Time since prior wildfire affects subsequent fire containment in black spruce

2017 ◽  
Vol 26 (11) ◽  
pp. 919 ◽  
Author(s):  
Jennifer L. Beverly
Keyword(s):  
Black Spruce ◽  
Structural Characteristics ◽  
Weather Conditions ◽  
Fire Spread ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Explanatory Variables ◽  
Time Since Fire ◽  
Crown Fires

In black spruce forests characterised by high-intensity crown fires, early detection and containment of fires while they are small is crucial for averting progression to fire intensities that exceed suppression capabilities. Fire behaviour conditions encountered during initial attack operations are a key determinant of containment success. Conditions will be controlled in part by stand structural characteristics that can be expected to vary as a fire-origin black spruce (Picea mariana (Mill.) B.S.P.) stand ages with increasing time-since-fire. In this study, the influence of time-since-fire on containment outcomes is assessed to explore whether or not prior wildfire exerts a negative feedback on subsequent fires in these ecosystems. Logistic regression analysis using point and polygon fire data for the province of Alberta, Canada, indicated the probability of a containment failure in black spruce increases with time-elapsed since the last fire. Other positive explanatory variables included the size of the fire at the initiation of firefighting and a relative rating of the expected rate of fire spread, the Initial Spread Index (ISI) of the Canadian Forest Fire Weather Index System. Legacy wildfires had a protective effect. When firefighting is initiated at fire sizes ≤1ha, the probability of a containment failure is low during the initial 20–45 years of post-fire stand development, except under the most extreme fire weather conditions.

Fire weather index system components for large fires in the Canadian boreal forest

2004 ◽  
Vol 13 (4) ◽  
pp. 391 ◽  
Author(s):  
B. D. Amiro ◽  
K. A. Logan ◽  
B. M. Wotton ◽  
M. D. Flannigan ◽  
J. B. Todd ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Fire Season ◽  
Fire Weather ◽  
Fuel Moisture ◽  
Weather Index ◽  
Fire Weather Index ◽  
System Parameters ◽  
System Components ◽  
Large Fires ◽  
Canadian Boreal Forest

Canadian Fire Weather Index (FWI) System components and head fire intensities were calculated for fires greater than 2 km2 in size for the boreal and taiga ecozones of Canada from 1959 to 1999. The highest noon-hour values were analysed that occurred during the first 21 days of each of 9333 fires. Depending on ecozone, the means of the FWI System parameters ranged from: fine fuel moisture code (FFMC), 90 to 92 (82 to 96 for individual fires); duff moisture code (DMC), 38 to 78 (10 to 140 for individual fires); drought code (DC), 210 to 372 (50 to 600 for individual fires); and fire weather index, 20 to 33 (5 to 60 for individual fires). Fine fuel moisture code decreased, DMC had a mid-season peak, and DC increased through the fire season. Mean head fire intensities ranged from 10 to 28 MW m−1 in the boreal spruce fuel type, showing that most large fires exhibit crown fire behaviour. Intensities of individual fires can exceed 60 MW m−1. Most FWI System parameters did not show trends over the 41-year period because of large inter-annual variability. A changing climate is expected to create future weather conditions more conducive to fire throughout much of Canada but clear changes have not yet occurred.

Evaluation of ERS SAR data for prediction of fire danger in a Boreal region

1999 ◽  
Vol 9 (3) ◽  
pp. 183 ◽  
Author(s):  
Laura L. Bourgeau-Chavez ◽  
Eric S. Kasischke ◽  
Mark D. Rutherford
Keyword(s):  
Boreal Forests ◽  
Black Spruce ◽  
Fire Danger ◽  
Fire Weather ◽  
Multilinear Regression ◽  
Weather Index ◽  
Fire Weather Index ◽  
Sar Data ◽  
Forest Fire Danger ◽  
In Fire

