8.5 Evaluating the ProbSevere Model at NWS Eastern and Central Region Weather Forecast Offices

Wednesday, 25 January 2017: 11:30 AM
620 (Washington State Convention Center )
Chad M. Gravelle, National Weather Service Operations Proving Ground, Kansas City, MO; and J. P. Craven and D. B. Radell

The ProbSevere Model, developed by NOAA's National Environmental Satellite, Data, and Information Service Center for Satellite Applications and Research and the University of Wisconsin’s Cooperative Institute for Meteorological Satellite Studies, uses Numerical Weather Prediction, geostationary satellite cloud growth rates, total lightning flash rate, and Multi-Radar/Multi-Sensor data to provide probabilistic guidance on the likelihood a thunderstorm will produce severe weather in the next 60 minutes. During 2014, 2015, and 2016, ProbSevere was evaluated during spring experiments at the Hazardous Weather Testbed’s Experimental Warning Program. The majority of participants at these evaluations discussed how the model heightened their situational awareness by highlighting which storms were most threatening. Some also mentioned that ProbSevere had an influence on their warning decisions. The successful evaluations at the Hazardous Weather Testbed led to the development of a larger ProbSevere Model evaluation at National Weather Service (NWS) Eastern and Central Region Weather Forecast Offices (WFO). Organized by the Operations Proving Ground, between 1 April and 1 October 2016, forecasters at fifty-two NWS WFOs evaluated ProbSevere for its usefulness in convective warning decision making. The goals of this evaluation were to gain additional insight on the strengths and weaknesses of ProbSevere, to determine how NWS forecasters were using the probabilistic output for warning decision making, and to expose NWS forecasters to a Probabilistic Hazard Information warning decision making paradigm. This presentation will highlight feedback from the evaluation and provide examples that illustrate how ProbSevere was used by NWS forecasters during warning operations.
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