Search

Fire activity in 288 areas (2.5° N × 10° E) in the Arctic region (50°–70° N, 0°–360° E) was analyzed using about 4.4 million satellite hotspot (HS) data from 2002 to 2021. A total of 21 high fire density areas from eastern Europe to western Canada were selected, and their fire–weather conditions during each active fire period were analyzed using about 1820 various weather maps at the upper and the lower air level. Analysis results showed that the active fires in the Arctic region occurred under the fire–weather conditions associated with the northward movement of cut-off high (COH) and warm air masses detached from the south caused by large westerly meandering (LWM). LWM is a sign of the beginning of an active fire period. Very active fires on HS peak days occurred several days after the start of the northward movement of COHs and under mainly high-pressure conditions in the upper air and strong wind conditions in the lower air. The time lag of these several days suggests that we may be prepared for very active fires. The fire–weather analysis approach described in this paper has shown that future large-scale fire outbreaks are predictable. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An important aspect of predicting future wildland fire risk is estimating fire weather—weather conducive to the ignition and propagation of fire—under realistic climate change scenarios. Because the majority of area burned occurs on a few days of extreme fire weather, this task should be able to resolve fire weather extremes. In this paper, we present a statistical downscaling procedure based on distribution based scaling (DBS) to bias correct the Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System, as calculated from modeled climate data. Our study area is western Canada (British Columbia and Alberta) and we consider both an historical control period (1990–2000) and three future time periods (2020–2030, 2050–2060, and 2080–2090). The historical data used to calibrate the DBS procedure comprises weather station data and weather from the North American Regional Reanalysis (NARR), whereas the future climate projections are the output of three regional climate models, corresponding to different model parameterizations and downscaled from the NCAR Community Earth System Model under the RCP 8.5 scenario. By fitting a truncated Weibull distribution to observed and modeled FWI values, our method is able to reproduce historical extremes in fire weather indices as determined by the distribution of annual potential spread days, which are defined as days with FWI values greater than 19. Moreover, by calibrating the DBS procedure with gridded reanalysis data as well as station observations, we are able to project future spread day distributions over the entire study area. The results of this study show the DBS procedure leads to a greater number of projected annual spread days at most locations compared with estimates using the uncorrected model output, and that all three RCM models show positive increases in potential annual spread days for the 2050–2060 and 2080–2090 time periods. [ABSTRACT FROM AUTHOR]

Background. Crown fires are an ecologically necessary but hazardous process in conifer forests. Prediction of their behaviour in Canada has largely depended on the Canadian Forest Fire Behaviour Prediction System, in which fire weather indices drive primarily fixed fuel type models. The Crown Fire Initiation and Spread (CFIS) system presents a more flexible approach to predicting crown fire occurrence than fixed fuel type models. Aims. Using a multi-decadal database of experimental fires carried out in conifer plots (1960–2019, n = 113), our aim was to develop updated models based on the CFIS system approach, fitting crown fire occurrence models to fire environment variables using logistic regression. Methods. We tested alternative fuel moisture estimates and compared various model forms using repeated cross-validation. In two-storeyed stands, crown fire occurrence was defined as the involvement of lower canopy stratum fuels. Key results. Final models based on wind speed, fuel strata gap, litter moisture and surface fuel consumption predicted crowning events correctly in up to 92% of cases in training data (89% in cross-validation). Conclusions and implications. These new models offer improved accuracy and flexibility that will help users assess how competing environmental factors interact under different fuel treatments and wildfire scenarios. [ABSTRACT FROM AUTHOR]

