The objective of this paper is to examine the sensitivity of fuel moisture to changes in temperature and precipitation and explore the implications under a future climate. We use the Canadian Forest Fire Weather Index System components to represent the moisture content of fine surface fuels (Fine Fuel Moisture Code, FFMC), upper forest floor (duff) layers (Duff Moisture Code, DMC) and deep organic soils (Drought Code, DC). We obtained weather data from 12 stations across Canada for the fire season during the 1971-2000 period and with these data we created a set of modified weather streams from the original data by varying the daily temperatures by 0 to +5°C in increments of 1°C and the daily precipitation from −40 to 40 % in increments of 10 %. The fuel moistures were calculated for all the temperature and precipitation combinations. When temperature increases we find that for every degree of warming, precipitation has to increase by more than 15 % for FFMC, about 10 % for DMC and about 5 % for DC to compensate for the drying caused by warmer temperatures. Also, we find in terms of the number of days equal to or above an FFMC of 91, a critical value for fire spread, that no increase in precipitation amount alone could compensate for a temperature increase of 1°C. Results from three General Circulation Models (GCMs) and three emission scenarios suggest that this sensitivity to temperature increases will result in a future with drier fuels and a higher frequency of extreme fire weather days.

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In the face of climate change, predicting and understanding future fire regimes across Canada is a high priority for wildland fire research and management. Due in large part to the difficulties in obtaining future daily fire weather projections, one of the major challenges in predicting future fire activity is to estimate how much of the change in weather potential could translate into on-the-ground fire spread. As a result, past studies have used monthly, annual, or multi-decadal weather projections to predict future fires, thereby sacrificing information relevant to day-to-day fire spread. Using climate projections from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), historical weather observations, MODIS fire detection data, and the national fire database of Canada, this study investigated potential changes in the number of active burning days of wildfires by relating 'spread days' to patterns of daily fire-conducive weather. Results suggest that climate change over the next century may have significant impacts on fire spread days in almost all parts of Canada's forested landmass; the number of fire spread days could experience a 2-to-3-fold increase under a high CO 2 forcing scenario in eastern Canada, and a greater than 50% increase in western Canada, where the fire potential is already high. The change in future fire spread is critical in understanding fire regime changes, but is also imminently relevant to fire management operations and in fire risk mitigation.

A 3.6 ha experimental fire was conducted in a black spruce peatland forest that had undergone thinning the year prior. After 50 m of spread in a natural stand at 35–60 m min−1, the crown fire (43,000 kW m−1 intensity using Byram’s method) encountered the 50% stem removal treatment; spread rates in the treatment were 50–60 m min−1. Fuel consumption in the control (2.75 kg m−2) was comparable to the treatment (2.35 kg m−2). Proxy measurements of fire intensity using in-stand heat flux sensors as well as photogrammetric flame heights had detected intensity reductions to 30–40% of the control. Crown fuel load reductions (compensated by higher surface fuel load) appear to be the most significant contributor to the decline in intensity, despite drier surface fuels in the treatment. The burn depth of 5 cm in moss and organic soil did not differ between control and treatment. These observations point to the limited effectiveness (likely reductions in crown fire intensity but not spread rate) of stem removal in boreal black spruce fuel types with high stem density, low crown base height and high surface fuel load. The observed fire behaviour impacts differ from drier conifer forests across North America.

