Advantages of GSMaP Data for Multi‐Timescale Precipitation Estimation in Luzon

Abstract

For climate and hydrological research, it is important to explore rainfall variation, as it is closely related to human lives, particularly in the context of economics, agriculture, and disaster prevention (Hung & Shih, 2019). In general, rainfall can be estimated using local rain gauges, radar, and satellite observations (Hsu et al., 2021;Huang & Chan, 2012). However, observations by rain gauges and radars are limited in spatial coverage and observation time (Chen et al., 1999;. In contrast, satellite-based rainfall estimation (SRE) with high spatial coverage can monitor a wider spatial range of rainfall variations Huang et al., 2023). Therefore, SRE is often used for various research purposes (e.g., climate studies, validating model performance, and other studies) (

Evaluation of Multiple Satellite, Reanalysis, and Merged Precipitation Products for Hydrological Modeling in the Data-Scarce Tributaries of the Pearl River Basin, China

“…It is worth noting that GSMaP exhibits the best performance, while the worst performance was found for PERSIANN-CCS and GSMaP-RNL. Their differing behavior patterns across the study basins may be attributed to the differences in the gauge-adjustment methods and the biases in their pre-non-gauge-adjusted products [68]. In addition, the spatial variability of errors in precipitation estimation can be caused by various factors such as complex terrains, climate, land-cover changes, and anthropogenic influences [69].…”