Hydrologic Evaluation of TRMM and GPM IMERG Satellite-based Precipitation in a Humid Basin of China

Zengxin Zhang,Zheng Duan,Xi Chen,Yuhan Huang,Jiaxi Tian,Sheng Chen

doi:10.3390/rs11040431

Abstract

Tropical Rainfall Measurement Mission (TRMM) is one of the most popular global high resolution satellite-based precipitation products with a goal of measuring precipitation over the oceans and tropics. However, in recent years, the TRMM mission has come to an end. Its successor, Global Precipitation Measurement (GPM) mission was launched to measure the earth's precipitation structure, with an aim to improve upon the TRMM project. Both of the precipitation products have their own strengths and weaknesses in resolution, accuracy, and availability. The aim of this study is to evaluate the hydrologic utilization of the TRMM and GPM products in a humid basin of China. The main findings of this study can be summarized as follows: (1) 3B42V7 generally outperforms 3B42V6 in terms of hydrologic performance. Meanwhile, 3B42RTV7 significantly outperforms 3B42RTV6, and showed close performance with the bias-adjusted TRMM Multi-satellite Precipitation Analysis (TMPA) products. (2) The GPM showed better agreement with gauge observation than the TMPA products with lower RB and higher correlation coefficient (CC) values at different time scales. (3) The VIC hydrological model generally outperformed the XAJ hydrological model with lower RB, higher Nash–Sutcliffe Coefficient of Efficiency (NSCE) and CC values; though the 3B42RTV6 and 3B42RTV7 showed higher CC values in simulating the streamflow hydrograph by using the VIC and XAJ hydrological models. It can be found that the conceptual hydrological model was enough for the hydrologic evaluation of TRMM and GPM IMERG satellite-based precipitation in a humid basin of China. This study provides a reference for the comparison of multiple models on watershed scale.

Highlights

Precipitation is one of the key input data for various hydrological models
Chen [6] thought that 3B42V7 clearly improved upon 3B42V6 over China in terms of daily mean precipitation; Yong et al [10] reported that 3B42RTV7 represented a substantial improvement over 3B42RTV6 with respect to the systematic bias in the low-latitude Mishui basin; Liu [8] found that 3B42V7 detected more rain events than 3B42V6 in June, July, and August along with December, January and February; Jiang et al [11] revealed that the 3B42RTV7 and 3B42V7 precipitation products had better performance in estimating precipitation in the Ganjiang River basin; Fei et al [12] indicated that 3B42V7 was better than 3B42V6 at seasonally and monthly scales
The spatial distribution of annual mean precipitation over the Ganjiang River basin derived from the observation and four TRMM Multi-satellite Precipitation Analysis (TMPA) products were analyzed during the period of 2003 to 2010

Summary

Introduction

Precipitation is one of the key input data for various hydrological models. The accuracy of precipitation is vital to improve hydrological simulation [1,2]. Several satellite-based precipitation products have been emerged to provide uninterrupted precipitation time series with quasi-global coverage. These satellite-based precipitation products provide an unprecedented opportunity for hydro-meteorological applications and climate studies [5,6]. Chen [6] thought that 3B42V7 clearly improved upon 3B42V6 over China in terms of daily mean precipitation; Yong et al [10] reported that 3B42RTV7 represented a substantial improvement over 3B42RTV6 with respect to the systematic bias in the low-latitude Mishui basin; Liu [8] found that 3B42V7 detected more rain events than 3B42V6 in June, July, and August along with December, January and February; Jiang et al [11] revealed that the 3B42RTV7 and 3B42V7 precipitation products had better performance in estimating precipitation in the Ganjiang River basin; Fei et al [12] indicated that 3B42V7 was better than 3B42V6 at seasonally and monthly scales. Chen et al [6] discovered that the 3B42V7 precipitation product showed a slightly downgraded performance at daily scale in the Qinghai-Tibetan plateau

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Conclusion