Association between NSSL Mesocyclone Detection Algorithm-Detected Vortices and Tornadoes

Abstract

Nearly 100 000 vortex detections produced by the Mesocyclone Detection Algorithm (MDA) are analyzed to gain insight into the effectiveness of the detection algorithm in identifying various types of tornado-producing events. Radar and algorithm limitations prevent raw vortex detections from being very useful without further discrimination. Filtering techniques are developed to remove spurious vortex detections and discriminate between vortices that are and are not related to mesocyclones. To investigate whether various vortex detections (and their attributes) are associated with severe weather phenomena, they are compared with available tornado reports to determine if detections with certain types of attributes can be associated with tornadic events. Tornado reports are used since the ground truth tornado set is more reliable than other databases of severe weather phenomena. Basic skill scores and more advanced principal component methods are used to quantify the correlation between vortex detection attributes and tornadoes. The results of this analysis reveal that only a very small percentage (<5%) of vortex detections, using the most basic definition, are associated with the occurrence of a tornado. Percentages increase to approximately 10% as the criteria for defining a vortex detection as a mesocyclone detection become more strict; however, many tornadic events are only associated with weaker detections and are ?missed? when the detection threshold is increased. Several velocity-derived detection attributes are shown to have weak to moderate predictive ability when determining whether a detection is (or is not) tornadic.