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Divergence Detection in Wind Fields Estimated by an Airport Surveillance Radar

Abstract : A technique is assessed for automatic detection of hazardous divergence in velocity fields estimated by an Airport Surveillance Radar (ASR). A least-squares approach was evaluated to radial divergence estimation through a performance analysis based on simulated data. This 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 the 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. (RH)