## 4 Discussion
As vapor pressure is generally large in low-latitude and low-altitude areas, these findings may imply that atmospheric water vapor influences the measurement accuracy of COSMIC refractivity. Moreover, because atmospheric water vapor generally decreases with height, the vertical mean biases between COSMIC and radiosonde refractivities from 0-5 km, 5-10 km, 10-15 km and 15-20 km are performed, respectively, and the results are presented in Figure 10. It is clear that the refractivity difference between COSMIC and radiosonde data below 5 km is largest in the coastal areas of China, where the atmospheric content of water vapor is higher than in other part of China. From 5 to 10 km, as the atmospheric content of water vapor decreases and the water vapor difference between coastal areas and other areas diminishes, the refractivity bias between COSMIC and radiosonde data decreases, but is still relatively large in wet southern China. Above 10 km, atmospheric water vapor is sparse; therefore, the refractivity bias between COSMIC and radiosonde data varies minimally, and the difference between 10-15 km and 15-20 km is also insignificant. Furthermore, the atmospheric water vapor similarly affects the refractivity RMSE between COSMIC and radiosonde data. As shown in Figure 11, the refractivity RMSE between COSMIC and radiosonde data below 10 km, especially below 5 km, are larger than those above 10 km. The refractivity difference between COSMIC and radiosonde data is closely related to the atmospheric water vapor, and its spatial distribution and variation with altitude exhibit a similar pattern as that of the vapor pressure. Additionally, previous studies found a negative refractivity bias in the lower and middle troposphere [10; 61; 62; 63]. Comparing Challenging Minisatellite Payload (CHAMP) observations with ECMWF analysis results, [PERSON] et al. [64] stated that the negative fractional refractivity difference was nearly 1-4% below 10 km. [PERSON] et al. [33] found that negative refractivity bias only occurs below 3 km for COSMIC data with a value of \(\sim\)1%. Our results indicate that the negative refractivity bias of COSMIC data occurs below 5 km and mainly appears in wet regions, especially southern China, which exhibits the largest difference of \(-\)2.2 N (less than 1%). This result may imply that enhanced atmospheric absorption and water vapor refraction contributes to the large refractivity difference between COSMIC and radiosonde data in the lower troposphere [65]. Moreover, super-refraction is also likely a cause of the negative refractivity bias in this region [62]. Figure 11: The refractivity RMSEs between COSMIC and radiosonde data in China for different altitudes. (**a**) H \(\leq\) 5 km; (**b**) 5 km < H \(\leq\) 10 km; (**c**) 10 km < H \(\leq\) 15 km; (**d**) 15 km < H \(\leq\) 20 km. The number of radiosonde stations for each RMSE class is listed in parentheses. Figure 10: The COSMIC refractivity biases compared to radiosonde observations in China for different altitudes. (**a**) H \(\leq\) 5 km; (**b**) 5 km < H \(\leq\) 10 km; (**c**) 10 km < H \(\leq\) 15 km; (**d**) 15 km < H \(\leq\) 20 km. The red dots are positive biases, and the blue dots are negative biases. The number of radiosonde stations for each bias class is listed in parentheses. Because a model background is used in the retrieval of COSMIC wetPrf profiles of 0-10 km, the mean bias and RMSE profiles of COSMIC retrievals compared to radiosonde are investigated to assess the impact of the background uncertainty on them. As shown in Figure 12a, the mean temperature bias becomes negative below 10 km and reaches the peak at around 5 km height, which suggests that the cold temperature bias between COSMIC and radiosondeis related to more humid conditions in the troposphere. Moreover, the worst temperature bias profile, which occurs in the QTP, has larger bias than the mean temperature bias profile at 4-7 km levels, and the mean temperature bias decreases below 4 km where most samples in the QTP are not available.