The vision of Warn-on-Forecast is to enable extended lead time for individual local severe weather hazards through design of new storm-scale probabilistic tools. Namely, the Warn-on-Forecast System (WoFS) employs rapid data assimilation, rapid forecast updates, and visualization of output at 5-minute resolution to provide movie-like probabilistic forecasts of individual storms on the 0-6 hour, “watch-to-warning” scale. Operating a relocatable, 900-km squared regional domain since 2017, the experimental 3-km WoFS has been shown to improve forecasts in testbed environments and to influence real-world decision-making and public threat communication at NWS national and local offices. WoFS migrated to the Microsoft Azure cloud in 2022, unlocking the capability to run multiple domains and/or larger domains. The NSSL double moment microphysics scheme designed in the WoF group is now available in the UFS, and WoFS is slated for an operational transition to the NWS, as part of the UFS, by late decade. Developing tools and processes within the UFS to support 5-15 minute data assimilation cycles, 30-minute relaunch cadence, and low-latency generation of unique ensemble visualizations will pave the way for future applications on a multitude of small-scale analysis and forecast problems.
Patrick Burke worked as a National Weather Service forecaster, including 5 years as a Lead Forecaster at the Weather Prediction Center. In 2020, he brought his operational experience to the Warn-on-Forecast (WoF) research group at the National Severe Storms Laboratory; Patrick is the WoF Program Lead. He holds an MS in meteorology from the University of Oklahoma. Growing up in the severe weather culture of Oklahoma he has always been motivated to help people stay safe during severe storm and flash flood events. In his spare time, Patrick enjoys running and writing music.
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