Modifications to the environment around a weather station or changes in instrument result in discontinuities or shift in weather data. This paper asks the often ignored questions such as, “what are the impacts of inhomogenized data?” and “does using homogenized weather data affect the conclusions of environmental research?” To answer these questions, we used the Canadian Forest Fire Weather Index (CFFWI) System for our studies. Weather station data are used to calculate wildfire danger indices. The homogenized data and raw (inhomogenized) observations for sixteen weather stations spread across Canada were used to calculate the CFFWI indices. The sixteen weather stations were further divided into three subset of stations based on the length of the accessible data during the fire season (April to end of September). The first set included stations that covered just 27 years of data and the second data sets had 49 years of data, while the third set included only five stations with the longest time period of 66 years. The majority of the stations, as measured by the Wilcoxon signed-rank test, rejected the null hypothesis (difference between the pairs follows a symmetric distribution around zero). The rejection rate increases to 100% as the length of data record increases from 27 to 66 years. Homogenization of 66 years data reduced the indices values approximately 0.7–8.4% and also reversed the long-term trend in some stations such as Kapuskasing. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fire is the dominant disturbance agent in Alaskan and Canadian boreal ecosystems and releases large amounts of carbon into the atmosphere. Burned area and carbon emissions have been increasing with climate change, which have the potential to alter the carbon balance and shift the region from a historic sink to a source. It is therefore critically important to track the spatiotemporal changes in burned area and fire carbon emissions over time. Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m (meters) resolution that utilizes finer-scale 30 m Landsat imagery to account for land cover unsuitable for burning. This method strictly balances omission and commission errors at 500 m to derive accurate landscape- and regional-scale burned-area estimates. Using this new burned-area product, we developed statistical models to predict burn depth and carbon combustion for the same period within the NASA Arctic–Boreal Vulnerability Experiment (ABoVE) core and extended domain. Statistical models were constrained using a database of field observations across the domain and were related to a variety of response variables including remotely sensed indicators of fire severity, fire weather indices, local climate, soils, and topographic indicators. The burn depth and aboveground combustion models performed best, with poorer performance for belowground combustion. We estimate 2.37×106 ha (2.37 Mha) burned annually between 2001–2019 over the ABoVE domain (2.87 Mha across all of Alaska and Canada), emitting 79.3 ± 27.96 Tg (±1 standard deviation) of carbon (C) per year, with a mean combustion rate of 3.13 ± 1.17 kg C m -2. Mean combustion and burn depth displayed a general gradient of higher severity in the northwestern portion of the domain to lower severity in the south and east. We also found larger-fire years and later-season burning were generally associated with greater mean combustion. Our estimates are generally consistent with previous efforts to quantify burned area, fire carbon emissions, and their drivers in regions within boreal North America; however, we generally estimate higher burned area and carbon emissions due to our use of Landsat imagery, greater availability of field observations, and improvements in modeling. The burned area and combustion datasets described here (the ABoVE Fire Emissions Database, or ABoVE-FED) can be used for local- to continental-scale applications of boreal fire science. [ABSTRACT FROM AUTHOR]

Copyright of Ecoscience (Ecoscience) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents an operational approach to predicting fire growth for wildland fires in Canada. The approach addresses data assimilation to provide predictions in a timely and efficient manner. Fuels and elevation grids, forecast weather, and active fire locations are entered into a fire-growth model; then predicted fire perimeters are mapped and presented on the web. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA/AVHRR) satellite-based detection systems are used to detect current wildiand fires (referred to as hotspots). For selected regions, fire-growth simulation environments are assembled. Fuel type data from several fire management agencies are available in grid format at a resolution of lOOm or less; in areas where such data are not available, a national fuels map based on Satellite Pour l'Observation de Ia Terre Vegetation sensor (SPOT VGT) land cover and forest inventory is used. Similarly, terrain data are available from a variety of sources. Current hotspots are used as ignition points while past hotspots are used to delineate area burned. Surface wind, temperature, and dew-point values (forecast by Environment Canada) are used to determine the fire weather conditions at the fire location. A ease study of two large fires in Canada consisting of 54 fire simulation days is used to test these hypotheses. [ABSTRACT FROM AUTHOR]

The present paper reviews the development of the Canadian Forest Fire Danger Rating System (CFFDRS) and its implementation in Canada and elsewhere, and suggests how this experience can be applied in developing fire danger rating systems in other forest or wildland environments. Experience with the CFFDRS suggests that four key scientific, technological, and human elements need to be developed and integrated in a national forest fire danger rating system. First among these is a sustained program of scientific research to develop a system based on relationships between fire weather, fuels, and topography, and fire occurrence, behavior, and impact appropriate to the fire environment. Development of a reliable technical infrastructure to gather, process, and archive fire weather data and to disseminate fire weather forecasts, fire danger information, and fire behavior predictions within operational agencies is also important. Technology transfer and training in the use of fire danger information in fire operations are necessary, as are cooperation and communication between fire management agencies to share resources and set common standards for information, resources, and training. These elements must be appropriate to the needs and capabilities of fire managers, and must evolve as fire management objectives change. Fire danger systems are a form of media; system developers should be careful not to overemphasize scientific and technological elements at the expense of human and institutional factors. Effective fire danger systems are readily assimilated by and influence the organizational culture, which in turn influences the development of new technologies. Most importantly, common vision and a sense of common cause among fire scientists and fire managers are needed for successful implementation of a fire danger rating system. [ABSTRACT FROM AUTHOR]

