Assessment of Four Satellite-Based Precipitation Products Over the Pearl River Basin, China

Precipitation is a major driven factor in water cycle and hydrological process. Since satellite sensors have been the main sources for acquiring globally continuous precipitation data, inter-comparison between satellite precipitation products (SPPs) from different sensors becomes increasingly significant, especially at daily or sub-daily scale and in regions suffering from frequent heavy rainfall and floods. This paper assessed the performance of four daily SPPs, including data from the Tropical Rainfall Measuring Mission (TRMM), Climate Hazards group Infrared Precipitation with Stations (CHIRPS), Climate prediction center MORPHmorphing technique (CMORPH) and Advanced SCATterometer (ASCAT) based Soil Moisture to RAINfall algorithm (SM2RAIN-ASCAT), using the ground gauge measurements from 2010 to 2014 over the Pearl River Basin (PRB), China. Accuracy of precipitation estimates and the capability in detecting rainy/non-rainy days and different precipitation categories were evaluated at both basin and station scale. The findings show that: 1) Performance of the SPPs varies temporally and spatially, and better performance can be observed in wet season and south-eastern part of the PRB, when or where precipitation is abundant. 2) All SPPs have poor performance in estimating extreme precipitation in the PRB; 3) Among the four SPPs, TRMM 3B42 exhibits the best performance in the PRB, followed by CMORPH, while CHIRPS performs the worst and is inapt for precipitation estimates in the PRB; SM2RAIN-ASCAT has quite high estimate errors, but it shows advantages against other products in detecting heavy precipitation events. Findings in this study are compared with recent studies conducted in other regions, and some limitations are discussed. This study provides significant reference for understanding the performance of daily SPPs in the PRB as well as areas with similar climate and surface condition.