学术文献库

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.