Testing the Future of Storm-Based Probabilistic Hazard Creation and Communication Across the Watch to Warning Paradigm

Storm-based Probabilistic Hazard Information (PHI) is designed to provide a meaningful quantification of hazard likelihood with additional spatial and temporal guidance relative to traditional weather watches and warnings. PHI can help fill gaps between the watch and warnings as well as provide information for storms that may not meet full warning criteria. When provided by National Weather Service forecasters, this additional information potentially allows decision makers and the general public to gain a much more comprehensive understanding of weather threats than that available from traditional binary weather warning polygons. Additionally, PHI can be layered with Threats-In-Motion (TIM) which moves the deterministic warning polygons using the storm motion, providing equitable lead time for downstream users. Thus, the system of PHI and TIM together can allow end-users to personalize the level of information and lead time necessary for the individual. Multiple experiments in the NOAA Hazardous Weather Testbed (HWT) have examined the creation of products and probabilistic communication within the watch-to-warning period by National Weather Service forecasters using both archive events as well as live data.

Several novel concepts were evaluated in these recent HWT experiments, from shorter-fused (up to two hours in length) adaptable watches through testing the feasibility of continuous forecaster generation of PHI and TIM simultaneously. Prototype cloud-based tools and platforms were used to create and distribute these products and algorithms across forecasters from different organizations. To ease forecaster workflow, multiple machine learning algorithms were used to provide a first guess of probabilities of tornadoes, hail, wind and lightning. Additionally, a new, relatively unobtrusive notification system was introduced to alert forecasters to actions which may require their attention, such as rapidly increasing hazard probabilities suggested by automated guidance or hazard information which has not been recently updated. Significant updates to the stability of automated guidance were integrated into the experiment, and their impact on forecaster workload was measured.

Finally, possible communications with partners using NWS chat via Slack as well as public facing social media were investigated, with exciting new communications templates arising from the experiment. Feedback gathered during the experiment has provided inspiration and direction for further development of storm-based probabilistic hazard research and communication, as well as guidance for which concepts might successfully progress towards operations. This presentation will focus on both results from the most recent experiments as well as discuss the potential impacts for future communication of the risk associated with individual severe storms hazards within the watch-to-warning period.