A Red Flag Threat Index Based on the Real-Time Mesoscale Analysis for Use in the Warn-on-Forecast System

Abstract The increasing frequency of high-impact wildfires has led to an emphasis on improving forecasts of the conditions that are favorable for wildfire initiation and rapid spread. The key atmospheric forecast products currently used are derived from low-level humidity and wind speed. One product that has seen widespread use by the National Weather Service (NWS) in the southern plains is known as the red flag threat index (RFTI). RFTI represents an index ranging from 0 to 10 where larger values indicate a more critical threat for favorable wildfire conditions. The current RFTI is based on 2-m humidity and 6-m wind speed climatologies from surface measurement sites located within a NWS forecast area resulting in a product that differs somewhat from office to office. RFTI forecasts are also only available from existing numerical weather prediction systems such as the Texas Tech modeling system that do not output forecasts with the temporal resolution and latency to forecast rapidly evolving environmental conditions. To address these limitations, this work describes the creation of a grid-based RFTI using a 5-yr, high-resolution (3-km, hourly) reanalysis product known as the Real-Time Mesoscale Analysis (RTMA). Using RTMA data allows for continuous wind and humidity climatology fields to be developed for a larger W-CONUS domain, potentially expanding the use of RFTI. We combine these new climatologies with forecast output from the Warn-on-Forecast System (WoFS) which provides short-term (0–6 h) probabilistic forecasts of high-impact weather over a regional domain. RFTI forecasts from examples occurring in 2022 and 2024 will be discussed as well as its evaluation in the new Fire Weather Testbed.