Using Z(Dr) Columns In Forecaster Conceptual Models And Warning Decision-Making

Research has shown that dual-polarization (dual-pol) data currently available to National Weather Service forecasters could provide important information about changes in a storm's structure and intensity. Despite these new data being used gradually by forecasters more over time, they are still not used extensively to inform warning decisions because it is unclear how to apply dual-pol radar data to specific warning decisions. To address this knowledge gap, rapid-update (i.e., volumetric update time of 2.3 min or less) radar data of 45 storms in Oklahoma are used to examine one dual-pol signature, known as the differential reflectivity (Z(DR)) column, to relate this signature to warning decisions. Base data (i.e., Z(DR), reflectivity, velocity) are used to relate Z(DR) columns to storm intensity, radar signatures such as upper-level reflectivity cores, and scientific conceptual models used by forecasters during the warning decision process. Analysis shows that 1) differences exist between the Z(DR) columns of severe and nonsevere storms, 2) Z(DR) columns develop and evolve prior to upper-level reflectivity cores, 3) rapid-update radar data provide a more complete picture of Z(DR) column evolution than traditional-update radar data (i.e., volumetric update time of about 5 min), and 4) Z(DR) columns provide a clearer and earlier indication of changes in updraft strength compared to reflectivity signatures. These findings suggest that Z(DR) columns can be used to inform warning decisions, increase warning confidence, and potentially increase warning lead time especially when they are integrated into existing conceptual models about a storm's updraft and intensity.