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Polarimetric variables such as differential phase Φ_DPand its range derivative, specific differential phaseK_DP, contain useful information for improving quantitative precipitation estimation (QPE) and microphysics retrieval. However, the usefulness of the current operationally utilized estimation method ofK_DPis limited by measurement error and artifacts resulting from the differential backscattering phaseδ. The contribution ofδcan significantly influence the Φ_DPmeasurements and therefore negatively affect theK_DPestimates. Neglecting the presence ofδwithin non-Rayleigh scattering regimes has also led to the adoption of incorrect terminology regarding signatures seen within current operationalK_DPestimates implying associated regions of unrealistic liquid water content. A new processing method is proposed and developed to estimate bothK_DPandδusing classification and linear programming (LP) to reduce bias inK_DPestimates caused by theδcomponent. 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.

Recent operationally driven research has generated a framework, known as the three ingredients method and mesovortex warning system, that can help forecasters anticipate mesovortex development and issue warnings within quasi-linear convective systems (QLCSs). However, dual-polarization radar data has not yet been incorporated into this framework. Therefore, several dual- and single-polarization radar signatures associated with QLCS mesovortices were analyzed to determine if they could provide additional information about mesovortex development and intensity. An analysis of 167 mesovortices showed that 1)K_DPdrops precede ∼95% of mesovortices and provide an initial indication of where a mesovortex may develop; 2) midlevelK_DPcores are a potentially useful precursor signature because they precede a majority of mesovortices and have higher magnitudes for mesovortices that produce wind damage or tornadoes; 3) low-levelK_DPcores and areas of enhanced spectrum width have higher magnitudes for mesovortices that produce wind damage or tornadoes but tend to develop at about the same time as the mesovortex, which makes them more useful as diagnostic than as predictive signatures; and 4) as range from the radar increases, the radar signatures become less useful in anticipating mesovortex intensity but can still be used to anticipate mesovortex development or build confidence in mesovortex existence.