LAUSR

The recent dual-polarization upgrade to the National Weather Service radar network provides forecasters with new information to use during operations, yet currently this information is not routinely used to explicitly make warning decisions. One potential way to increase operational use is to link new radar signatures and products to existing forecaster conceptual models and the warning decision process. Over the past several years, a unique dataset consisting of rapid-update (<2-min volumes) radar data of storms over central Oklahoma has been collected to examine possible links between ZDR columns and forecaster conceptual models. In total, over 1400 volume scans from 42 storms—ranging from tornadic supercells to nonsevere multicells—are used to relate ZDR column depth to storm reports and radar signatures typically used to issue warnings, such as −20°C reflectivity core and low-level mesocyclone evolution. After completing the analysis, the following key operational findings emerged: 1) no clear differences exist between the ZDR column depth of tornadic and nontornadic mesocyclones, but statistically significant differences do exist between severe and nonsevere storms, 2) the lead time in advance of severe hail and wind reports provided by peaks in ZDR column depth is greater than that provided by peaks in −20°C reflectivity cores, 3) increases in ZDR column size precede increases in −20°C reflectivity core size by about 3.5–9.0 min, and 4) rapid-update volumetric data captures signature evolution several minutes earlier than conventional-update data therefore providing forecasters more time to anticipate hazards and issue warnings.