## 5 Conclusions  
In this work, we analyzed the ionospheric behavior during the 10 June 2021 annular solar eclipse and its impact on DF-GNSS PPP-AR accuracy. We use a large global GNSS network located around the planet to estimate the effects on positioning. This solar eclipse had a trajectory over the northern polar region. We used global ionospheric TEC maps with data gathered by ground-based GNSS stations. The TEC maps show a noticeable depletion under the moon's shadow, reaching A[%] \(<-60\%\). Furthermore, a significant TEC decrease (A[%] \(<-60\%\)) can also be observed far from the ionosphere under the moon's shadow in regions close to the crests of the EIA over the Caribbean and South America, with a duration or \(\Delta\)T over 10 h. Then, percentages of the ionospheric TEC over the Caribbean and South America were similar to those obtained for GNSS stations located in the region of the eclipse. Our study also confirms that there are cases and places where the disturbance can last much longer than previously expected. We show that TEC enhancement caused by geomagnetic activity on the day after the eclipse did not cause problems in the ionospheric TEC background to our presented results for the eclipse day. We also validated the ionospheric variations estimated with GNSS receivers through measurements from other instruments such as the Swarm-A satellite (VTEC and in situ Ne), and four ionosondes (TEC, foF2, and hmF2). The ionospheric behavior clearly demonstrates that electrons are less active in that layer during the solar eclipse. Furthermore, our results are consistent with ionospheric effects reported in similar previous solar eclipses. This study not only analyzes the eclipse's day but also compares the effects of the ionosphere and its impact on the positioning precision with those over 2 days previous and 2 days after the day of the eclipse. The day of the eclipse was the day with the second highest percentage of stations that exceeded the selected positioning thresholds (maximum 3D positioning error \(\geq\) 10 cm, 3D-RMS \(\geq\) 3 cm), only surpassed by the day after, which had geomagnetic activity. The data analysis shows that the eclipse had a significant effect on GNSS precision for a long time (\(\sim\)10 h). The Greenland and South America sectors are within the regions that presented GNSS stations with the highest positioning errors during the eclipse time window. Moreover, both regions had the greatest ionospheric TEC decrease (\(\sim\)\(-\)60%). The ROTI variations were not relevant. Thus, the results reinforce the idea that ROTI activity is not a necessary condition to affect DF-GNSS PPP-AR accuracy. Additionally, the results suggest that when maximum 3D errors are larger than 60%, the A[%] is much less than \(-\)49%. However, the opposite is not necessarily true. The following are available online at [[https://www.mdpi.com/article/10.3390/rs14133119/s1](https://www.mdpi.com/article/10.3390/rs14133119/s1)]([https://www.mdpi.com/article/10.3390/rs14133119/s1](https://www.mdpi.com/article/10.3390/rs14133119/s1)), Video S1: Eclipse obscuration mask from P1 to P4 time at 350 km altitude. Figure S1: Ionospheric TEC maps during the 10 June 2021 Annular Solar Eclipse: the world and Northern Hemisphere polar plots. Figure S2: DVTEC[TECu] maps using the Kriging interpolation method to the eclipse day. Table S1: Mean and standard deviation for each map of Figure S2. Table S2: 3D-RMS in Greenland and South America. Table S3: Maximum 3D positioning error in Greenland and South America. Table S4: ROTI in Greenland and South America. Conceptualization, J.C.V.-A., M.A.D. and M.B. ; methodology, J.C.V.-A. and M.A.D. ; software, J.C.V.-A., M.B. and Y.S.-S.; validation, J.C.V.-A., M.A.D., M.B., J.C.B. and Y.S.-S.; formal analysis, J.C.V.-A., M.B. and Y.S.-S.; investigation, J.C.V.-A., M.A.D., M.B., J.C.B. and Y.S.-; resources, J.C.V.-A., M.A.D., M.B., J.C.B. and Y.S.-S.; data curation, J.C.V.-A., M.B. and Y.S.-S.; writing--original draft preparation, J.C.V.-A., M.B.