Evaluation and mapping of precipitable water in Southeast Asia using ground-based and satellite data for solar energy application

Abstract This article presents column integrated precipitable water (PW) readings from a NASA satellite and fourteen sites of the Aerosol Robotic Network (AERONET). The Terra satellite was compared with that obtained from ground-based observations in the tropics. It was found that the PW from the MODIS aboard the Terra satellite and those obtained from ground-based observations were in good agreement, with a root mean square error (RMSE) of 4.27% and a mean bias error (MBE) of 0.03% for the monthly. Develop empirical model to estimate the PW using data from relative humidity (AIRS) and temperature (AIRS) of ambient air. The model was developed to determine the daily and monthly PW based on PW data obtained from these stations over a 5-year period (2012–2016) and it was then validated against independent data for the previous 4-year period (2017–2020). It can be seen that the monthly PW values calculated using the empirical model had a RMSE of 3.64%. Develop a model2 to allow users to estimate the PW, namely relative humidity (AIRS) and temperature (GLDAS Model) of ambient air. This model2 performs reasonably when tested against an independent data set with the root mean square error (RMSE) and mean bias error (MBE) of 9.30% and − 0.05%, respectively (daily) and 3.58% and 0.02%, respectively (monthly). This research presents PW resource maps generated with the Geographic Information System (GIS) by satellite-based data from the Terra satellite for the 21-year period (2000–2020) and from AIRS (relative humidity and temperature) for the nineteen-year period (2002–2020). According to the monthly PW maps, Southeast Asia's PW values are generally high during the wet season (May to October) and low during the dry season (November to April) and according to the annual PW map, areas near the sea have high PW.