## 6 Conclusions  
In this study, the accuracies of nine zenith tropospheric delay (ZTD) models, as well as the SPP biases caused by the residual ZTD (dZTD) after model correction were evaluated using IGS-ZTD products from around 400 globally distributed monitoring stations. The nine ZTD models are saas+norm/GPT/GPT2/GPT2w/GPT3, UNB3, UNB3m, EGNOS, and VMF3. The seasonal, latitudinal, and altitudinal discrepancies were analyzed respectively. From the study, the following conclusions can be obtained:  
(1) The nine models can be generally divided into four groups, that are saas+norm/GPT, EGNOS/UNB3/UNB3m, saas+GPT2/GPT2w/GPT3, and VMF3. The model accuracies and stabilities are comparable within each group, and significantly increase among groups. RMSs of EGNOS/UNB3/UNB3m are nearly 30% smaller than saas+GPT, and are 20% larger than saas+GPT2/GPT2w/GPT3. The bias of VMF3-ZTD is ignorable, and the RMS is just 1.31 cm.  
(2) The SPP solution biases caused by the dZTD mainly occur on the vertical (U) direction, nearly to decimeter level, and biases on horizontal (N and E) directions are significantly smaller, just at centimeter level. Generally, the dZTD values are adversely magnified about 5 times on the vertical SPP solution biases globally, and the impacts are slightly smaller at mid-latitude zones.  
(3) In terms of seasonal effects, all of the nine models show lower stabilities in summer, and stabilities in the other three seasons are comparable. For latitude effects, the four groups show inconsistent tendencies. Generally, these models show larger variations and discrepancies at equatorial and south polar regions. Finally, for altitude effects, the model stabilities generally increase as the station heights increase except for the saas+GPT2 and VMF3 models.  
By the above assessments and analyses, the question of how much the uncorrected dZTD would sway the SPP solution on a global scale is answered. Meanwhile, references for the refinement and applications of the nine ZTD models are provided.  
Conceptualization, L.Y.; methodology, L.Y. and J.W.; software, J.W.; validation, L.Y. and H.L.; formal analysis, L.Y. and J.W.; investigation, L.Y. and J.W.; resources, H.L. and T.B.; data curation, J.W.; writing--original draft preparation, J.W. and L.Y.; writing--review and editing, L.Y. and J.W.; visualization, H.L. and T.B.; supervision, H.L. and T.B.; project administration, H.L. and T.B.; funding acquisition, H.L. and T.B. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (41504022), the Shanghai Natural Science Foundation (20 ZR1462000), and the Open Research Fund Program of LIESMARS (Grant No. 19R02).  
**Data Availability Statement:** Publicly available datasets were analyzed in this study. These data can be found here: [[[https://vmf.geo.tuwien.ac.at/](https://vmf.geo.tuwien.ac.at/)]([https://vmf.geo.tuwien.ac.at/](https://vmf.geo.tuwien.ac.at/)) accessed on 9 August 2020] and [[[ftp://cddis.gsfc.nasa.gov/gps/data](ftp://cddis.gsfc.nasa.gov/gps/data)]([ftp://cddis.gsfc.nasa.gov/gps/data](ftp://cddis.gsfc.nasa.gov/gps/data)) accessed on 20 January 2019].  
**Acknowledgments:** The authors would like to thank IGS and TU Wien for providing zenith tropospheric delay products.  
**Conflicts of Interest:** The authors declare no conflict of interest.