## 3 Results
### Regional Analysis
For C2 and ERA5 at 3 km (Figure 9a), a moderate relationship (R = 0.597) is observed between the two variables, as SH differences typically increase as the local humidity gradient becomes larger. The relationship between C2 and MERRA-2 at 3 km (Figure 9b) is a bit milder (R = 0.446) and the spread between points is larger, indicating larger SH differences occurring more often. Similar patterns are also observed at 7 km (Figure 9c,d). Correlation coefficients are almost the same (0.413 and 0.426, respectively) albeit with slightly less obvious trends. Based on the sample size (\(n\) = 251), each of these correlation coefficients are significant at the 99% confidence interval. There are some instances where maximum gradients are relatively large and SH differences are small. In these cases, SH differences can be affected by the location of the C2 ray path relative to the gradient (e.g., if both the C2 ray path and the ERA5 profile are on the moist side of the gradient). Additionally, the direction of the C2 ray path relative to the SH gradient was analyzed (not shown). Larger SH differences were more commonly observed when the ray path crossed through the moisture gradient (e.g., Figure 8), although large differences were seen even when the ray path was parallel to the isohumes. Figure 9: (**a,c**) Scatterplot of C2 and ERA5 specific humidity differences vs. the ERA5 local maximum moisture gradient per 100 km at 3 km and 7 km, and (**b,d**) C2 and MERRA-2 specific humidity differences vs. the MERRA-2 local maximum moisture gradient per 100 km at 3 km and 7 km within 10\({}^{\circ}\)N-15\({}^{\circ}\)N, 150\({}^{\circ}\)E-155\({}^{\circ}\)E from September–December 2019. The number of collocated profile pairs is shown in the title and the trend line and correlation coefficient are also shown on each panel. The last analysis section focuses on two regions with poorer correlations from Figure 5. First, we look more closely at central Africa, which is a region that has frequent convection along with some of the deepest convection in the world [47]. This small region was the only location at either altitude where the C2 and ERA5 correlation coefficient was <0.65. Figure 10 shows C2 and ERA5/MERRA-2 SH profile pair sampling distributions at 3 km and 7 km within 5\({}^{\circ}\)S-5\({}^{\circ}\)N, 20\({}^{\circ}\)E-30\({}^{\circ}\)E. At 3 km, agreement is generally better between C2 and MERRA-2 (Figure 10b) than C2 and ERA5 (Figure 10a) even though coefficients are similar. This better agreement is especially obvious in higher-moisture environments. For example, when specific humidity is between 7-10 g/kg, the C2 and MERRA-2 sampling distribution is centered along the 1:1 line whereas ERA5 displays a negative bias of nearly 0.5 g/kg. However, when moisture amounts become lower (between 5-7 g/kg), agreement between C2 and each reanalysis is relatively similar. At 7 km, correlation coefficients become closer to 1 for both reanalyses. Agreement between C2 and ERA5 (Figure 10c) is excellent in low SH environments, while a negative bias for ERA5 SH appears as moisture begins to increase and is largest in the highest SH environments. In contrast, a large positive bias for the MERRA-2 SH is observed at all humidity values (Figure 10d) and confirms the results shown in Figures 4 and 6. Finally, we look at northern South America, which is another region with poorer correlations between C2 and reanalysis SH and also sees frequent convection. Figure 11 shows C2 and ERA5/MERRA-2 SH profile pair sampling distributions at 3 km and 7 km within 5\({}^{\circ}\)S-5\({}^{\circ}\)N, 60\({}^{\circ}\)W-70\({}^{\circ}\)W. At 3 km (Figure 11a,b), the C2 and ERA5 correlation coefficient increases considerably (R = 0.754) relative to over central Africa (R = 0.624). While C2 still displays slightly more moisture than ERA5 at high moisture values (e.g., >8 g/kg), better agreement is generally observed relative to over central Africa.