Real-time estimation of mean field bias in radar rainfall data

Abstract To reduce systematic errors in radar rainfall data used for operational hydrologic forecasting, the precipitation estimation stream in the National Weather Service (NWS) uses procedures that estimate mean field bias in real time. Being a multiplicative correction over a very large area, bias adjustment has a huge impact, particularly on volumetric estimation of rainwater, and hence performance of the procedure is extremely important to quantitative hydrologic forecasting using radar rainfall data. In this paper, we describe a new procedure for real-time estimation of mean field bias in WSR-88D (Weather Surveillance Radar—1988 Doppler version) rainfall products. Based largely on operational experience of the existing procedures in NWS, the proposed procedure is intended to be unbiased, parsimonious, and intuitive. To evaluate the procedure, true validation is performed using hourly rain gage and WSR-88D rainfall data from Tulsa and Twin Lakes, Oklahoma.

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