Prototype Tool Development for Creating Probabilistic Hazard Information for Severe Convective Phenomena

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Tuesday, 4 February 2014: 8:45 AM
Georgia Ballroom 2 (The Georgia World Congress Center )
Chris Karstens, CIMMS/Univ. of Oklahoma and NSSL/NOAA, Norman, OK; and T. M. Smith, K. M. Calhoun, A. J. Clark, C. Ling, G. J. Stumpf, and L. P. Rothfusz
Manuscript (1007.4 kB)

Advancements in technology and communications have introduced opportunity for forecasting and disseminating more detailed severe weather information. Forecasting a Continuum of Environmental Threats (FACETs) aims to modernize the binary watch/warning paradigm by delivering a rapidly-updating stream of probabilistic hazard information (PHI) optimized for effective, user-specific decision making in the proper societal contexts. A major component of FACETs is the creation of tools that allow forecasters to effectively bridge the gap between cutting-edge guidance sources [e.g., Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS), Storm-Scale Ensemble of Opportunity (SSEO), Warn-on-Forecast] and the end-user's continuum of diverse needs.

This presentation will discuss early development of next-generation, highly interactive prototype PHI creation tools, in addition to reviewing prior PHI tool development and testing conducted at the National Severe Storms Laboratory and Hazardous Weather Testbed. This development process is taking into consideration several factors, including forecaster workload, user-interface functionality, and public communication and response. The resulting prototype aims to test how forecasters can effectively convey uncertainties (i.e., time, space, motion, intensity) associated with multi-scale severe weather threats. As part of the presentation we will provide examples of the current prototype PHI tools under development as well as explore the underlying science necessary for forecasters to turn mesoscale and storm-scale statistical and numerical model output of severe convective phenomena into understandable and readily-applicable, grid-based hazardous weather information.