## 3 Results and Discussion
### Spatial and Seasonal Variations
In order to investigate the detailed latitudinal variability of PW, zonal mean values are obtained in latitudinal bins. The numbers of soundings (COSMIC) and stations (IGRA) in each latitude bin are presented in Figure 5. Note the sparse radiosonde station distribution in the southern hemisphere, which brings a larger uncertainty to the radiosonde results in this region (Figure 5b). In general, the patterns of the latitudinal variation of two observational datasets are quite similar. These patterns are also consistent with the global precipitation variation decreasing from the tropics to two poles reported by [PERSON] et al. (2018). In the Southern Hemisphere, PWs are very similar in different seasons; while in the Northern Hemisphere, PWs in four seasons show larger differences in magnitude. For example, PW in the Northern Hemisphere summer is obviously larger than in the other three seasons, especially for the region with latitudes larger than 30\({}^{\circ}\) N. It is consistent that larger PW values occur in the summer of the Northern Hemisphere, as mentioned in Figure 4.  
To quantify the differences between two observations, the PW differences of two observations in latitudinal variations are analyzed, along with the standard deviations of latitudinal seasonal results (Figure 6). Regarding the standard deviations of two datasets, they are generally larger in the Northern Hemisphere. The larger standard deviations for the IGRA PWs may result from the inhomogeneous stations' distribution. The differences range from \(-6\) mm to \(12\) mm and vary in latitude (Figure 6c). The distinct differences occur in the tropical area and they are generally more than \(5\) mm. The differences decrease linearly from the tropical region to the mid-latitudes. Overall, IGRA PW is larger than COSMIC PW. There are two exceptions. One is the high latitudes in the Southern Hemisphere, with a COSMIC PW 1 mm larger. The other one is the region around 30\({}^{\circ}\) N in the Northern Hemisphere: the COSMIC PWs are about \(5\) mm larger than the ones derived from radiosonde. Figure 5: Latitudinal variation of seasonal mean PW derived from two observations (**a**: COSMIC; **b**: IGRA). In addition, the different variations also show apparent seasonal features. For the 30\({}^{\circ}\) S to 30\({}^{\circ}\) N region, except for the equator region, differences in summer are usually greater than the ones in winter. No seasonal variations are found around the equator region. The seasonal differences are close there. Regarding the middle and high latitudes in the Southern Hemisphere, the differences do not show any seasonal variability either, and the values are around 0. On the other hand, for the middle and high latitudes in the Northern Hemisphere, the seasonal differences show a different pattern. The largest differences occur in autumn and spring, while differences in summer and winter are both close to 0. The IGRA PW is about 2 mm greater than the COSMIC PW in autumn, while it is the opposite situation for the spring. The PWs derived from COSMIC in autumn and spring are similar from about 40\({}^{\circ}\) N to 90\({}^{\circ}\) N (Figure 5a). However, the IGRA PWs in autumn are generally greater than the ones in spring in this region (Figure 5b), which may result in the different patterns in the seasonal differences (Figure 6c). In Figure 6d, the percentage of PW differences of IGRA and COSMIC shows that large differences in magnitude do not equal large differences in percentage. Even though the differences in polar regions between two observations are small (Figure 6c), the corresponding percentages of differences are relatively larger than the ones in the tropical region. For the regions from 60\({}^{\circ}\) S to 30\({}^{\circ}\) N, the differences in percentages are within 20%, with little seasonal variations. There are two latitudinal bins with percentages larger than 50%. One is the difference in winter and autumn over the Antarctic. For this region, the observation itself may have large uncertainties.