Potential Benefits of Assimilating Phased Array Radar Data for Convective‐Scale Analysis and Prediction of Supercell Storms: A Proof‐of‐Concept OSSE Study

Abstract This study investigates the impact of phased array radar (PAR) scanning strategies on short‐term convective‐scale analyses and forecasts through an Observing System Simulation Experiment framework. The Weather Research and Forecasting model, coupled with the Data Assimilation Research Testbed ensemble adjustment Kalman filter, is used to assimilate synthetic radar observations from PAR and WSR‐88D scanning strategies across three idealized supercell cases: slow‐moving, fast‐moving, and fast‐moving/fast‐growing storms. For the slow‐moving storm, PAR and WSR‐88D experiments produce comparable analyses and forecasts, with only marginal improvement from PAR. In contrast, for fast‐moving and fast‐growing storms, the 5‐min WSR‐88D scan introduces substantial temporal errors associated with storm advection and evolution, resulting in distorted storm structure. The rapid 1‐min update capability of PAR significantly reduces these errors, producing superior analyses and forecasts. These findings suggest that the implementation of a future US national PAR network would substantially enhance the accuracy of short‐term severe weather forecasts.