The total electron content (TEC) profiles from the FORMOsa SATellite mission‐3/Constellation Observing System for the Meteorology, Ionosphere, and Climate (COSMIC) and the Fengyun‐3C (FY‐3C) radio occultation (RO) missions during 2006 and 2019 are used to establish the models for deriving the ionospheric sporadic E (Es) critical frequency (foEs). Smax is derived as the maximum vertical gradient of TEC disturbance, which is extracted from a RO TEC profile using the singular spectrum analysis method. Three candidate conversion models are obtained by fitting Smax with foEs observed by collocated ionosondes, and the one with the best performance, the COSMIC&FY‐3C (CF) model, is applied for deriving foEs (foEsCF) from the TEC data of the two missions jointly. For comparison, the C model, which is of similar form as the CF model while being established without using the FY‐3C data, is applied for deriving foEs (foEsC) from the COSMIC TEC data only. The validations over four independent ionosonde stations demonstrate that mean improvements of 0.11 MHz (32%) in the absolute bias and 0.24 MHz (17%) in the root mean square error are obtained by foEsCF compared with foEsC. The spatiotemporal distributions of Es intensity during 2015 and 2019, presented respectively by foEsCF and foEsC, are further compared. The CF model provides more abundant and more detailed information about Es intensity distribution, which is most distinct at high latitudes where the contribution of FY‐3C RO TEC data is significant. Our results reveal that with the aging of the COSMIC satellites, FY‐3C TEC data is a valuable supplementary RO data source for Es‐related studies.

The Global Positioning System (GPS) radio occultation (RO) data provided by the Fengyun-3C (FY-3C) mission during January 2015 to December 2019 are used to detect the existence of sporadic E (Es) layers over the globe, based on which the spatial and temporal distributions of the Es occurrence rates (ORs) are presented and analyzed. The results are compared with the Es morphology obtained using the RO data from the Constellation Observing System for the Meteorology, Ionosphere, and Climate (COSMIC) mission. It is found that the seasonal variation patterns of the spatial distributions of Es ORs derived from the FY-3C RO data, which show clearly the effects of wind shear mechanism and the Earth’s magnetic field on the formation of Es layers, are basically consistent with those derived from the COSMIC RO data. While the limited local time distribution of the FY-3C RO-detected Es occurrences makes it impossible to resolve the complete diurnal variations of Es layers. Detailed comparisons of the Es morphologies derived from the two different RO missions reveal that the magnitudes of the Es ORs derived by FY-3C data are slightly smaller than those derived by COSMIC data in the middle and low latitudes, which is due to that the top heights of the 50 Hz RO data of FY-3C mission are generally lower than those of the COSMIC mission. In the polar regions, the distinctly low ratio of the FY-3C RO 50 Hz measurements which reach the height of 90 km reduces the capability of these observations for Es-layer detections. Graphical Abstract

There are a large number of excellent research cases in Global Navigation Satellite System (GNSS) positioning and disaster prediction in Japan region, where the simulation and prediction of total electron content (TEC) is a powerful research method. In this study, we used the data of the GNSS Earth Observation Network (GEONET) established by the Geographical Survey Institute of Japan (GSI) to compare the performance of two regional ionospheric models in Japan, in which the spherical cap harmonic (SCH) model has the best performance. In this paper, we investigated the spatial and temporal variations of ionospheric TEC in Japan and their relationship with latitude, longitude, seasons, and solar activity. The results show that the TEC in Japan increases as the latitude decreases, with the highest average TEC in spring and summer and the lowest in winter, and has a strong correlation with solar activity. In addition, the observation and analysis of ionospheric disturbances over Japan before the 2016 Kumamoto earthquake and geomagnetic storms showed that GNSS observing of ionospheric TEC seems to be very effective in forecasting natural disasters and monitoring space weather.