We present a global high-resolution calculation of the Canadian Fire Weather Index (FWI) System indices using surface meteorology from the ERA5 HRES reanalysis for 1979–2018. ERA5 HRES represents an improved dataset compared to several other reanalyses in terms of accuracy, as well as spatial and temporal coverage. The FWI calculation is performed using two different procedures for setting the start-up value of the Drought Code (DC) at the beginning of the fire season. The first procedure, which accounts for the effects of inter-seasonal drought, overwinters the DC by adjusting the fall DC value with a fraction of accumulated overwinter precipitation. The second procedure sets the DC to its default start-up value (i.e. 15) at the start of each fire season. We validate the FWI values over Canada using station observations from Environment and Climate Change Canada and find generally good agreement (mean Spearman correlation of 0.77). We also show that significant differences in early season DC and FWI values can occur when the FWI System calculation is started using the overwintered versus default DC values, as is highlighted by an example from 2016 over North America. The FWI System moisture codes and fire behaviour indices are made available for both versions of the calculation at 10.5281/zenodo.3626193 (McElhinny et al., 2020), although we recommend using codes and indices calculated with the overwintered DC, unless specific research requirements dictate otherwise. [ABSTRACT FROM AUTHOR]

We compared three monthly adaptations of the daily Drought Code (DC) of Canada's Fire Weather Index System and applied them to interpret drought conditions associated with historical fires in montane forests of south-eastern British Columbia. The three adaptations were compared with the monthly mean DC calculated from daily values for the Palliser fire-weather station. Two adaptations improved on the existing Monthly DC calculated from monthly climate data by (1) accounting for overwinter drying and an early start to the fire season, and (2) improving estimates of effective precipitation. Using a cross-dated fire-scar record from 20 sites in montane forests surrounding the Palliser station, we found significant fire–drought associations from June to August with all adaptations, and significant associations in April and May with the two new adaptations. Of the 17 fire years from 1901 to 2013, 6 years had low initial drought conditions that increased late in the fire season, and 5 years had high drought conditions throughout the fire season. We conclude that variable drought within and among fire seasons influenced fire severity. Our findings provide a connection between modern drought indices used to rank fire danger and drought effects on the historical mixed-severity fire regime in montane forests of south-eastern British Columbia. Accuracy of monthly drought codes increased after accounting for overwinter drying, early fire season starts, and effective precipitation. April–August drought codes were significantly associated with historical fires. Variations in fire-season drought influenced fire severity, connecting modern fire-weather indices with historical mixed-severity fire regimes in montane forests of south-eastern British Columbia. [ABSTRACT FROM AUTHOR]

Meteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, Alberta, Canada. The basin is a 9.4 km 2 , alpine–montane forest headwater catchment of the Saskatchewan River basin that provides vital water supplies to the Prairie Provinces of Canada. It was heavily instrumented, experimented upon, and operated by several federal government agencies between 1962 and 1986, during which time its main and sub-basin streams were gauged, automated meteorological stations at multiple elevations were installed, groundwater observation wells were dug and automated, and frequent manual measurements of snow accumulation and ablation and other weather and water variables were made. Over this period, mature evergreen forests were harvested in two sub-basins, leaving large clear cuts in one basin and a "honeycomb" of small forest clearings in another basin. Whilst meteorological measurements and sub-basin streamflow discharge weirs in the basin were removed in the late 1980s, the federal government maintained the outlet streamflow discharge measurements and a nearby high-elevation meteorological station, and the Alberta provincial government maintained observation wells and a nearby fire weather station. Marmot Creek Research Basin was intensively re-instrumented with 12 automated meteorological stations, four sub-basin hydrometric sites, and seven snow survey transects starting in 2004 by the University of Saskatchewan Centre for Hydrology. The observations provide detailed information on meteorology, precipitation, soil moisture, snowpack, streamflow, and groundwater during the historical period from 1962 to 1987 and the modern period from 2005 to the present time. These data are ideal for monitoring climate change, developing hydrological process understanding, evaluating process algorithms and hydrological, cryospheric, or atmospheric models, and examining the response of basin hydrological cycling to changes in climate, extreme weather, and land cover through hydrological modelling and statistical analyses. The data presented are publicly available from Federated Research Data Repository (10.20383/101.09, Fang et al., 2018). [ABSTRACT FROM AUTHOR]

Canada is expected to see an increase in fire risk under future climate projections. Large fires, such as that near Fort McMurray, Alberta in 2016, can be devastating to the communities affected. Understanding the role of human emissions in the occurrence of such extreme fire events can lend insight into how these events might change in the future. An event attribution framework is used to quantify the influence of anthropogenic forcings on extreme fire risk in the current climate of a western Canada region. Fourteen metrics from the Canadian Forest Fire Danger Rating System are used to define the extreme fire seasons. For the majority of these metrics and during the current decade, the combined effect of anthropogenic and natural forcing is estimated to have made extreme fire risk events in the region 1.5 to 6 times as likely compared to a climate that would have been with natural forcings alone. [ABSTRACT FROM AUTHOR]

