## 3 Ionospheric Model Quality
### Ionospheric Models in TEC Domain
(**a,b**) show TEC bias, (**c,d**) show mean absolute TEC error, (**e,f**) show mean percentage TEC error, (**g,h**) show mean absolute percentage TEC error. While Figure 9 considers yearly mean global parameters, Figure 10 shows the absolute TEC error for single GNSS stations in the same way as Figure 5.  
For all models, the highest errors are obtained for solar maxima and the lowest for solar minima. Equatorial stations feature higher errors for all the models except BDGIM. The latter features similar errors at high, mid-, and low latitudes. The cumulative distribution functions of absolute TEC error (Figure 11) show a remarkable difference between Klobuchar/GLONASS and NeQuickG/BDGIM models. The data for Figures 11-16 cover periods when all the models appeared in the data set (2015-2020). Figure 10: Dynamics of the yearly mean absolute TEC error at different stations (Figure 1) at high latitudes (blue dots), mid-latitudes (black dots), and low latitudes (red dots) for Klobuchar (**a**), NeQuickG (**b**), GLONASS (**c**), and BDGIM (**d**) models. Figure 11: The cumulative distribution function of absolute TEC error by different models: GLONASS (**a**, red), Klobuchar (**a**, blue), NeQuickG (**a**, magenta), BDGIM (**a**, black), GEMTEC (**b**, orange), NeQuick2 (**b**, purple), IRI-2012 (**b**, sea green), IRI-2016 (**b**, light green), and IRI-Plas (**b**, green). The horizontal light grey line shows a 0.5 level. Figure 12: Solar activity influence on absolute TEC errors. _F10.7_ dependence of absolute TEC errors for the following different models: GLONASS (**a**, red), Klobuchar (**a**, blue), NeQuickG (**a**, magenta), BDGIM (**a**, black), GEMTEC (**b**, orange), NeQuick2 (**b**, purple), IRI-2012 (**b**, sea green), IRI-2016 (**b**, light green), and IRI-Plas (**b**, green). Figure 13: Geomagnetic activity influence on absolute TEC errors. _Kp_ dependence of absolute TEC errors for the following different models: GLONASS (**a**, red), Klobuchar (**a**, blue), NeQuickG (**a**, magenta), BDGIM (**a**, black), GEMTEC (**b**, orange), NeQuick2 (**b**, purple), IRI-2012 (**b**, sea green), IRI-2016 (**b**, light green), and IRI-Plas (**b**, green). Figure 14: Absolute TEC errors vs. local time: GLONASS (red), Klobuchar (blue), NeQuickG (magenta), BDGIM (black), GEMTEC (orange), NeQuick2 (purple), IRI-2012 (sea green), IRI-2016 (light green), and IRI-Plas (green). (**a,b**) show mean absolute TEC error, (**c,d**) show mean absolute percentage TEC error. Figure 15: Absolute TEC errors vs. latitude: GLONASS (red), Klobuchar (blue), NeQuickG (magenta), BDGIM (black), GEMTEC (orange), NeQuick2 (purple), IRI-2012 (sea green), IRI-2016 (light green), and IRI-Plas (green). (**a,b**) show mean absolute TEC error, (**c,d**) show mean absolute percentage TEC error. From the cumulative distributions (panel a), we see that for small errors (~5 TECU) NeQuickG performs slightly better than BDGIM, while for errors greater than ~10 TECU, the distributions are similar. This reflects the peculiarities pointed out in Figure 9, where the mean absolute error for NeQuickG exceeds those for BDGIM. Table 3 summarizes 25%, 50%, 75%, 90%, and 95% error percentiles (\(\gamma\)), i.e., what amount of data (\(\gamma\)) has an error less than the one shown in the table. In Table 3, the models are ranked in accordance to positioning domain error (\(\sigma_{\text{3D}}\)), from the least to the most accurate. If instead, we consider the TEC domain, e.g., 90% and  
Figure 7:0 Absolute TEC errors vs. total electron content from GIM ISSG: GLONASS (red), Klobuchar (blue), NeQuickG (magenta), BDGIM (black), GEMTEC (orange), NeQuick2 (purple), IRI-2012 (sea green), IRI-2016 (light green), and IRI-Plas (green). (**a,b**) show mean absolute TEC error, (**c,d**) show mean absolute percentage TEC error.