One of the key parameters in climate change is Precipitable Water Vapor (PWV) which plays an important role in identifying precipitation distribution, hydrological cycles and important meteorological and climatic phenomena. Therefore, it is important to study the long-term changes in PWV time series in an area. MODIS near-infrared PWV product (MOD-NIR-PWV) provides a suitable spatial coverage of PWV with a resolution of 1 km and temporal resolution of 1 day. This study compares statistically the time series of MODIS PWV from 2000 to 2018 with radiosonde values. MODIS data under cloudless conditions at a maximum distance of 1 km from the position of the radiosonde station were used for statistical analysis. The results show that the consistency between two sets of water vapor data in terms of correlation coefficient was obtained at 0.81, 0.78 and 0.67 in Tehran, Isfahan and Mashhad stations, respectively. Also, the linear trend of PWV time series in the study areas was investigated using Mann-Kendall (MK) statistical test. PWV values in both datasets have undergone similar trends, according to time series analysis of radiosonde and MODIS. Therefore, free remote sensing methods such as MODIS products along with local data can be used for long-term studies of PWV to study the trends of the PWV parameter. Furthermore, a decrease in precipitation and an increase in surface temperature along with an increase in the PWV value of MODIS data was observed in studies with synoptic data in the studied stations, which may in some way reflect the effects of global warming in the studied stations. D