## 4 Discussion  
This research shows that C2 moisture information, in general, agrees very well with ERA5 and has larger differences with MERRA-2 (although it still shows relatively good agreement). C2 moisture shows a negative bias within the boundary layer, which is similar to previous research using C1 data [16; 22; 23]. Agreement between C2 and both reanalyses was closest just above the boundary layer (3 km) and decreased into the mid-troposphere (7 km), with C2 displaying slightly more moisture than ERA5 and much less moisture than MERRA-2. Strong correlations were displayed between C2 and both reanalyses, although correlations were typically stronger for C2 and ERA5. Correlations were generally strongest in the subtropics towards the midlatitudes and a bit weaker in the deep tropics. On first glance, it seems this could be related to overall moisture content, as higher SH is observed in the tropics and lower SH is observed in the subtropics. However, this does not hold true everywhere. For example, excellent correlations (>0.9) were observed in subtropical regions with more moisture (such as in the southeastern United States and southeast Asia) whereas  
Figure 11: (**a,c**) Sampling distribution of C2 and ERA5 specific humidity at 3 km and 7 km, and (**b,d**) sampling distribution of C2 and MERRA-2 specific humidity at 3 km and 7 km within 5\({}^{\circ}\)S–5\({}^{\circ}\)N, 60\({}^{\circ}\)W–70\({}^{\circ}\)W from September–December 2019. The number of collocated profile pairs is shown in the title and the correlation coefficient is also shown on each panel. poor correlations were observed in dry tropical regions (such as over the stratocumulus regions off the west coast of South America). Thus, more work is needed to determine the cause of the larger SH variability between C2 and each reanalysis in the deep tropics. However, even though C2 and reanalysis SH agreement is generally good, collocated profile pairs can still show large differences. These large SH differences were observed regardless of whether C2 was compared with ERA5 or MERRA-2, although perhaps unsurprisingly, more variability was observed between C2 and MERRA-2 likely due to the coarser resolution (both spatial and temporal) of MERRA-2, as well as the underlying AGCM used. Additionally, there were a non-insignificant number of profile pairs that exhibited extremely large moisture differences (e.g., greater than \(\pm\)4 g/kg). For example, in Figure 2, the maximum regional mean specific humidity at 3 km is near 8 g/kg. Thus, profiles pairs with SH differences of over 4 g/kg result in biases of 50% or more. Scatterplots of C2-ERA5 humidity vs. C2-MERRA-2 humidity were also made (not shown) which showed that when larger differences between C2 and one reanalysis do occur, they are not necessarily associated with large differences between the corresponding pairs of C2 and the other reanalysis. This indicates that model resolution and physics likely play a large role when large differences do occur, and this would be exacerbated in locations experiencing sharp humidity gradients. Additionally, the largest moisture differences and weakest correlations were typically observed in regions that experience frequent convection. For example, the largest positive bias between C2 and ERA5 at 7 km was observed along the ITCZ, over the Pacific Warm Pool, or over central Africa. We speculate that this could be due to the underrepresentation of moisture within ERA5 in the presence of convection (e.g., deep clouds), but this is purely speculation and would need further studies to confirm. Time series analysis of C2 and reanalysis SH differences were conducted over central Africa (not shown) which displayed a distinct shift in the trend of the differences in late November. For example, C2 exhibited relatively good agreement with MERRA-2 at 3 km from September through late November which shifted to C2 consistently observing less moisture from late November through December.