Thursday, 6 November 2014
Capitol Ballroom AB (Madison Concourse Hotel)
Tornadic debris contains a diverse range of shapes, sizes, and orientations of meteorological and non-meteorological scatterers. When debris are lofted into the beam of a polarimetric radar, a tornadic debris signature (TDS) is usually identified by a decrease in co-polar cross correlation coefficient (ρHV
), a decrease in differential reflectivity (ZDR
) to around zero, and an increase in horizontal reflectivity (ZH
). An observation of a TDS can provide a warning forecaster with confirmation of a damaging tornado, especially in events where ground truth may not be available such as when the tornado is rain-wrapped or occurring at nighttime. Researchers at the National Severe Storms Laboratory are developing ways to automate the detection of these signatures for incorporation into the Hydrometeor Classification Algorithm or other standalone product, however, the development of thresholds for such an algorithm requires the assembly of a large dataset to determine the range of desirable thresholds for each base radar product.
This study describes the assembly of a geographic and climatologically diverse dataset of TDS detections spanning from 2010 through 2013. Comparison of a prototype automated detection system developed using thresholds from the research literature and human-identified detections through a sequence of TDS events will be discussed. Overall, the spatiotemporal attributes of a TDS can vary based on several factors affecting radar signal quality and should serve as a motivator to develop a dynamic identification framework instead of a single, all-purpose detection product.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner