Probabilistic Weather Forecast Data for Fire Decision Makers

Probabilistic Weather Forecast Data for Fire Decision Makers

NWS Missoula has experimented with methods for distributing probabilistic forecast information from the National Blend of Models (NBM). These are text-based and intended to compliment “spot” weather forecasts for prescribed fires, wildland fire suppression and other incidents. Efforts so far have concentrated on probabilistic forecast information for Wind Speed, Rainfall Amount and Lightning Risk. Questions remain about how to proceed, such as which level of fire weather community (Fire fighter vs. managers and decision makers) would benefit from this information? What dissemination methods is appropriate and how much training needs to be developed and provided for these new products?

The NBM provides a statistical gridded probability of lightning ground strikes for various forecast lead times. The lightning forecasts have been verified for summer 2020, utilizing the groundbased lightning detection network for lightning occurrence data. The prediction system and verification results will be discussed.

Chris Gibson is the Science and operations Officer for the National Weather Service in Missoula. His local NWS role is to develop and track forecaster training and attempt research-to-operations efforts in office programs, such as Winter Road Weather and Fire Weather and encourage use of modern forecast techniques.

Ryan Leach is a Senior Meteorologist at NWS Missoula and an active Incident Meteorologist since 2014. Ryan manages the local grid forecast management program and is a contributor to national forecasting technique development.