7A.6 Utilization of specific attenuation for rainfall estimation at S, C, and X bands

Tuesday, 17 September 2013: 11:45 AM
Colorado Ballroom (Peak 4, 3rd Floor) (Beaver Run Resort and Conference Center)
Alexander Ryzhkov, Univ. of Oklahoma/CIMMS, Norman, OK; and P. Zhang, C. Simmer, and M. Diederich

A novel technique for radar rainfall estimation based on utilization of specific attenuation A emerges as a promising alternative to other polarimetric radar QPE methods which use radar reflectivity Z, differential reflectivity ZDR, and specific differential phase KDP. Specific attenuation is estimated from the radial profile of the measured Z and the total span of the differential phase using the ZPHI method. The R(A) estimate is less susceptible to variability of drop size distributions than traditional rainfall algorithms and is immune to radar miscalibration, partial beam blockage, and impact of wet radome. Basic principles of the R(A) method and preliminary results of its performance at S, C, and X bands are summarized in this study. The advantages and shortcomings of the R(A) algorithm are analyzed and illustrated with results of observations. The R(A) method produces rainfall estimates with better radial resolution compared to the R(KDP) estimator but does not work well in “hotspots” like hail, hence the segmentation of the ray is required in the presence of “hotspots” and the R(A) estimates should be complemented by the estimates obtained from the R(Z), R(Z,ZDR), or R(KDP) algorithms. The dependence of the retrieved A on temperature and the net ratio α = A/KDP along the ray may also pose certain problems. The R(A) algorithm is applicable for all radar wavelengths utilized in radar meteorology including S band where attenuation is usually vanishingly small. It is shown that a robust retrieval of A can be made if the total span of differential path ΔΦDP exceeds only 1 - 3° along the ray. Polarimetric radar observations performed at S, C and X bands confirm that the method is immune to partial beam blockage and radar miscalibration and can be very efficient for making rainfall composites using the data from several radars which may operate at different wavelengths.
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