On Imaging South African Regional Ionosphere Using 4D‐var Technique

Abstract

AbstractOne of the major research areas in the space weather community is the ability to understand, characterize, and model a time‐space variant ionosphere through which transionospheric signals propagate. In this paper a strong constraint four‐dimensional variational data assimilation (4D‐var) technique was used to more accurately estimate the South African regional ionosphere (bound latitude 20–35°S, longitude 20–40°E, and altitude 100–1,336 km). The altitude was capped to the JASON‐1 satellite orbital altitude for the purpose of eliminating the plasmasphere contribution hence reducing the computation expense. Background densities were obtained from an empirical internationally recognized ionosphere model (IRI‐2016) and propagated in time using a Gauss‐Markov filter. Ingested data were STECs (slant total electron content) obtained from the South African Global Navigation Satellite System receiver network (TrigNet). The vertically integrated electron content was validated using Global ionosphere Maps and JASON‐3 data over the continent and ocean areas, respectively. Further, vertical profiles after assimilation were compared with data from a network of ground‐based regional ionosondes Hermanus (34.25°S, 19.13°E), Grahamstown (33.3°S, 26.5°E), Louisvale (21.2°S, 28.5°E), and Madimbo (22.4°S, 30.9°E). Results show that assimilation of STEC data has a profound improvement on the estimation of both the horizontal and vertical structures during quiet and storm periods. Accuracy of the horizontal structure decreases from the continent toward the ocean area where GPS receivers are less abundant. Superiority of assimilating STEC is best pronounced during daytime especially when estimating maximum electron density of the F2 layer (NmF2), with a 60% root‐mean‐square error improvement over the background values.