Conceptual framework enabling the spatio-temporal analysis of post-sunset equatorial ionospheric irregularities for space weather forecast

The forecast of the occurrence of scintillation for end-use predictions over the Indian region is a challenging task. In the context of this challenge, the understanding of the day-to-day spatial and temporal variability of the post-sunset equatorial F-region ionospheric irregularities represents a very important problem. Notably, the spatial (zonal) variations in the scintillation occurrence depends upon the day-to-day perturbations in the equatorial vertical ExB drift and the zonal movement of scintillation patches follow the zonal ExB drift patterns. A conceptual framework that combines information from scintillation indices (as derived from the GNSS receivers) with modelled background information (as derived from physics based ionospheric models) is proposed. The idea is to understand the dependence of local morphology on the physical mechanisms responsible for the formation of the equatorial F-region ionospheric irregularities in the range of 9^o N to 18^o N geographical latitudes and 74^o E to 82^o E geographic longitudes respectively. The Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) is chosen as a background model to provide several parameters of significance in this context. A day-wise correlation analysis for the year 2014 (high solar activity year) is performed between all the TIEGCM model outputs and observed S₄ index variations within the above mentioned pre-defined geographical boundary. The output parameters (e.g., equatorial zonal ExB drift, vertical ExB drift, critical height) show positive correlation with the observed post sunset variations in the S₄ index. Moreover, the zonal ExB drift is also ingested with observations from the Communication/Navigation Outage Forecast System (C/NOFS) satellite. A method to infer the zonal and vertical ExB drifts from the combination of TIEGCM outputs, C/NOFS in-situ data, and GNSS S₄ observations is introduced on the basis of a two-dimensional image evaluation approach. This framework establishes a basis for the prediction of spatial ionospheric irregularities over the region of interest.