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Author(s): Abatzoglou, John T; Hatchett, Benjamin J; Fox-Hughes, Paul; Gershunov, Alexander; Nauslar, Nicholas J

A global increase in megafires has occurred since the mid-1990s. Defined as wildfires that burn more than 405 km2 (100 000 ac), megafires are complex phenomena with wide ranging societal impacts. In the United States, scientific literature and wildland fire policy has traditionally focused upon megafires in forests of the American West. However, megafires also pose a significant threat to life and property on the southern Great Plains. The southern Great Plains is characterized by grass-dominated prairie and is climatologically prone to dry and windy weather, which facilitates extreme rates of fire spread leading to some of the largest wildfires in North America. This study documents 16 megafires on the plains of New Mexico, Texas, Oklahoma, and Kansas between 2006 and 2018. Most of these megafires occurred during southern Great Plains wildfire outbreaks, or plains firestorms, characterized by fire-effective low-level thermal ridges. Fuel and weather conditions supporting the 2006–2018 plains megafires are quantified by antecedent precipitation anomalies, fuel moisture, Energy Release Component, relative humidity, sustained wind speed, and temperature percentiles. Three modes of plains megafire evolution are identified by the analyses as short-duration, long-duration, and hybrid. Abrupt wind shifts and carryover fire in heavy dead fuels dictate megafire potential and evolutionary type. The presented analyses define favorable fuel and weather conditions that allow forecasters to discriminate megafire environments from typical plains fire episodes. Further, predictive signals for plains megafire conceptual model types can improve anticipation of southern Great Plains megafire evolution, threats, and management strategies.

Spot weather forecasts (SWFs) are issued by Weather Service offices throughout the United States and are primarily for use by wildfire and prescribed fire practitioners for monitoring local-scale weather conditions. This paper focuses on use of SWFs by prescribed fire practitioners. Based on qualitative, in-depth interviews with fire practitioners and National Weather Service forecasters, this paper examines factors that influence perceptions of accuracy and utilization of SWFs. Results indicate that, while several well-understood climatological, topographical, and data-driven factors influence forecast accuracy, social factors likely have the greater impact on perceptions of accuracy, quantitative accuracy, and utilization. These include challenges with building and maintaining relationships between forecasters and fire managers, communication issues around updating SWFs, and communicating forecast confidence and uncertainty. Operationally, improved quantitative skill in a forecast is always desirable, but key opportunities for improving accuracy and utilization of these forecasts lie in 1) enhancing the processes and mechanisms for communication between a Weather Forecast Office and fire practitioners—before, during, and after an SWFs is issued—and 2) working with the wildland fire community to experiment with forecast uncertainty and confidence information in SWFs and evaluate impacts of these approaches.

Fire management officials request spot forecasts from National Weather Service (NWS) Weather Forecast Offices to provide detailed guidance regarding atmospheric conditions in the vicinity of prescribed and wildland fires. Verifying spot forecasts represents an integral component of the forecast process and helps assess and improve the accuracy of forecasts. The verification analysis here utilizes NWS spot forecasts of mixing height, transport winds, and the Haines index (HI) from 2009–2013 issued for a location within 50 km of an upper-air sounding site and valid for the day of the fire event. Mixing height was calculated from the 0000 UTC sounding via the Stull, Holzworth, and Richardson methods. Transport wind speeds were determined by averaging the wind speed through the boundary layer as determined by the three mixing height methods from the 0000 UTC sounding. The HI was calculated at low, mid, and high elevation based on the elevation of the sounding and spot-forecast locations. Forecast statistics, including mean error and mean absolute error, were calculated for each lower-atmospheric variable by region. Mixing height forecasts exhibited large mean absolute errors and were biased toward overforecasting. Forecasts of transport wind speeds and HI outperformed mixing height forecasts with smaller errors relative to their respective means. Based on these results and the methodology, recommendations are provided to improve spot forecasts and the verification process.

Santa Ana winds (SAW) are among the most notorious fire-weather conditions in the United States and are implicated in wildfire and wind hazards in Southern California. This study employs large-scale reanalysis data to diagnose SAW through synoptic-scale dynamic and thermodynamic factors using mean sea level pressure gradient and lower-tropospheric temperature advection, respectively. A two-parameter threshold model of these factors exhibits skill in identifying surface-based characteristics of SAW featuring strong offshore winds and extreme fire weather as viewed through the Fosberg fire weather index across Remote Automated Weather Stations in southwestern California. These results suggest that a strong northeastward gradient in mean sea level pressure aligned with strong cold-air advection in the lower troposphere provide a simple, yet effective, means of diagnosing SAW from synoptic-scale reanalysis. This objective method may be useful for medium- to extended-range forecasting when mesoscale model output may not be available, as well as being readily applied retrospectively to better understand connections between SAW and wildfires in Southern California.