The vortex detection and characterization (VDAC) technique is designed to identify tornadoes, mesocyclones, and other convective vortices in multiple-Doppler radar data and retrieve their size, strength, and translational velocity. The technique consists of fitting radial wind data from two or more radars to a simple analytical model of a vortex and its near environment. The model combines a uniform flow, linear shear flow, linear divergence flow (all of which comprise a broad-scale flow), and modified combined Rankine vortex. The vortex and its environmental flow are allowed to translate. A cost function accounting for the discrepancy between the model and observed radial winds is evaluated over space and time so that observations can be used at the actual times and locations they were acquired. The model parameters are determined by minimizing this cost function. Tests of the technique using analytically generated, numerically simulated, and one observed tornadic wind field were presented by Potvin et al. in an earlier study. In the present study, an improved version of the technique is applied to additional real radar observations of tornadoes and other substorm-scale vortices. The technique exhibits skill in detecting such vortices and characterizing their size and strength. Single-Doppler experiments suggest that the technique may reliably detect and characterize larger (>1-km diameter) vortices even in the absence of overlapping radar coverage.