Developing Tools for Nowcasting Storm Severity

Abstract

A conceptual model is presented for developing a new tool for nowcasting severe thunderstorms using existing operational data. Selected output from two operational, automated, weather detection and forecasting systems have been combined together within a fuzzy logic?based, data fusion system to test the concept and produce 15-min nowcasts of severe weather. The NCAR Auto-Nowcast System provides information and nowcasts on the evolving boundary layer and storm initiation, growth, and decay. The National Severe Storms Laboratory Warning Decision Support System (WDSS) identifies severe weather attributes within storms and provides storm-centric and specific detections of strong winds, mesocyclones, tornadoes, and probabilities of hail and severe hail. A modified version of the Auto-Nowcast System is employed as the engine for combining the Auto-Nowcast gridded output with the object-based WDSS output. Severe thunderstorm nowcasts are compared with available spotter reports for a multicellular, hail-producing squall-line event and a tornadic supercell event. Proof of concept is demonstrated and the results are encouraging as some skill is observed with the 15-min nowcasts. Many challenges still exist in producing a robust tool and these challenges are discussed.