Predictive models of fire frequency conditional on weather and land cover are essential to assess how future cover-type distributions and weather conditions may influence fire regimes. We modelled the effects of bottom-up variables (e.g. land cover) and top-down variables (e.g. fire weather) simultaneously with data aggregated or interpolated to spatial and temporal units of 100 km2 and 1 yr in the boreal forest of Québec, Canada. For models of human-caused fires, we used road density as a surrogate for human access and behaviour. We exploited the additive property of Poisson distributions to estimate cover-type specific fire count rates, which would normally not be possible with data of this spatial resolution. We used piecewise linear functions to model nonlinear relations between fire weather and fire frequency for each cover-type simultaneously. The estimated conditional rates may be considered as expected mean counts per unit area and time. It follows that these rates can be rescaled to arbitrary spatial and temporal extents. Our results showed fire frequency increased nonlinearly as aridity increased and more quickly in disturbed areas than other types. Road density exerted the strongest influence on the frequency of human-caused fires, which were positively correlated with road density. The estimates may be used to parameterize the fire ignition component of spatial simulation models, which often have a resolution different from that at which the data were collected. This is an essential step in incorporating biotic and abiotic feedbacks, land-cover dynamics, and climate projections into ecological forecasting. The insight into the power of Poisson additivity to reveal high-resolution ecological processes from low-resolution data could have applications in other areas of ecology. [ABSTRACT FROM AUTHOR]

Results from studies of climate model scenarios suggest that forest fire ignitions will increase in Canada in the future because of climate change. Yet, there have been few studies that monitor long-term trends in Canadian historical fire records. Although there are seasonal trends to historically reported fires within a fire season, there are also periods of zero-heavy behaviour as well as periods during which more fires are reported than usual. We develop a flexible mixture-modelling framework that permits the joint assessment of temporal trends in these dominant characteristics in terms of fire risk, defined as the daily probability that one or more fires are reported. The statistical power of such trend tests are also evaluated. We identify statistically significant increases in lightning-caused fire risk between 1963 and 2009 in the boreal forest regions of the Rainy River and Lake of the Woods ecoregions in Northwestern Ontario, Canada. These observed changes in lightning-caused fire risk were found to be associated with temperature and fire danger rating index anomalies. If such trends continue into the future, the duration of elevated periods of lightning-caused forest fire risk is forecasted to increase by over 50% by the middle of this century. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Year-to-year variation in fire activity in Canada constitutes a key challenge for fire management agencies. Interagency sharing of fire management resources has been ongoing on regional, national and international scales in Canada for several decades to better cope with peaks in resource demand. Inherent stressors on these schemes determined by the fire regimes in constituent jurisdictions are not well known, nor described by averages. We developed a statistical framework to examine the likelihood of regional synchrony of peaks in fire activity at a timescale of 1 week. Year-to-year variations in important fire regime variables and 48 regions in Canada are quantified by a joint distribution and profiled at the Provincial or Territorial level. The fire regime variables capture the timing of the fire season, the average number of fires, area burned, and the timing and extent of annual maxima. The onset of the fire season was strongly correlated with latitude and longitude. Regional synchrony in the timing of the maximum burned area within fire seasons delineates opportunities for and limitations to sharing of fire suppression resources during periods of stress that were quantified in Monte Carlo simulations from the joint distribution. Spatial and temporal variation in seven fire regime variables are described for Canada's managed forests. Opportunities for sharing forest fire suppression resources are explored with simulations of fire regimes and quantifying the degree of temporal and spatial synchrony in peak fire-activities. [ABSTRACT FROM AUTHOR]

