New & Improved 7-Day Wildland Fire Outlook

RMC is developing a system of statistical weather-based models for forecasting wildland fire potential & fire risk out to 7-10 days on a uniform national grid. The development of this gridded system of predictive equations has been planned to proceed in 4 phases with R&D tasks being executed under a Joint Venture Agreement with Colorado State University’s Cooperative Institute for Research in the Atmosphere (CIRA). Phase 1 began in October 2017 and was completed in February of 2019. It included the development and initial verification of a comprehensive system of logistic equations for predicting the probabilities of one-or-more and 10-or-more lightning flashes based on operational GFS model forecast fields produced by the National Centers for Environmental Protection (NCEP). Phase 2 focused on conducting a full verification of the lightning-forecast model for ConUS derived and assembling/formatting all necessary datasets for the development of regional equations to predict fire-ignition probabilities 7-10 days out on a 20-km national grid using the fire occurrence dataset developed by Dr. Karen Short, NCEP North American Regional Reanalysis (NARR) weather grids, gridded drought indices, and vegetation characteristics going back 27 years. Phase 3 completed the development of a set of monthly regional equations for forecasting the probabilities of wildland-fire ignition over ConUS and prepared an independent data set for model verification. Phase 4 to be completed by Sep. 20 2021 includes: verification of the monthly equations for forecasting of wildland-fire ignition probabilities over ConUS out to 7-10 days on a 20-km grid; developing a lightning-strike probability model for Alaska; and developing a web page to prototype/demonstrate the fire-ignition probability forecast model in an operational environment.

Developing a national 20-km grid-resolution model for forecasting probabilities of fire ignition as a function of current & future (up to 10 days) weather, past drought conditions and vegetation/fuel characteristics. These forecasts are intended for National Predictive Services and Fire Management.

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