Tuesday, 30 January 2024
Hall E (The Baltimore Convention Center)
Since the upgrade to the national network of WSR-88D radars, completed in 2013, several polarimetric radar signatures have been identified and observed in supercells. Investigation of these signatures has revealed that many are indicative of storm-scale processes ongoing within a supercell, some of which may be relevant to tornadogenesis, such as size sorting. Two signatures that result from size sorting are an enhanced area of differential reflectivity (ZDR) values located along the inflow edge of the forward flank and an enhanced area of specific differential phase (KDP) values found in the forward flank. Recently, the separation distance between these two signatures, in addition to the orientation of the vector connecting the two regions relative to storm motion (termed the ZDR-KDP separation vector), has been the subject of many studies and was found to be related to the storm-relative winds within a supercell. Two methodologies developed to quantitatively analyze the separation vector are the “dynamic thresholding” approach from Loeffler et al. (2020) and the Supercell Polarimetric Observation Research Kit (SPORK) from Wilson and Van Den Broeke (2022). While these methodologies are powerful tools for interrogating past cases, they are not properly suited in their current forms for use in real-time by forecasters. To that end, a novel algorithm known as “w2sepvec” was developed within the Multi-Radar Multi-Sensor (MRMS) and Warning Decision Support System - Integrated Information (WDSS-II) frameworks. Polarimetric radar data (e.g., ZDR, KDP, correlation coefficient) are combined with MRMS output (e.g., AzShear) and data from the 13km RAP to identify and track the ZDR-KDP separation vector. This study will present an overview of w2sepvec, in addition to key similarities and differences between w2sepvec, SPORK, and the dynamic thresholding approach from analyzing identical sets of tornadic and nontornadic supercells.

