An aided Abel inversion technique assisted by artificial neural network-based background ionospheric model for near real-time correction of FORMOSAT-7/COSMIC-2 data

The assumption of spherical uniformity while the retrieval electron density profiles from Global Navigation Satellite Systems-Radio Occultation (GNSS-RO) observations is often violated and introduces significant errors in retrieved profile data. This paper presents an improved Abel-inversion technique by incorporating horizontal gradients ionosphere, which are routinely derived Artificial Neural Network (ANN) based background NmF2 (peak F2-layer) model (ANNC2) assimilated with near real-time Constellation Observing System for Meteorology, Ionosphere, Climate-2 (FORMOSAT-7/COSMIC-2) ANNC2-aided Abel inversion then implemented more accurate COSMIC-2 real-time. It found that has values around F2-region below, yields a clear separation between two anomaly crests. Further, had significantly reduced artificial plasma caves beneath equatorial ionization Furthermore, obtained both classical compared ground-based Digisonde data gives better results. study provides some new insights on aided assisted ANN models correction profiles.