Estimation of Missing GPS Precipitable Water Vapor Data by Zenith Wet Delay and Meteorological Data

Abstract

This article presents a statistical correlation between GPS precipitable water vapor and meteorological data, i.e., surface temperature, air pressure, relative humidity, dew point temperature, and water vapor pressure by using linear regression. The data, recorded over a 4-year period, was used as an estimation of missing GPS precipitable water vapor data from discontinuous recordings. A multiple linear regression equation showed a correlation among zenith wet delay (ZWD), water vapor pressure (e) and surface temperature (T) was ZWD(e,T) = 17.4952e-0.8281T-93.164, with a coefficient of determination (R2) of 0.725, a mean absolute error of 8.71 mm, a root mean square error of 10.39 mm, and a mean absolute percentage error of 18.63%. The equation obtained can be used to estimate GPS precipitable water vapor data which is missing from recordings due to accident or technological error.