State‑of‑the‑Art Computerized Ionospheric Tomography over Africa and Türkiye

Abstract

This study presents an application of the 4‑D computerized ionospheric tomography (CIT) algorithm, IONOLAB‑Fusion, developed for reconstructing ionospheric electron density as a function of height, latitude, longitude, and time. The algorithm integrates data from ground‑based Global Positioning System (GPS) receivers and Radio Occultation (RO) satellite measurements to generate high‑fidelity ionospheric models under varying observational conditions. In this study, IONOLAB‑Fusion is applied to two distinct regions: Türkiye, representing a well‑instrumented midlatitude environment in the Northern Hemisphere, and Africa, encompassing both equatorial and midlatitude sectors characterized by limited receiver coverage. Over Türkiye, validation against Global Ionospheric Maps (GIMs) shows that the algorithm significantly outperforms Total Electron Content (TEC) estimates from the IRI‑Plas model, achieving improvements of up to 90% during quiet ionospheric conditions. Over Africa, despite severe data sparsity, improvements of up to 77% on quiet days and 63% on disturbed days relative to GIMs are achieved. Further validation using ionosonde vertical electron density profiles in South Africa shows consistency between observations and reconstructions, with accuracy gains of over 84% and over 53% for quiet and disturbed conditions, respectively. Additionally, a case study conducted using RO data shows that reconstructions without and with RO measurements improve upon IRI‑Plas by 50% and 54%, respectively, highlighting the added value of RO observations. These findings confirm that IONOLAB‑Fusion provides robust, accurate, computationally efficient, and physically consistent reconstructions across regions with both dense and sparse observation networks, demonstrating strong potential for regional and global ionospheric modeling, space weather monitoring, and improved global navigation system reliability.