Quantitative Error Analysis on Polarimetric Phased Array Radar Weather Measurements to Reveal Radar Performance and Configuration Potential

Abstract. The initial weather measurements from two polarimetric phased array radars (PPAR) with cylindrical and planar configurations, both developed by the Advanced Radar Research Center (ARRC) at the University of Oklahoma (OU), were compared with those from the dish-antenna systems, the operational KTLX Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Oklahoma City, Oklahoma (~23 km northeast of OU). Both the cylindrical PPAR (CPPAR) and the planar PPAR (PPPAR) in Horus are S-band two-dimensional (2D) electronic scan PPAR. This comparison investigates the error statistics of the polarimetric measurements in one-dimensional (1D) electronic scan from each radar during two convective rain events. The first event occurred on 30 August 2019, when the CPPAR performed a 3.3° elevation plan-position indicator (PPI) scan at 25 azimuth angles. The second event took place on 4 October 2023, when Horus conducted range-height indicator (RHI) scans at 64 elevations. For both events, KTLX provided volumetric polarimetric radar data and served as the reference. To ensure temporal and spatial alignment between the radars, reconstructed RHI scans and PPI sectors from KTLX were matched to the corresponding Horus rays and CPPAR domain, respectively. The standard deviations and mean biases of the PPAR weather measurements were calculated and analyzed. The standard deviations of the two PPARs were similar and met the Radar Functional Requirements set by the National Oceanic and Atmospheric Administration/National Weather Service. However, as noted in previous studies, the standard deviation, and biases of polarimetric variables from Horus exhibited varying error characteristics depending on the electronic steering angle from broadside. The present results suggest that PPPARs may have difficulties in producing high-quality polarimetric data at large steering angles and further investigation on both CPPAR and 2D PPPAR is required to find the optimal design for future weather applications.