Comparative evaluation demonstrates dynamic total electron content tracking by ionospheric tomography models during geomagnetic storms, highlighting the utility of adaptive modeling in data-scarce...
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.
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Nigussie Mezgebe Giday (2026) studied this question.
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