Abstract

This study evaluates the capacity of three gridded precipitation products (MSWEP V2.2, TRMM-3B42 V7, and GPM-IMERG V6) to detect precipitation in the Min Jiang watershed, a data-scarce and mountainous region in western China. A set of statistical and contingency indices is calculated for the precipitation products and compared with rain gauge observations at 23 ground stations from July 2000 to May 2016. Consistency between gridded and ground precipitation datasets is examined at different temporal (i.e., daily, monthly, seasonally, and annually) and spatial (i.e., site level, sub-regional level, and watershed level) resolutions. We identify possible reasons for discrepancies among precipitation datasets. Our results indicate that: (1) the MSWEP product is best suited for the study of long-term mesoscale rainfall, rather than short-term light or extreme rainfall; (2) the IMERG product represents stable performance for the simulation of rainfall spatial variability and detection capability; and (3) Composition of the datasets, climatic systems, and regional topography are key factors influencing the consistency between gridded and ground precipitation datasets. Therefore, we suggest using MSWEP V2.2 and GPM-IMERG V6 as potential precipitation data sources for hydrometeorological studies over the Min Jiang watershed. The findings of this study inform future hydrometeorological and climate applications in data-scarce regions with complex terrain.

Highlights

  • Reliable long-term records of precipitation at high spatiotemporal resolutions can support a wide range of applications, such as hydrological model optimization [1,2], water resources management [3,4], drought and flood forecast and warning [5,6,7,8], agricultural irrigation planning [9,10], hydrometeorology analysis [11,12], and climate studies [13,14,15,16]

  • The Min Jiang or Min River is located in southwest China, between 102◦ 590 E and longitude and 29◦ 530 N and 33◦ 150 N latitude

  • We evaluated three gridded precipitation products, including Multi-Source Weighted-Ensemble Precipitation (MSWEP)

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Summary

Introduction

Precipitation is a primary component of the global water cycle and energy balance.Reliable long-term records of precipitation at high spatiotemporal resolutions can support a wide range of applications, such as hydrological model optimization [1,2], water resources management [3,4], drought and flood forecast and warning [5,6,7,8], agricultural irrigation planning [9,10], hydrometeorology analysis [11,12], and climate studies [13,14,15,16].Information on precipitation from imagery and measurements provides an understanding of a region’s climate and is needed to facilitate rainfall prediction (e.g., about potential flooding and droughts) [17]. Reliable long-term records of precipitation at high spatiotemporal resolutions can support a wide range of applications, such as hydrological model optimization [1,2], water resources management [3,4], drought and flood forecast and warning [5,6,7,8], agricultural irrigation planning [9,10], hydrometeorology analysis [11,12], and climate studies [13,14,15,16]. Accurate precipitation datasets with the high spatiotemporal resolution and long-term records are difficult to achieve [18], in mountainous areas, mainly due to the inadequate and uneven distribution of ground observation 4.0/). Complex topography and variable rainfall characteristics add particular challenge in regions where ground-based precipitation monitoring is limited [22]

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