Assessing the Usefulness of the National Fire Danger Rating System Data for Issuing Red Flag Warnings

Wildfires pose significant threats to public safety and property, necessitating accurate fire danger assessment and timely warnings. The National Weather Service (NWS) issues Red Flag Warnings (RFW) to warn of elevated wildfire risks with varying criteria nationwide. Most include thresholds of relative humidity (RH) and wind gusts, with the only connection to fuel conditions limited to land manager input and non-automated processes. However, changing technology allows additional inputs such as the National Fire Danger Rating System (NFDRS) to provide underlying fuels information that can aid land manager, forecaster, and first responder decisions. The Kansas Mesonet, a network of 80+ weather stations, collects hourly weather data that is incorporated into the United States Forest Service Weather Information System (WIMS) to calculate NFDRS variables. Additionally, the NWS provides forecast information into WIMS for each weather station out seven days. This study investigates the performance of the Kansas Mesonet's NFDRS fire weather forecasts of Burning Index (BI, a short duration parameter most dependent on wind and RH) and Energy Release Component (ERC, a long term parameter that better categorizes drought). Results indicate that while the Kansas Mesonet's NWS point forecasts of BI and ERC correlated well with their forecasts, the peak fire risk was often underpredicted. NWS NFDRS forecasts predicted for hour 1300 each day, meaning they did not predict peak burning conditions which typically occur between 1400-1800 depending on the season. Additionally, BI predictions were more challenging due to short term weather variability resutling in statistical less accuracy than ERC. Correlation coefficients were lowest at day seven (~0.6 for BI and ~0.8 for ERC) and gradually improved by each subsquent forecast with highest accuracy on day one. This study also compared four years of observed Kansas Mesonet weather and BI/ERC data throughout the entire dataset, during RFWs, and during large fire days (LFDs). Additionally, this study also evaluated the Red Flag Threat Index (RTFI), which ranks observed wind/RH against historical percentiles compared to NDFRS ratings. RFWs and LFDs consistently exhibit elevated wind gusts, BI, ERC, and reduced RH most conducive to Kansas fire spread. Notably, observations during RFWs exhibited more extreme conditions than LFDs, likely because wildfire ignitions are not limited to peak burning conditions and/or RFW issuance. As a result, only 55% of LFDs were warned with RFWs, revealing some opportunity for RFW improvement based upon fuels conditions. While maximum ratings during each LFD reached “High” or greater more often for RTFI (+15.2% of all LFD days), all ratings during LFDs reached “High” or greater more often for NFDRS (+34.9%). This shows BI and ERC’s usefulness as stable values given that they have less daily variation than winds and can be more representative of drought and other long term conditions. This study suggests that automated BI and ERC forecasts like the Kansas Mesonet’s can be used to incorporate fuel conditions in RFW criteria. It also shows that other fire environment tools such as RFTI are useful, but the fuel component is still a necessity to capture extreme wildfire potential. By refining fire danger assessment and warning systems, communities can better prepare for and mitigate the impacts of wildfires.