Evaluation of the Global Satellite Mapping of Precipitation (GSMaP) data on sub-daily rainfall patterns in Vietnam

This study aims to evaluate the performance of Global Satellite Mapping of Precipitation (GSMaP) data in observing the sub-daily rainfall patterns in Vietnam using synoptic gauge measurements considering seasonal variations in rainfall. Differences in the estimations of the three GSMaP products, including the standard version 7 (MVKv7) and two gauge-calibrated versions 6 and 7 (GAUv6 and GAUv7), were clarified based on rainfall characteristic parameters and statistical indices. The present study clarified that the contribution of sub-daily rainfall in Vietnam was higher during the afternoon than at other times, predominantly in the Central Highlands and Southern Plain, while it occurred most often during the evening to early morning in northern regions. Distinct regional features were also identified along the central coast. Most of the summer afternoon maximum fell in the western mountainous area, while the eastern coastal plain experienced an insignificant amount of rainfall. As rainfall characteristics varied with seasons and regions, the performance of GSMaP demonstrated this variation quite well compared to in-situ observations. However, GSMaP still exhibited high biases in rainy season and topographically heterogeneous areas, especially in the northern regions where sub-daily rainfall cycles had large variations. The standard GSMaP (MVK) product illustrated an afternoon peak better than the gauge-calibrated (GAU) product, which suggests that utilizing the MVK in the Central Highlands and Southern Plain and the GAU over central coastal regions would be appropriate when considering the characteristics of sub-daily precipitation.

A Comparison Between Global Satellite Mapping of Precipitation Data and High-Resolution Radar Data – A Case Study of Localized Torrential Rainfall over Japan

This paper presents a case study comparing the latest algorithm version of Global Satellite Mapping of Precipitation (GSMaP) data with C-band and X-band Multi-Parameter (MP) radar as high-resolution rainfall data in terms of localized heavy rainfall events. The study also obliged us to clarify the spatial and temporal resolution of GSMaP data using high-accuracy ground-based radar, and evaluate the performance and reporting frequency of GSMaP satellites. The GSMaP_Gauge_RNL data with less than 70 mm/day of daily rainfall was similar to the data of both radars, but the GSMaP_Gauge_RNL data with over 70 mm/day of daily rainfall was not, and the calibration by rain-gauge data was poor. Furthermore, both direct/indirect observations by the Global Precipitation Measurement/Microwave Imager (GPM/GMI) and the frequency thereof (once or twice) significantly affected the difference between GPM/GMI data and C-band radar data when the daily rainfall was less than 70 mm/day and the hourly rainfall was less than 20 mm/h. Therefore, it is difficult for GSMaP_Gauge to accurately estimate localized heavy rainfall with high-density particle precipitation.