Improvements on Cluster Identification and Tracking in a New Circulation Detection Algorithm

Circulation detection algorithms such as the Mesocyclone Detection Algorithm (MDA) and the Tornado Detection Algorithm (TDA) have been used by National Weather Service forecasters to aid with warning decision-making since the mid-1990s. However, the MDA and TDA are often plagued with misidentified circulations and poor tracking which limit their use as an operational tool. Because of ever-increasing data flow rates from radar upgrades (e.g. WSR-88D “super-resolution”), new technologies (e.g. Phased Array Radar), and the need to quickly analyze circulation signatures in the immense historical WSR-88D data set, NSSL is developing an improved algorithm to identify, diagnose, and track both mesocyclone and tornado size circulations. The algorithm operates on a field of “azimuthal shear”, which is the rotational derivative of the Doppler radial velocity field. “Clusters” of high azimuthal shear values in both low level (0-3 km above the surface) and mid level (3-7 km above the surface) layers of the storm are identified in the radar data. The clustering and tracking methods were developed on relatively smooth reflectivity fields, but are now being applied to a much noisier azimuthal shear field. This project compares multiple methods of cluster identification and tracking to determine which is best.