Tropospheric delay is considered as a disturbing parameter in GNSS positioning. Therefore, it is necessary to eliminate or reduce its effects in order to increase the accuracy of position determination. However, nowadays for meteorological applications such as precipitation prediction, the amount of water vapor in troposphere is determined by obtaining the delay of GPS signal while crossing Earth’s atmosphere because tropospheric delay is a function of pressure, temperature and humidity.
Since the development of the meteorology with GPS methods in 1990s, global navigation satellite system is known as an effective way to study atmosphere, e.g. the estimation of zenith tropospheric delay. Tropospheric delay can be estimated in two ways, the double differencing technique and precise point positioning technique. In precise point positioning technique, one receiver is used to collect data. This method is used to directly derive zenith tropospheric delay by non-differenced observations.
Today, permanent GPS networks not only are used for geodetic and surveying applications but also are used to determine the amount of water vapor in troposphere. In fact, these networks are used to predict weather condition. To do this, along with GPS receivers, meteorological sensors should be installed and functioned. These sensors are used to measure surface pressure, humidity and temperature. The collected data are used in existed equations such as Saastamoinen equation for the case of prediction.
Knowing the exact amount of water vapor in the atmosphere is of great importance in predicting the weather. In this study, due to the benefits of the dual differential method, such as low costs, Precise Point Positioning (PPP) approach has been used. Also by using Precise Point Positioning (PPP) approach, Zenith Tropospheric Delay (ZTD)  parameter estimated with the help of GPS receivers of SAMT system and TEHN station. Observations have been used for twenty consecutive days from 07/10/2015 to 07/29/2015. By using synoptic meteorological data, the share of the hydrostatic (dry) section from the non-hydrostatic (wet) section in Zenith Tropospheric Delay is separated. Then by using the transfer function, the delay caused by the non-hydrostatic section which is due to water vapor in the atmosphere, turned into water vapor that could rain. For processing, the three types of clock and final orbital data, rapid and ultra-rapid data produced by the International Global Navigation Satellite System (GNSS) Service (IGS) have been used. Observations was Processed in the software Bernese 5.0. The obtained results were compared with the results of precipitation weather stations. To validate the amount of water vapor calculated by the GPS, we used the corresponding values were observed by radiosonde. For this purpose, the TEHN GPS stations and Mehrabad Airport weather station was selected. The results showed that when clock and final orbital data were used, the standard deviation, RMS and correlation were 1/2564, 1/0962 and 0/9698 Respectively, And when clock and rapid orbital data were used, these parameters were 1/5650, 1/2235 and 0/9647, respectively. Finally, The values of standard deviation, RMS and correlations for ultra-rapid data were 2/6086, 1/5796 and 0/9352, respectively.