Water vapor in the atmosphere is one of the primary greenhouse gases, and has a significant impact on climate change (Kiehl & Trenberth 1997). For research on climate change and numerical weather forecasting, it is important to have accurate estimates of the amount and the distribution of water vapor. However, this is difficult due to the high spatial and temporal variability of water vapor (Bevis et al. 1992). Zenith total delay (ZTD) estimates based on the Global Navigation Satellite System (GNSS) can be transformed into atmospheric water vapor content (Bevis et

The performance of up-to-date mapping functions and various mean temperature equations were analyzed to derive optimal mapping function and mean temperature equation when GNSS precipitable water vapor (PWV) was investigated in the Korean Peninsula. Bernese GNSS Software 5.2, which can perform high precision GNSS data processing, was used for accurate analysis, and zenith total delay (ZTD) required to calculate PWV was estimated via the Precise Point Positioning (PPP) method. GNSS, radiosonde, and meteorological data from 2009 to 2014 were acquired from Sokcho Observatory and used. ZTDs estimated by applying the global mapping function (GMF) and Vienna mapping function 1 (VMF1) were compared with each other in order to evaluate the performance of the mapping functions. To assess the performance of mean temperature equations, GNSS PWV was calculated by using six mean temperature equations and a difference with radiosonde PWV was investigated. Conclusively, accuracy of data processing was improved more when using VMF1 than using GMF. A mean temperature equation proposed by Wu (2003)