## 1 Introduction
's (2018) research of wet profiles obtained from GPS RO and radiosonde over China, temperature differences between two observations were found positively correlated with station altitudes in the Qinghai-Tibet Plateau region, while pressure, water vapor pressure, as well as refractivity differences, were negatively correlated with altitudes. Authors speculated the differences between GPS RO and radiosonde observations at high altitude area might be caused by the complex topography and the limitation in the background models used in GPS RO retrievals. Also, [PERSON] et al. pointed out that a negative refractivity difference of two observations occurs below 5 km and is related to humid atmosphere and super-refraction. Similar results can be found in [PERSON] et al. 's (2018) research of negative refractivity over the ocean. The differences are found after comparing to the reanalysis data and show a seasonal clustered variation over oceans where super-refraction often occurs. Earlier studies about the validation of GPS RO and radiosonde PW observations make weather and climate research using these observations convincing. With the water vapor obtained from GPS RO technique, special cases such as storm events and baroclinic disturbances in certain regions are detected and analyzed in higher temporal and spatial resolution ([PERSON] et al., 2016). [PERSON] et al. (2016) compared the humidity variations during a strong typhoon by using radiosonde observations and GPS RO observations; the result confirms the superiority of the satellite GPS RO observations of atmospheric water vapor during extreme weather when radiosondes cannot function fully. Moreover, in [PERSON] et al. 's study of 2018 ([PERSON] et al., 2018), GPS RO observations of atmospheric total water vapor were compared to microwave radiometers, and they found that GPS RO retrievals are rarely affected by weather such as clouds and precipitation, which is one of the advantages of RO observations. In recent years, more research has been focused on the relationships between PW (water vapor content) and specific meteorological variables, such as the temperature of different levels, the rainfall amount, atmospheric general circulation, etc. The climatological characteristics of PW in different regions have also been studied in the recent years. [PERSON] and [PERSON] (2018) studied atmospheric water vapor from 1970 to 1990 in China, and the positive correlation between PW and precipitation over China is confirmed; seasonal correlation differences are also observed. [PERSON] et al. (2018) studied the variability of PW over India in detail, and a diurnal cycle coinciding with the daily solar cycle is discovered in this country with differences in regions. Moreover, the relationship between PW and the Asia monsoon is revealed in China and India [16; 17]; PWs in both countries show seasonal correlations. Studies of PW also show that PW is affected by North Atlantic Oscillation (NAO) in Turkey [18] and El Nino-southern oscillation (ENSO) events [19]. However, GPS RO records used in this study only have observations since 2006, which is not long enough for climate research; radiosonde observations only have measurements over land twice-daily and the global station distribution is uneven, which makes global climate research of PW incomplete. Using both GPS RO and radiosonde observations, the full coverage of global PW climate characteristics is studied in this study. We evaluated the consistency in PWs calculated from two observational datasets. Besides the spatial and temporal variations in global PW, the long-term trend (60-year radiosonde records) and most recent decade trend (10-year COSMIC data) in PW are also studied. The data and methods used in this study are presented in Section 2. Section 3 presents the results, firstly with a detailed comparison of two observation results and then followed by the results of variabilities and trends in PW. Section 4 consists of the conclusions.