Performance evaluation of high-resolution rainfall estimation by X-band dual-polarization radar for flash flood applications in mountainous basins

Abstract

Different relations between surface rainfall rate, R , and high-resolution polarimetric X-band radar observations were evaluated using a dense network of rain gauge measurements over complex terrain in Central Italian Alps. The specific differential phase shift, K DP , rainfall algorithm ( R KDP ) although associated with low systematic error it exhibits low sensitivity to the spatial variability of rainfall as compared to the standard algorithm ( R STD ) that is based on the reflectivity-to-rainfall ( Z – R ) relationship. On the other hand, the dependence of the reflectivity measurement on the absolute radar calibration and the rain-path radar signal attenuation introduces significant systematic error on the R STD rainfall estimates. The study shows that adjusting the Z – R relationship for mean-field bias determined using the R KDP estimates as reference is the best technique for acquiring unbiased radar-rainfall estimates at fine space–time scales. Overall, the bias of the R KDP -adjusted Z – R estimator is shown to be lower than 10% for both storm cases, while the relative root-mean-square error is shown to range from 0.6 (convective storm) to 0.9 (stratiform storm). A vertical rainfall profile correction (VPR) technique is tested in this study for the stratiform storm case. The method is based on a newly developed VPR algorithm that uses the X-band polarimetric information to identify the properties of the melting layer and devices a precipitation profile that varies for each radar volume scan to correct the radar-rainfall estimates. Overall, when accounting for the VPR effect there is up to 70% reduction in the systematic error of the 3° elevation estimates, while the reduction in terms of relative root-mean-square error is limited to within 10%.