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Hydrology 2018, 5(3), 48;

Mitigating Spatial Discontinuity of Multi-Radar QPE Based on GPM/KuPR

Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
School of Meteorology, University of Oklahoma, Norman, OK 73072, USA
Author to whom correspondence should be addressed.
Received: 30 June 2018 / Revised: 23 August 2018 / Accepted: 30 August 2018 / Published: 1 September 2018
(This article belongs to the Special Issue Remote Sensing in Hydrological Modelling)
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Reflectivity factor bias caused by radar calibration errors would influence the accuracy of Quantitative Precipitation Estimations (QPE), and further result in spatial discontinuity in Multiple Ground Radars QPE (MGR-QPE) products. Due to sampling differences and random errors, the associated discontinuity cannot be thoroughly solved by the single-radar calibration method. Thus, a multiple-radar synchronous calibration approach was proposed to mitigate the spatial discontinuity of MGR-QPE. Firstly, spatial discontinuity was solved by the intercalibration of adjacent ground radars, and then calibration errors were reduced by referring to the Ku-Band Precipitation Radar (KuPR) carried by the Global Precipitation Measurement (GPM) Core Observatory as a standard reference. Finally, Mosaic Reflectivity and MGR-QPE products with spatial continuity were obtained. Using three S-band operational radars covering the lower reaches of the Yangtze River in China, this method was evaluated under four representative precipitation events. The result showed that: (1) the spatial continuity of reflectivity factor and precipitation estimation fields was significantly improved after bias correction, and the reflectivity differences between adjacent radars were reduced by 78% and 82%, respectively; (2) the MGR-QPE data were closer to gauge observations with the normalized absolute error reducing by 0.05 to 0.12. View Full-Text
Keywords: quantitative precipitation estimation; QPE spatial discontinuity; GPM/KuPR; quality control; reflectivity correction; radar calibration error quantitative precipitation estimation; QPE spatial discontinuity; GPM/KuPR; quality control; reflectivity correction; radar calibration error

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Chu, Z.; Ma, Y.; Zhang, G.; Wang, Z.; Han, J.; Kou, L.; Li, N. Mitigating Spatial Discontinuity of Multi-Radar QPE Based on GPM/KuPR. Hydrology 2018, 5, 48.

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