Improving Estimation of Specific Differential Phase and Assessing Differential Backscattering Phase

Abstract

Abstract Polarimetric variables such as differential phase ΦDP and its range derivative, specific differential phase KDP, contain useful information for improving quantitative precipitation estimation (QPE) and microphysics retrieval. However, the usefulness of the current operationally utilized estimation method of KDP is limited by measurement error and artifacts resulting from the differential backscattering phase δ. The contribution of δ can significantly influence the ΦDP measurements and therefore negatively affect the KDP estimates. Neglecting the presence of δ within non-Rayleigh scattering regimes has also led to the adoption of incorrect terminology regarding signatures seen within current operational KDP estimates implying associated regions of unrealistic liquid water content. A new processing method is proposed and developed to estimate both KDP and δ using classification and linear programming (LP) to reduce bias in KDP estimates caused by the δ component. It is shown that by applying the LP technique specifically to the rain regions of Rayleigh scattering along a radial profile, accurate estimates of differential propagation phase, specific differential phase, and differential backscattering phase can be retrieved within regions of both Rayleigh and non-Rayleigh scattering. This new estimation method is applied to cases of reported hail and tornado debris, and the LP results are compared to the operationally utilized least squares fit (LSF) estimates. The results show the potential use of the differential backscattering phase signature in the detection of hail and tornado debris.