MIDAS outperformed AfriTEC in capturing transient TEC fluctuations, such as diurnal variations and storm-induced enhancements, though it showed occasional variability compared to GIM. The results demonstrate the potential of tomographic techniques in regional ionospheric studies, especially in data-scarce regions, and underscore the importance of model adaptability to geomagnetic variations.