Search

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.

En las regiones mediterráneas, el efecto combinado del éxodo rural, la falta de gestión forestal y las políticas de supresión de incendios han contribuido notablemente en el aumento de la carga y continuidad de los combustibles forestales sobre extensas áreas. El resultado es una creciente incidencia de incendios forestales que supera la capacidad de extinción. Debido a una limitada disponibilidad de recursos económicos para la gestión del paisaje, resulta necesario priorizar la protección de los bienes con una expectativa de pérdida elevada y el tratamiento del combustible en puntos estratégicos para contener los incendios que impactan en núcleos urbanos. Este estudio se desarrolla en el Valle de Juslapeña (Navarra, España) para demostrar la priorización de actuaciones en la gestión de combustibles. En el área de estudio, los frecuentes y grandes incendios forestales han causado notables daños en el patrimonio forestal y los bienes de las comunidades rurales. Primero, se generó la cartografía de riesgo de incendios para los bienes de elevado valor, a continuación, se diseñó el mosaico óptimo de tratamientos dentro de la cuenca de exposición en base a la exposición de las masas arboladas y la transmisión a viviendas residenciales. A su vez, se identificaron los rodales capitalizados en existencias donde las extracciones podrían abastecer las necesidades de la población local o costear parcialmente el coste de los tratamientos. Según se observa, las mayores pérdidas se obtuvieron en las viviendas localizadas al sur del área de estudio debido a su elevada probabilidad de quema. Los incendios iniciados fuera del área de estudio también afectaron a las viviendas residenciales y, por tanto, la extensión de los planes de gestión de incendios debe ser ajustada considerando el origen y la escala del riesgo en los núcleos urbanos. La metodología que se presenta en este estudio puede ser adaptada a la gestión multifuncional de cualquier otra región mediterránea con un elevado riesgo de incendios. In Mediterranean areas, the combined effects of the rural exodus, lack of forest management, and fire suppression policies have substantially contributed to increased forest fuel loadings and continuity over large areas. The result is a growing incidence of wildfires that exceed fire suppression capacity. Economic resources for landscape management are limited, and thus they must be prioritized towards the protection of valued assets where there is a high expectation of loss and the fuel treatments on strategic locations that restrict fires spreading into communities. We completed a case study in the Juslapeña Valley (Navarra, Spain) to demonstrate prioritization of fuel management activities. The study area has frequent and large forest fires that have caused significant damage to forest values and assets in rural communities. We first generated a wildfire risk map for valued assets, and then designed the optimal treatment mosaic within the community fireshed considering the wildfire exposure to forestlands and fire transmission to residential housing. We also identified overstocked stands where the timber or firewood production might supply the needs of local communities and partially cover the treatment cost. We found that the highest economic losses were obtained in residential houses located in the southern portion of the study area, mainly due to a higher burn probability. Fires ignited outside of the study area also exposed communities, and thus the extent considered in wildfire management plans needs to be adjusted to reflect the source and scale of risk to communities. The assessment framework presented in this study can be adapted to the multi-functional forest management in any fire-prone Mediterranean region elsewhere.

Red Flag Warnings (RFWs) issued by the National Weather Service in the United States (U.S.) are an important early warning system for fire potential based on forecasts of critical fire weather that promote increased fire activity, including the occurrence of large fires. However, verification of RFWs as they relate to fire activity is lacking, thereby limiting means to improve forecasts as well as increase value for end users. We evaluated the efficacy of RFWs as forecasts of large fire occurrence for the Northwestern U.S.&mdash, RFWs were shown to have widespread significant skill and yielded an overall 124% relative improvement in forecasting large fire occurrences than a reference forecast. We further demonstrate that the skill of RFWs is significantly higher for lightning-ignited large fires than for human-ignited fires and for forecasts issued during periods of high fuel dryness than those issued in the absence of high fuel dryness. The results of this first verification study of RFWs related to actualized fire activity lay the groundwork for future efforts towards improving the relevance and usefulness of RFWs and other fire early warning systems to better serve the fire community and public.

Downslope Sundowner winds in southern California's Santa Ynez Mountains favor wildfire growth. To explore differences between Sundowners and Santa Ana winds (SAWs), we use surface observations from 1979 to 2014 to develop a climatology of extreme Sundowner days. The climatology was compared to an existing SAW index from 1979 to 2012. Sundowner (SAW) occurrence peaks in late spring (winter). SAWs demonstrate amplified 500 hPa geopotential heights over western North America and anomalous positive inland mean sea-level pressures. Sundowner-only conditions display zonal 500 hPa flow and negative inland sea-level pressure anomalies. A low-level northerly coastal jet is present during Sundowners but not SAWs.

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.

Two extreme wind-driven wildfire events impacted California in late 2017, leading to 46 fatalities and thousands of structures lost. This study characterizes the meteorological and climatological factors that drove and enabled these wildfire events and quantifies their rarity over the observational record. Both events featured key fire-weather metrics that were unprecedented in the observational record that followed a sequence of climatic conditions that enhanced fine fuel abundance and fuel availability. The North Bay fires of October 2017 occurred coincident with strong downslope winds, with a majority of burned area occurring within the first 12 hours of ignition. By contrast, the southern California fires of December 2017 occurred during the longest Santa Ana wind event on record, resulting in the largest wildfire in California&rsquo, s modern history. Both fire events occurred following an exceptionally wet winter that was preceded by a severe four-year drought. Fuels were further preconditioned by the warmest summer and autumn on record in northern and southern California, respectively. Finally, delayed onset of autumn precipitation allowed for critically low dead fuel moistures leading up to the wind events. Fire weather conditions were well forecast several days prior to the fire. However, the rarity of fire-weather conditions that occurred near populated regions, along with other societal factors such as limited evacuation protocols and limited wildfire preparedness in communities outside of the traditional wildland urban interface were key contributors to the widespread wildfire impacts.

Strong afternoon downslope Sundowner winds in southern California's Santa Ynez Mountains favor wildfire growth. To determine whether Sundowners are different from Santa Ana winds (SAW), we use surface observations from 1979–2014 to develop a climatology of extreme Sundowner days. The climatology was compared against an existing SAW index from 1979–2012. Sundowner occurrence peaks in late spring whereas SAWs peak during winter. SAWs demonstrate amplified 500 hPa geopotential heights over western North America and strong anomalously positive inland mean sea level pressures. In contrast, Sundowner-only conditions occur during zonal 500 hPa flow and moderate negative inland sea level pressure anomalies.

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.

We implemented a fire risk assessment framework that combines spatially-explicit burn probabilities, post-fire mortality models and public auction timber prices, to estimate expected economic losses from wildfires in 155 black pine stands covering about 450 ha in the Juslapena Valley of central Navarra, northern Spain. A logit fire occurrence model was generated from observed historic fires to provide required fire ignition input data. Wildfire likelihood and intensity were estimated by modeling 50,000 fires with the minimum travel time algorithm (MTT) at 30 m resolution under 97th percentile fire weather conditions. Post-fire tree mortality due to burning fire intensity at different successional stages ranged from 0.67% in the latest stages to 9.22% in the earliest. Stands showed a wide range of potential economic losses, and intermediate successional stage stands presented the highest values, with about 124 € ha− 1 on average. A fire risk map of the target areas was provided for forest management and risk mitigation purposes at the individual stand level. The approach proposed in this work has a wide potential for decision support, policy making and risk mitigation in southern European commercial conifer forests where large wildfires are the main natural hazard.