Correlation Analysis of GNSS-Derived Precipitable Water Vapor (PWV) with Rainfall Data in Indonesia

Abstract

GNSS (Global Navigation Satellite Systems) have become an important tool for various activities related to positioning, such as navigation, construction projects, and deformation measurement. Additionally, GNSS can also estimate Precipitable Vapor Vapor (PWV) for meteorological purposes. PWV is a measure of atmospheric water vapor, which can eventually precipitate as rain. Since Indonesia’s climate is mainly characterized by the change in rainfall, monitoring precipitation is a crucial step in understanding its pattern. In this study, we aim to analyze the correlation between PWV and rainfall in Indonesia. We used GNSS observations from the InaCORS network across Indonesia, as well as rainfall data from GSMaP at the InaCORS stations in 2019 from 1st January to 31st December. Both of these data are normalized every five days (pentad days) and compared to each other to obtain the Pearson’s correlation coefficients. From these results, we generated a heatmap of the Pearson’s correlation coefficients between pentad PWV and rainfall at InaCORS locations in Indonesia, with the highest correlation of 0.753819 in Garut Regency and the lowest correlation of 0.090146 in Fakfak Regency. Moreover, we also analyzed the timeseries of PWV and rainfall comparison at several sampling stations. From the results we found, PWV and rainfall correlate each other in positive way. Southern regions of Indonesia have higher correlation compared to northern regions of Indonesia.