Preliminary Use of Convection-allowing Models in Fire Weather

Abstract

Multiple high-impact wildfire episodes on the southern Great Plains in 2021/22 provided unique opportunities to demonstrate the emerging utility of Convection-allowing Models (CAMs) in fire-weather forecasting. This short contribution article will present preliminary analyses of the deterministic Texas Tech Real Time Weather Prediction System’s Red Flag Threat Index (RFTI) compared to wildfire activity observed via the Geostationary Operational Environmental Satellite-16 during four southern Great Plains wildfire outbreaks. Visual side-by-side comparisons of model-predicted RFTI and satellite-detected wildfires will be shown in static and animated displays that demonstrate the model’s prognostic signal in depicting fire-outbreak evolution. The data analyses are supplemented with preliminary information from state forestry agencies that provide context to predicted RFTI relative to size-based categorization of observed wildfires and human casualties. In addition, use of the National Severe Storm Laboratory’s Warn-on-Forecast System to provide short-term updates on the evolution of fire-effective atmospheric features that promote new fire ignition, problematic spread, and extreme fire behavior is also demonstrated. The examples presented here suggest that CAMs serve an important role in the mesoscale prediction of dangerous wildfire conditions. With this novel use of CAMs in fire meteorology, the authors advocate for expanded availability of fire weather-specific fields and parameters in high-resolution numerical weather prediction systems that would improve wildfire forecasts and associated impact-based decision support.