Precipitable water vapor (PWV) is a parameter that used to describe the water vapor content in the atmosphere has the potential to become a precipitation. Thus, it is important to measure PWV and investigate its trends and variability for potential forecasting precipitation. This study presents the variation of PWV at Tanay Upper Station (14°34’52.8”N, 121°22’08.9”E) from radiosonde operated by the Philippine Atmospheric, Geophysical and Astronomical Services Administration and at PIMO station (14°38’08.5”N, 121°04’39.4”E) using Global Navigation Satellite System (GNSS) operated by NASAJet Propulsion Laboratory under the International GNSS Service (IGS) network from 2015-2017. Moreover, there is no significant difference (p-values < 0.05) among PWV radiosonde, GNSS-PWV and rainfall as a function of year of observation. Monthly mean variation conforms to the Coronas climate classification, Climate Type I, in terms of the amount of precipitation. It is shown that PWV is high during wet months and least during dry months (November to April). Further, monthly mean variation is moderate correlated with surface temperature from radiosonde (R = +0.589). Evaporation rate depends on the surface temperature, which contributes in forming water vapor. The results showed that PWV from radiosonde gave reasonable values to be considered during wet and dry season as well as the seasonal variation of rainfall.
Precipitable water vapor (PWV) is a parameter used to estimate water vapor content in the atmosphere. In this study, estimates of PWV from PIMO, PLEG and PPPC global navigation satellite system (GNSS) stations are evaluated regarding the PWV obtained from its collocated radiosonde (RS) stations. GNSS PWV were highly correlated with RS PWV (R ~ 0.97). Mean bias error (MBE) between −0.18 mm and −13.39 mm, and root mean square error (RMSE) between 1.86 mm and 2.29 mm showed a good agreement between GNSS PWV and RS PWV. The variations of PWV are presented. Daily variations of PWV conformed to the daily data of rainfall which agrees to the climate types of Quezon City (Type I), Legaspi (Type II), and Puerto Princesa (Type III) based on the Coronas climate classification. Moreover, PWV monthly variation at all sites is high from May to October (~62 mm) and low from November to April (~57 mm). The relationship between PWV and rainfall at all stations showed positive correlation coefficients between +0.49 to +0.83. Meanwhile, it is observed that when PWV is high (low), its variability is low (high). This study shows the potential of GNSS to study water vapor and its contribution to weather analysis.
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