Update on Model-Generated Predictions of Dry Thunderstorm Risk
Miriam Rorig, USDA Forest Service, Seattle, WA
Every year dry thunderstorms cause numerous wildfires throughout the western U.S. and Alaska. We have previously developed an algorithm to determine the risk of dry thunderstorms, and applied this methodology using output variables from the Penn State/NCAR mesoscale model (MM5) to produce a predictive scheme for estimating the risk of “dry” lightning. We are currently updating and improving this algorithm by incorporating additional data to include other geographic areas, incorporating predictions of large lightning outbreaks, and migrating to other domains and meteorological models with broader coverage than the Pacific Northwest MM5 domain. The latest results from these efforts will be presented.
Session 10, Operational Forecasting (Short to Long Term) of Fire Weather for Wild, Prescribed, and Fire Use Fires
Thursday, 15 October 2009, 10:30 AM-12:00 PM, Ballroom B
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