Performance assessment of weighted mean temperature models derived from AIRS and ERA5 reanalysis for calculating GPS precipitable water vapor in the thailand region

Abstract

The determination of Precipitable Water Vapor (PWV) using GNSS data with Precise Point Processing (PPP) is a useful alternative for precisely estimating atmospheric water vapor. The use of GNSS data allows for all-weather PWV tracking 24 h a day, 7 days a week. The weighted mean temperature (T_m) is an important variable in deriving GNSS-PWV values with high accuracy, especially in tropical zones. Unfortunately, the usual method of obtaining T_m is through expensive meteorological instruments such as radiosondes which are not available in every region of Thailand. This current research derives empirical models of T_m based on two data sets: one provided by the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua platform, and one provided in the European Centre for Medium-Range Weather Forecasts’ (ECMWF) ERA5 Reanalysis. GNSS-PWV was calculated for 76 GNSS CORS around Thailand using T_m values calculated by the developed models in conjunction with GipsyX software. Results were validated against AIRS-PWV values, and compared against other existing T_m models. Results based on the developed AIRS-Tm and ERA5-Tm models, as well as the existing Suwantong, Bevis, Mendes, Schueler, and GPT3 models, showed mean biases in PWV difference against AIRS-PWV values of 0.3, 0.2, − 0.3, 1.0, 0.8, 1.8, and 1.1 mm, respectively. These results conclude that the mean bias of GPS-PWV estimations can be reduced when a more localized countrywide T_m model is used versus a global model.