  It is increasingly acknowledged that cold pools can influence the initiation
of new convective cells. Yet, the full complexity of convective organization
through cold pool interaction is poorly understood. This lack of understanding
may partially be due to the intricacy of the dynamical pattern formed by
precipitation cells and their cold pools. Additionally, how exactly cold pools
interact is insufficiently known. To better understand this dynamics, we
develop a tracking algorithm for cold pool gust fronts. Rather than tracking
thermodynamic anomalies, which do not generally coincide with the gust front
boundaries, our approach tracks the dynamical cold pool outflow. Our algorithm
first determines the locus of the precipitation event. Second, relative to this
origin and for each azimuthal bin, the steepest gradient in the near-surface
horizontal radial velocity $v_r$ is employed to determine the respective locus
of the cold pool gust front edge. Steepest $v_r$-gradients imply largest
updraft velocities, hence strongest dynamical triggering. Results are compared
to a previous algorithm based on the steepest gradient in temperature ---
highlighting the benefit of the method described here in determining
dynamically active gust front regions. Applying the method to a range of
numerical experiments, the algorithm successfully tracks an ensemble of cold
pools. A linear relation emerges between the peak rain intensity of a given
event and maximal $v_r$ for its associated cold pool gust front --- a relation
found to be nearly independent of the specific sensitivity experiment.
