# Global GNSS-RO Electron Density in the Lower Ionosphere
## 5 Conclusions and Future Work  
We have extended the bottom-up \(N_{e}\) retrieval to the \(D\)-region (60-90 km) using the \(\Delta hTEC\) measurement derived from high-rate GNSS-RO data. The new algorithm can produce an \(N_{e}\) profile up to 180 km if the high-rate RO top reaches this height. The optimal estimation inversion has been updated to handle both measurement vectors \(hTEC\) with the Abel weighting function and \(\Delta hTEC\) with the \"bottom-up\" weighting function. This flexibility allows the algorithm to process the podTEC data, if needed, for the \(N_{e}\) retrieval. In addition to the \(D\)/\(E\)-region \(N_{e}\), a new \(TEC\) retrieval technique was developed using the high-rate RO data with a top above 120 km. For better characterizing the \(E\)- to \(F\)- \(N_{e}\) transition and the novel \(TEC\) retrieval, it is recommended to have the routine GNSS-RO acquisition up to \(h_{t}=220\) km. The RO \(N_{e}\) retrieval was compared briefly with the ionosonde observations at the Hermanus, South Africa site. A generally good agreement was found in the \(E\)-region, with the RO \(N_{e}\) profile being lower in density and shifted upwards slightly in altitude. Encouraged by the preliminary comparison, a greater validation effort is planned to include more ionosonde sites from different latitudes. The morphology of new GNSS-RO \(N_{e}\) data revealed many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations. While the \(D\)/\(E\)-region \(N_{e}\) is a strong function of solar zenith angle (\(\chi\)), it exhibits strong latitudinal variations for the same \(\chi\), and its distribution is asymmetric about noon. The magnetic-field modulation of \(N_{e}\) varies from month to month. There are large longitudinal variations along the same pitch angle of magnetic field. The summer-midlatitude \(N_{e}\) distributions in June and December closely resemble the global \(E_{s}\) morphology, suggesting that the same processes likely drive these geophysical variations. In the polar region, the \(N_{e}\) distribution correlates better with the pitch angle derived from the magnetic field in the magnetosphere than from the 100 km, as expected for the magnetosphere-driven auroral electron precipitation. There is a clear semiannual variation in the nighttime zonal mean \(N_{e}\) in the \(D\)-region with peaks near the equinox months. We were able to derive the daytime and nighttime solar-cycle variations in the \(D\)-region \(N_{e}\) from the MetOp RO data that had stable operation and uniform sampling at \(\sim\)9 a.m. and \(\sim\)9 p.m. local times. There is a good correlation between the long-term \(N_{e}\) variations and the F10.7 flux during 2007-2021. Spatiotemporal sampling is critical to characterize large diurnal and geographical variabilities in the ionosphere. Because there are more high-rate RO measurements than podTEC, it provides a clear advantage to sample the \(D\)/\(E\)-region ionosphere better with the high-rate RO observations. The combined spatiotemporal observations from COSMIC-2 and Spire constellations have provided an unprecedented coverage for studying the ionosphere since 2021. As the constellation continues to expand, it is feasible to improve the diurnal sampling to one-hour intervals and a spatial sampling better than the \(8^{\circ}\times 4^{\circ}\) longitude-latitude grid, as used in this study. The dense spatial sampling will perhaps allow a tomographic retrieval of \(N_{e}\), to improve the horizontal resolution of the GNSS-RO technique. For future algorithm developments, we plan to apply the retrieval to the podTEC and ionPhs data to obtain a full \(N_{e}\) profile in the ionosphere. The podTEC data from CDAAC contain the \(hTEC\) profile with absolute calibration that can be readily processed with the algorithm developed in this study for an Abel inversion of \(N_{e}\).