Abstract
Extreme precipitation has received much attention because of its implications for hazard assessment and risk management. However, accurate precipitation information for extreme precipitation research from dense rain gauges is still difficult to obtain in developing countries or mountainous regions. Satellite-based precipitation products (SPPs) with high spatial and temporal resolution offer a new way of supplementing data from gauge-based observations. This study aims to evaluate the precision of six SPPs in detail at multiple temporal and spatial scales and explore their ability to capture the characteristics of extreme precipitation from 2009 to 2014 over a semi-arid to semi-humid climate transition area (Wei River basin) in China. The six products are TRMM 3B42RT, TRMM 3B42V7, PERSIANN, PERSIANN CDR, CMORPH RAW, and CRORPH CRT. China gauge-based daily precipitation analysis (CGDPA) provided by the China Meteorological Administration is used as the benchmark reference data. Various statistical evaluation techniques and extreme precipitation indices are used to evaluate and compare the performance of the selected products. The results show that the post real-time products (TRMM 3B42V7, PERSIANN CDR, and CMORPH CRT) agreed better with the reference data than PERSIANN and CMORPH RAW. On a daily scale, TRMM 3B42V7, PERSIANN CDR, and CMORPH CRT displayed similarly good performance. However, at the monthly or annual scale, TRMM 3B42V7 was superior to the other products. With regard to the spatial distribution of precipitation, the datasets performed better over plains and were disappointing over mountainous areas. Additionally, TRMM 3B42V7 provided higher precision and less spatial uncertainty when monitoring extreme precipitation. This study provides a basis for selecting alternative precipitation data for climate transition basins.
Highlights
Extreme precipitation refers to when the amount of a precipitation event exceeds a certain threshold [1], resulting in a series of social, environmental, and ecological problems [2,3]
We found that the R0.1 mm values for CMORPH RAW, CMORPH CRT, PERSIANN, and PERSIANN CDR had a wide distribution, indicating uncertainty in capturing precipitation days
We found that the post real-time products (TRMM 3B42V7, CMORPH CRT, and PERSIANN CDR) had a higher precision for the Wei River basin
Summary
Extreme precipitation refers to when the amount of a precipitation event exceeds a certain threshold [1], resulting in a series of social, environmental, and ecological problems [2,3]. Amplified by the observed climate change, many studies have shown that extreme precipitation events have become more intensive than they were in the past and are likely to further intensify in the future [4,5,6]. The most popular SPPs include the tropical rainfall measuring mission (TRMM) [15], climate prediction center (CPC) morphing technique (CMORPH) [16], precipitation estimation from remotely sensed information using artificial neural networks (PERSIANN) [17], global satellite mapping of precipitation (GSMaP) [18], global precipitation measurement (GPM) [19], naval research laboratory blended satellite (NRL-Blend) high-resolution precipitation product (HRPP) [20], and climate hazards group infrared precipitation with station data (CHIRPS) [21]
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