15B.1 The 2016 Hazard Services – Probabilistic Hazard Information (HS-PHI) Experiment at the NOAA Hazardous Weather Testbed

Thursday, 10 November 2016: 1:30 PM
Pavilion Ballroom West (Hilton Portland )
Gregory J. Stumpf, CIMMS/Univ. of Oklahoma and NOAA/NWS Meteorological Development Laboratory, Norman, OK; and T. L. Hansen, J. G. LaDue, C. Ling, K. L. Manross, A. V. Bates, D. M. Kingfield, T. C. Meyer, C. Golden, and N. Hardin

Forecasting a Continuum of Environmental Threats (FACETs) is a proposed next-generation severe weather watch and warning framework that is modern, flexible, and designed to communicate clear and simple hazardous weather information to serve the public.  One of the underlying aspects of FACETs is rapidly-updating probabilistic hazard grids, known as Probabilistic Hazard Information (PHI).  PHI can be used to provide custom user-specific products that can be tailored to adapt to a variety of needs – for example, providing longer lead times, at lower confidence, for more vulnerable populations with a lower tolerance for risk.

The National Severe Storms Laboratory has developed a prototype PHI tool which allows forecasters to integrate probabilistic guidance and their own interpretations of the atmosphere to issue PHI for severe convective hazards - hail, wind, and tornadoes.  This prototype tool was tested in the NOAA Hazardous Weather Testbed (HWT) in the springs of 2014, 2015, and 2016.  Information collected by meteorologists and human factors experts is being used to improve the prototype PHI tool, so that its capabilities can be integrated into National Weather Service (NWS) operations.

That technology transfer to operations includes adapting an experimental version of the NWS Advanced Weather Information Processing System (AWIPS) Hazard Services (HS) software to include the capabilities for forecasters to provide PHI at the 0-2 hour “warning” scale.  For 3 weeks in May and June of 2016, two forecasters per week used Hazard Services – PHI (HS-PHI) in a variety of real-time and displaced real-time scenarios.  Meteorologists, software developers, and human factors experts collected data on the effectiveness of the software and the concepts of PHI for NWS warning operations. What was learned from this experiment will be used to further refine HS-PHI over the next two years, after which it could eventually be integrated into NWS operations.

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