# Improvement of Global Ionospheric TEC Derivation with Multi-Source Data in Modip Latitude
## 5 Conclusions  
We analyzed the improvement of two aspects in global ionospheric TEC derivation: multi-source data and coordinate system. In order to have an overall understanding of these two aspects, we first generated TEC using the IRI-2016 model at a resolution of \(2.5^{\circ}\times 5^{\circ}\times 0.1\) h in latitude, longitude and time. Simulation with the IRI model showed that the RMSE can be decreased by about 10.88% when using modip latitude and multi-source data, and the improvement of adding space-based observations is about 4.49% in the extrapolation areas, which have a relation to the amount of space-based data we added. Large deviations mainly occur in the EA, SAMA region and oceans where observation data is limited. Global TEC were derived by using an SH function in modip latitude with multi-source data at a resolution of \(2.5^{\circ}\times 5^{\circ}\times 2\) h in latitude, longitude and time. Observations from GNSS, JASON-2/3 satellite altimetry and COSMIC-1/2 occultation, and virtual observations from the IRI-2016 model, which were added at the center of each grid with no observation, were combined to derive the global ionospheric TEC, and following conclusions were made: the RMSE reduction of fitting with modip latitude had a mean value of about 7.02% in the 12 days of geomagnetic quiet conditions for four seasons in 2014 when using multi-source data, and the improvement was the largest in March and smallest in June; the mean residual in the EA, where the difference is supposed to be obvious, showed a diurnal variation and reached the maximum when the positions of the EIA and SAMA are close; the improvement of using modip latitude was less obvious in the year of low solar activity; the DCB difference between GACI and CODE was about 0.17 ns, and the TEC difference was mainly at the EA and oceans, where the GIMs from GACI had a larger value of about 5 TECU in the oceanic areas of the Southern Hemisphere due to the use of multi-source data. These results show that more satellite observations and a suitable coordinate system play an important role in global ionospheric TEC derivation. With the development of  
Figure 12: Differences in differential code bias (DCB) (P1-P2) in GACI with respect to CODE on DOY 265, 2014 (**top**), and DCB (P1-P2) comparison for GNSS and GACI with respect to CODE in 2014 (**bottom**). various ionospheric sounding techniques, multi-source observation data will become increasingly crucial in the obtainment of GIMs with high precision in the future. Conceptualization, W.F. and G.M. ; methodology, W.F., G.M. and T.M. ; software, W.F. and W.L. ; validation, J.L., Q.W., J.F. and X.W. ; formal analysis, W.F. ; investigation, W.F. ; resources, W.F. ; writing--original draft preparation, W.F. ; writing--review and editing, G.M. ; supervision, G.M. ; project administration, G.M. All authors have read and agreed to the published version of the manuscript. This research was supported by the National Key Research Program of China 'Collaborative Precision Positioning Project' (No. 2016 YFB0501900) and the National Natural Science Foundation of China (Nos. 11873064, 12073049 and U2031146). Not applicable. **Data Availability Statement**: Publicly available datasets were analyzed in this study. This data can be found here: CDDIS [[[https://cddis.nasa.gov](https://cddis.nasa.gov)]([https://cddis.nasa.gov](https://cddis.nasa.gov))], AVISO+ [[[https://www.aviso.altimetry.fr](https://www.aviso.altimetry.fr)]([https://www.aviso.altimetry.fr](https://www.aviso.altimetry.fr))], CDAAC [[[https://cdaac-www.cosmic.ucar.edu](https://cdaac-www.cosmic.ucar.edu)]([https://cdaac-www.cosmic.ucar.edu](https://cdaac-www.cosmic.ucar.edu))], and IRI-2016 model [[[http://irimodel.org](http://irimodel.org)]([http://irimodel.org](http://irimodel.org))] (all accessed on 28 March 2021).