Abstract
The Global Precipitation Mission (GPM) Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6) with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.
Highlights
Precipitation is a key determining factor for planetary water cycles, the energy cycle, and many socioeconomic activities, and is a primary input for hydrometeorological and climate models [1,2].accurate estimation of rainfall amounts at sufficient temporal and spatial resolutions is crucial for a wide range of applications from global climate and hydrological modeling to local weather and flood forecasting [3]
The results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users
Global Satellite Mapping of Precipitation product (GSMap)-Gauge was corrected by observational data in this study, it still resulted in negative mean error (ME) values
Summary
Accurate estimation of rainfall amounts at sufficient temporal and spatial resolutions is crucial for a wide range of applications from global climate and hydrological modeling to local weather and flood forecasting [3]. Ground-based measurement networks (rain gauges) tend to be distributed unevenly or are sparse, and may be unable to capture the spatial and temporal variability of precipitation systems, especially over remote/rural areas where these measurement networks are, in some cases, nonexistent. This lack of spatial coverage constitutes a significant challenge for applications of gauge-based rainfall estimates at regional and global scales [4,5,6]
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