Towards an optimal polarimetric radar rainfall methodology: Demonstration during a water-logging disaster in eastern China

A water-logging disaster occurred in Eastern China on 1 June 2016 was utilized to investigate the practical performance of six radar rainfall estimators based on horizontal reflectivity ( $Z_{\mathrm{H}}$ ), specific attenuation ( $A_{\mathrm{H}}$ ), specific differential phase ( $K_{\text{DP}}$ ), and multi-variable estimators that integrate differential reflectivity ( $Z_{\text{DR}}$ ), namely $R(Z_{\mathrm{H}},\, Z_{\text{DR}}), R(K_{\text{DP}}, Z_{\text{DR}})$ and $R(A_{\mathrm{H}}, Z_{\text{DR}})$ . Detailed evaluation with a local rain gauge network and drop size distribution (DSD) measurements shows that (i) $R(A_{\mathrm{H}},\, Z_{\text{DR}})$ underestimates the light rain pattern, but it achieves the best scores and performs the best among the various estimators; (ii) each radar rainfall estimator can outperform other estimators at a certain period of time determined by the rainfall patterns; (iii) both the optimal radar rainfall relationship and high calibration accuracy are required to obtain accurate rainfall estimates; (iv) the contamination of melting solid hydrometeors on $A_{\mathrm{H}} \text{and}/\text{or}K_{\text{DP}}$ may make them less effective than $Z_{\mathrm{H}}$ . In addition, with appropriate adjustment of $\alpha$ coefficient, $R(A_{\mathrm{H}})$ can perform better than $R(K_{\text{DP}})$ .