The Fire Weather Index module of the Canadian Forest Fire Danger Rating System (CFFDRS) was evaluated during two consecutive fire seasons in the Mediterranean environment of Crete, Greece. The Duff Moisture Code (DMC), the Drought Code (DC), the Buildup Index (BUI) and the Fire Weather Index (FWI) were highly correlated to fire occurrence but only moderately to area burned. Logistic regression was applied in order to classify the FWI values into fire danger classes appropriate for the Mediterranean environments, as follows: 0-38 Low, 39-48 Moderate, 49-59 High, > 60 Extreme. The new classification was necessary because the existing Canadian fire danger classes were found inapt for the dry and extremely fire prone eastern Mediterranean climate of Crete. After the modification, the fluctuation of the FWI values predicted more successfully the days of high fire risk, as proved by the actual fire occurrence. High correlation was found between measured litter (L layer) moisture values and those predicted by the Fine Fuel Moisture Code (FFMC). The use of an equilibrium duff moisture content value lower than 20% in Mediterranean environments, would probably improve the Duff Moisture Code (DMC) predictions. The Drought Code (DC) was poorly correlated to the upper soil moisture content. Overall, the FWI demonstrated several aptitudes related to its potential use as a meteorological fire danger rating index in Mediterranean regions. However, long-term studies are necessary to determine the precise range of each fire danger class according to fire occurrence data. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The Fire Weather Index System has been in use across Canada for the past 30 years in the daily operations of fire management agencies. As part of this system, the Drought Code (DC) was developed to act as a daily index of water stored in the soil. A major obstacle to the completion of climate risk analyses on the DC is that lengthy series of daily temperature and precipitation are not available for large portions of the circumboreal forest. Here the authors present a methodological modification to the daily DC to allow its approximation using monthly data. This new Monthly Drought Code (MDC) still retains its ability to capture moisture trends in deep organic layers. On the basis of high-resolution temperature and precipitation data, an analysis of summer moisture availability across Canada over 1901–2002 is presented. The driest periods on record were from the 1920s to the early 1960s, with the driest years being 1955, 1958, and 1961. The wettest period was from the mid-1960s to the 1980s. For the century-long period, drying was statistically significant in northern Canada. Locations south of the Hudson Bay, in the eastern Maritimes, and in western Canada recorded a trend toward decreasing dryness. When analyzed over 1951–2002, trends could hardly be distinguished from the (multi) decadal variability. Annual values of a spatial average of all July MDC grid cells showed an excellent fit against fire statistics: 63% of the variance in the Canada-wide annual area burned from 1959 to 1999 was explained by summer moisture availability. [ABSTRACT FROM AUTHOR]

Forecasting future fire activity as a function of climate change is a step towards understanding the future state of the western mixedwood boreal ecosystem. We developed five annual weather indices based on the Daily Severity Rating (DSR) of the Canadian Forest Fire Weather Index System and estimated their relationship with annual, empirical counts of lightning fire initiation for 588 landscapes in the mixedwood boreal forest in central-eastern Alberta, Canada from data collected between 1983 and 2001 using zero-inflated negative binomial regression models. Two indices contributed to a parsimonious model of initiation; these were Seasonal Severity Rating (SSR), and DSR-sequence count. We used parameter estimates from this model to predict lightning fire initiation under weather conditions predicted in 1 × CO2 (1975–1985), 2 × CO2 (2040–2049) and 3 × CO2 (2080–2089) conditions simulated by the Canadian Regional Climate Model (CRCM). We combined predicted initiation rates for these conditions with existing empirical estimates of the number of fire initiations that grow to be large fires (fire escapes) and the fire size distribution for the region, to predict the annual area burned by lightning-caused fires in each of the three climate conditions. We illustrated a 1.5-fold and 1.8-fold increase of lightning fire initiation by 2040–2049 and 2080–2089 relative to 1975–1985 conditions due to changes in fire weather predicted by the CRCM; these increases were calculated independent of changes in lightning activity. Our simulations suggested that weather-mediated increases in initiation frequency could correspond to a substantial increase in future area burned with 1.9-fold and 2.6-fold increases in area burned in 2040–2049 and 2080–2089 relative to 1975–1985 conditions, respectively. We did not include any biotic effects in these estimates, though future patterns of initiation and fire growth will be regulated not only by weather, but also by vegetation and fire management. [ABSTRACT FROM AUTHOR]

Abstract Historical relationships between weather, the Canadian fire weather index (FWI) system components and area burned in Canadian ecozones were analysed on a monthly basis in tandem with output from the Canadian and the Hadley Centre GCMs to project future area burned. Temperature and fuel moisture were the variables best related to historical monthly area burned with 36–64% of the variance explained depending on ecozone. Our results suggest significant increases in future area burned although there are large regional variations in fire activity. This was especially true for the Canadian GCM where some ecozones show little change in area burned, however area burned was not projected to decrease in any of the ecozones modelled. On average, area burned in Canada is projected to increase by 74–118% by the end of this century in a 3 × CO2 scenario. These estimates do not explicitly take into account any changes in vegetation, ignitions, fire season length, and human activity (fire management and land use activities) that may influence area burned. However, the estimated increases in area burned would have significant ecological, economic and social impacts for Canada. [ABSTRACT FROM AUTHOR]