1063 Performance Assessment of Satellite-Based Quatitative Precipitation Estimation during Typhoon Mangkut

Wednesday, 15 January 2020
Hall B (Boston Convention and Exhibition Center)
Xiaoyu Li, Nanning Normal Univ., Nanning, China; and S. Chen

Global Satellite Mapping of Precipitation (GSMaP) and Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) are all precipitation products with the highest spatio-temporal resolution in the current remote sensing precipitation field.Their spatio-temporal resolution reached 0.1°/60min (~10 km) and 0.1°/30min respectively. IMERG takes the advantage of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Climate Prediction Center morphing technique(CMORPH), and TRMM Multi-satellite Precipitation Analysis(TMPA). It provides the public with a suite of QPE products , including Early (Late) run multi-satellite products ~4 (12) hours after observation time, and Final Run multi-satellite product ~2.5 months after the observation month once the monthly gauge analysis is received.Typhoon landing will bring extreme heavy rainfall.Typhoon Mangkut was the largest typhoon in Asia in 2018 when the maximum wind speed reached 162 kilometers per hour, and it was the strongest typhoon since records began in 1949.It is known that the current satellite rainfall products still have limitations in terms of resolution and accuracy, especially for this type of extreme typhoon. In this study, the lastest version 6.0 GSMaP and version 6.0 IMERG products were evaluated for during the 2018 Typhoon Mangkut over China, using Gauge-Calibrated Climate Prediction Centre (CPC) Morphing Technique (CMORPHGC) as reference. Several commonly used skill scores like Root Mean-Squared Error (RMSE), Fractional Standard Error(FSE), Relative Bias (RB), Correlation Coefficient (CC) are used for quantitatively assessing the performance of the satellite-based precipitation products.The performance of satellite-based precipitation products in the characteristic of accumulated rainfall is highlighted in the study. This timely useful feedbacks are expected to offer insights into performance of these precipitation products to both algorithm developers and the scientific end users,and thus provide a better understanding of how well the IMERG products capture the typhoon extreme precipitation events .
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