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Evaluating three satellite-based precipitation products of different spatial resolutions in Shanghai based on upscaling of rain gauge

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Gridded precipitation products have been widely used in scientific literatures, e.g., weather forecasting, hydrological process modelling and disaster simulating. However, it is necessary to evaluate their accuracies before using them for practical purposes. In this study, three mainstream different-spatial-scale daily gridded precipitation data (GPD), including [Global Satellite Mapping of Precipitation–gauge adjusted (GSMAP_Gauge), TRMM 3B42 version-7 (TRMM 3B42V7) and Global Precipitation Climatology Project version 1.2 (GPCP-V1.2)] were systematically evaluated against local rain gauges for their ability to detect precipitation characteristics of Shanghai in 2008 based on upscaling of rain gauge. In general, the gridded precipitation products overestimate precipitation compared to upscaled ground observations (UGOs). However, all of the products have an obvious underestimation on extreme precipitation (>50 mm day−1). In contrast, the results show that GSMaP_Gauge has the highest correlation coefficient, TRMM 3B42V7 has the lowest RMSE, and Probability of Detection (POD) in GPCP-V1.2 is better than that in TRMM 3B42V7 and GSMaP_Gauge. As the spatial resolution decreases, the frequency and amount of extreme precipitation events decrease regardless of detection from UGOs and GPD. We also find that those heavy precipitation events detected from TRMM 3B42V7 at 0.25° and 1.0° are significantly underestimated. Overall, we believe that it is necessary to evaluate gridded precipitation products at the urban scale based on upscaling of rain gauge.
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Document Type: Research Article

Affiliations: 1: Institute of Urban Studies, Shanghai Normal University, Shanghai, China 2: Department of Civil and Environmental Engineering, Princeton University, Princeton, USA 3: Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China 4: Department of Architecture, Built Environment and Construction Engineering, Politecnico Milano, Milano, Italy 5: Department of Geography, Shanghai Normal University, Shanghai, China 6: Shandong Academy of Building Research, Jinan, China 7: Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

Publication date: August 3, 2019

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