This report assesses a technique for automatic detection of hazardous divergence in velocity fields estimated by an Airport Surveillance Radar (SAR). We evaluate a least-squares approach to radial divergence estimation through a performance analysis based on simulated data. That approach is compared to an existing decision-based radial shear finding method used for the Terminal Doppler Weather Radar (TDWR). Empirical results derived by the application of two techniques to data collected at ASR testbeds in Huntsville, Alabama and in Kansas City, Missouri are presented. Results indicate that a simple, least-squares divergence estimator combined with time association logic to increase temporal continuity of algorithm output is an equally effective means of detecting divergent wind shear in velocity fields estimated from ASR signals.