Abstract:Wildfires burn an average of 2 million hectares per year in Canada, most of which can be attributed to only a few days of severe fire weather. These "spread days" are often associated with large-scale weather systems. We used extreme threshold values of three Canadian Fire Weather Index System (CFWIS) variables -the fine fuel moisture code (FFMC), initial spread index (ISI), and fire weather index (FWI) -as a proxy for spread days. Then we used self-organizing maps (SOMs) to predict spread days, with sea-level pressure and 500 hPa geopotential height as predictors. SOMs require many input parameters, and we performed an experiment to optimize six key parameters. For each month of the fire season (May-August), we also tested whether SOMs performed better when trained with only one month or with neighbouring months as well. Good performance (AUC of 0.8) was achieved for FFMC and ISI, while nearly good performance was achieved for FWI. To our knowledge, this is the first study to develop a machine-learning model for extreme fire weather that could be deployed in real time.Key words: wildland fire, fire danger, fire regimes, SOM, weather.Résumé : Les feux, dont la plupart peuvent être imputés à seulement quelques jours durant lesquels les conditions météorologiques sont propices aux incendies forestiers sévères, détruisent en moyenne deux millions d'hectares de forêt par année au Canada. Ces jours propices à la propagation des feux sont souvent associés à de vastes systèmes météorologiques. Nous avons utilisé des valeurs seuils extrêmes pour trois variables de la méthode canadienne de l'indice forêt-météo (MCIFM) : l'indice du combustible léger (ICL), l'indice de propagation initiale (IPI) et l'indice forêt-météo (IFM) en tant que substituts pour les jours propices à la propagation des feux. Ensuite, nous avons utilisé des cartes autoorganisables (SOM) pour prédire les jours propices à la propagation des feux avec comme prédicteurs la pression au niveau de la mer et une hauteur du géopotentiel de 500 hPa. Les SOM exigent plusieurs paramètres d'entrée et nous avons effectué une expérience pour optimiser six paramètres clés. Pour chaque mois de la saison des feux (mai-août), nous avons aussi testé si les SOM étaient plus performantes lorsqu'elles étaient entraînées avec seulement un mois ou en incluant aussi les mois voisins. Une bonne performance (AUC de 0,8) a été obtenue pour ICL et IPI, alors qu'une performance satisfaisante a été obtenue pour IFM. À notre connaissance, il s'agit de la première étude qui élabore un modèle d'apprentissage automatique pour des conditions météorologiques extrêmes propices aux incendies forestiers qui peut être déployé en temps réel. [Traduit par la Rédaction] Mots-clés : feux de forêt, danger d'incendie, régime des feux, cartes autoorganisables (SOM), conditions météorologiques.

Current methods of predicting fire spread in Canadian forests are suited to large wildfires that spread through natural forests. Recently, the use of mechanical and thinning treatments of forests in the wildland-urban interface of Canada has increased. To assist in community wildfire protection planning in forests not covered by existing operational fire spread models, we use FIRETEC to simulate fire spread in lowland black spruce fuel structures, the most common tree stand in Canada. The simulated treatments included the mechanical mulching of strips, and larger, irregularly shaped areas. In all cases, the removal of fuel by mulch strips broke up the fuels, but also caused wind speed increases, so little decrease in fire spread rate was modelled. For large irregular clearings, the fire spread slowly through the mulched wood chips, and large decreases in fire spread and intensity were simulated. Furthermore, some treatments in the black spruce forest were found to be effective in decreasing the distance and/or density of firebrands. The simulations conducted can be used alongside experimental fires and documented wildfires to examine the effectiveness of differing fuel treatment options to alter multiple components of fire behavior.

Firebrand travel and ignition of spot fires is a major concern in the Wildland-Urban Interface and in wildfire operations overall. Firebrands allow for the efficient breaching across fuel-free barriers such as roads, rivers and constructed fuel breaks. Existing observation-based knowledge on medium-distance firebrand travel is often based on single tree experiments that do not replicate the intensity and convective updraft of a continuous crown fire. Recent advances in acoustic analysis, specifically pattern detection, has enabled the quantification of the rate at which firebrands are observed in the audio recordings of in-fire cameras housed within fire-proof steel boxes that have been deployed on experimental fires. The audio pattern being detected is the sound created by a flying firebrand hitting the steel box of the camera. This technique allows for the number of firebrands per second to be quantified and can be related to the fire's location at that same time interval (using a detailed rate of spread reconstruction) in order to determine the firebrand travel distance. A proof of concept is given for an experimental crown fire that shows the viability of this technique. When related to the fire's location, key areas of medium-distance spotting are observed that correspond to regions of peak fire intensity. Trends on the number of firebrands landing per square metre as the fire approaches are readily quantified using low-cost instrumentation.