Evaluation of Probabilistic Hazard Information (PHI) in Weather Forecast Offices: Initial Results of a Collaborative NSSL/NWS Research Effort

Under development for several years as a component of the Forecasting a Continuum of Environmental Threats (FACETs) program at the National Severe Storms Laboratory (NSSL), Probabilistic Hazard Information (PHI) aims to provide continuously updating spatiotemporal guidance at the warning time-scale regarding the potential for severe storm threats. Improvements to PHI in recent years have advanced the technology to be capable of providing stable, automated hazard probabilities that are informed by machine learning algorithms for tornado (Tornado Probability Algorithm (TORP)), severe (ProbSevere), and lightning (ProbLightning) threats. As of 2023, the NWS and NSSL have come together in a collaborative effort to evaluate the utility of PHI by distributing research data feeds to several Southern and Eastern Region Weather Forecast Offices (WFOs).

This presentation will cover feedback received thus far in the collaborative evaluation and corresponding data feed changes and improvements, as well as observed use cases of the automated PHI plumes within WFO operations and warnings. Also covered will be implementation details of the collaborative effort, including methodology for the creation and provision of research data feeds and challenges that were overcome. The current status of the collaborative research will be discussed, and future tools and improvements that are envisioned to assist in the continued evaluation of PHI will be outlined.