An Object-Based Algorithm for the Identification and Tracking of Convective Outflow Boundaries

Convective outflow boundaries such as density currents and bores could play an important role in the dynamics of mesoscale convective systems (MCSs). Up to this end, their identification has relied primarily on the analysis of surface observations and composite radar displays. Although previous studies have proposed various methods for defining density currents in gridded model data sets, these methods cannot be easily extended to describe atmospheric bores. To address the aforementioned research gap, this study discusses the development of an object-based algorithm for the identification and tracking of convective outflow boundaries. A novel aspect of the algorithm is its ability to provide a unified description of both density currents and bores, achieved by a careful application of several image processing techniques. To ensure the robustness of objects’ tracking, the algorithm employs filters based on both statistical and dynamical considerations.

The following presentation is divided into two main parts. The first one discusses the technical details pertaining to the identification and tracking steps of the algorithm. The second part shows how the algorithm’s capabilities could be utilized for an objective verification of bore forecasts as well as a general framework for studying the evolution of nocturnal convective outflow boundaries. The study concludes with a relevant discussion on some of the challenges faced by the operational implementation of the algorithm and possible suggestions for its future improvement.