32nd Conference on Broadcast Meteorology/31st Conference on Radar Meteorology/Fifth Conference on Coastal Atmospheric and Oceanic Prediction and Processes

Thursday, 7 August 2003: 10:30 AM
Rainfall estimation with a polarimetric prototype of the operational WSR-88D radar
Alexander V. Ryzhkov, CIMMS/Univ. of Oklahoma, Norman, OK; and S. Giangrande and T. J. Schuur
Poster PDF (301.4 kB)
As part of the evolution and future enhancement of the WSR-88D, the National Severe Storms Laboratory recently upgraded the KOUN WSR-88D radar to include polarimetric capability. In this paper, we assess the quality of rainfall estimation with the new radar using a dense micronetwork of 42 gages in central Oklahoma. Dataset includes 16 rain events with 32 hours of observations during the period from June to December 2002. One-hour rain accumulations were estimated using a conventional method based on the radar reflectivity factor Z and a new polarimetric algorithm utilizing Z, specific differential phase KDP, and differential reflectivity ZDR. The polarimetric method combines Z and ZDR for light rain, KDP and ZDR for moderate rain, and relies exclusively on KDP for heavy rain. The new algorithm demonstrates superior performance compared to the conventional one. The RMS error of the one-hour total estimate is reduced by factor of 1.5 for point estimates and by factor of 2 for areal rainfall estimates. The suggested algorithm is especially successful in eliminating outliers associated with unusual drop size distributions. The results obtained from the polarimetric WSR-88D are in general agreement with our findings from the previous observations made with the research Cimarron dual-polarization radar in the same area. In addition, they provide indirect proof of the viability of the simultaneous transmission/reception polarization scheme that was adopted for the polarimetric WSR-88D. Because the KOUN data were collected with signal dwell times and antenna rotation rates compatible with existing operational parameters of WSR-88D, it follows that significant improvement in rainfall estimation can be achieved without degradation of the volume update rate.

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