Research was conducted to determine the utility of Synthetic Aperture Radar (SAR) data for measuring the fuel moisture status of boreal forests as reflected in Fire Weather Index Codes. Three years (May to August 1992–1995) of SAR data from the European Remote Sensing Satellite (ERS) were analysed over the 1990 Tok Alaska burned and adjacent unburned black spruce forests. Corresponding Fire Weather Index Codes of the Canadian Forest Fire Danger Rating System were obtained from Tok Area Forestry, Station number 500720. Strong relationships were expected between the SAR data and fire codes because of the dependence of ERS SAR backscatter on the moisture status of forests and exposed surfaces (burn scars). Astepwise multilinear regression procedure was used to analyse the relationships. Three statistically significant multilinear regression models resulted from this analysis procedure. The models developed show there is potential for using ERS SAR backscatter to generate indicators that are related to Fire Weather Index, Duff Moisture Code, and Drought Code. This research could lead to the ability for remote prediction of fire danger over large regions at relatively fine spatial resolution with minimal weather information.

What are the drivers of dangerous fires in Mediterranean France?

2018 ◽  
Vol 27 (3) ◽  
pp. 155 ◽  
Author(s):  
S. Lahaye ◽  
T. Curt ◽  
T. Fréjaville ◽  
J. Sharples ◽  
L. Paradis ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Quantile Regression Model ◽  
Mediterranean Europe ◽  
Main Driver ◽  
Large Fires ◽  
Strong Winds ◽  
Mediterranean France

Wildfire containment is often very challenging for firefighters, especially for large and rapidly spreading fires where the risk of firefighter entrapment is high. However, the conditions leading to these ‘dangerous’ fires are poorly understood in Mediterranean Europe. Here, we analyse reports and interviews of firefighters over the last 40 years in four regions of south-eastern France and investigate the weather conditions that induce large fires, fast-growing fires and fires that are conducive to entrapment. We adopt a quantile regression model to test the effect of weather conditions across different fire sizes and growth rates. The results show that strong winds drive the largest fires everywhere except in Corsica, the southernmost region, where high temperature is the main driver. Strong winds also drive entrapments whereas high temperatures induce rapidly spreading fires. This emphasises that wind-driven fire is the dominant pattern of dangerous fires in France, but it reveals that large ‘convective’ fires can also present considerable danger. Beyond that, the Fire Weather Index appears to be a good predictor of large fires and fires conducive to entrapments. Identifying weather conditions that drive ‘dangerous’ wildfires will provide useful information for fire agencies to better prepare for adverse fire behaviours.

Environmental determinants of lightning- v. human-induced forest fire ignitions differ in a temperate mountain region of Switzerland

2010 ◽  
Vol 19 (5) ◽  
pp. 541 ◽  
Author(s):  
Björn Reineking ◽  
Patrick Weibel ◽  
Marco Conedera ◽  
Harald Bugmann
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Weather Conditions ◽  
Forest Composition ◽  
Small Range ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Independent Variables ◽  
Fire Ignitions

Understanding the environmental and human determinants of forest fire ignitions is crucial for landscape management. In this study, we consider lightning- and human-induced fires separately and evaluate the relative importance of weather, forest composition and human activities on the occurrence of forest fire ignitions in the most fire-prone region of Switzerland, the Canton Ticino. Independent variables included 14 drought and fire weather indices, forest composition and human influences. Logistic regression models were used to relate these independent variables to records of forest fires over a 37-year period (1969–2005). We found large differences in the importance of environmental and human controls on forest fire ignitions between lightning- and human-induced events: lightning-induced fires occurred in a small range of weather conditions well captured by the Duff Moisture Code from the Canadian Forest Fire Weather Index System and the LandClim Drought Index, and with negligible influence of distance to human infrastructure, whereas human-induced fires occurred in a wider range of weather conditions well captured by the Angstroem and the Fosberg Fire Weather Index, mainly in deciduous forests, and strongly depending on proximity to human infrastructure. We conclude that the suitability of fire indices can vary dramatically between ignition sources, suggesting that some of these indices are useful within certain regions and fire types only. The ignition source is an important factor that needs to be taken into account by fire managers and when developing models of forest fire occurrence.

scholarly journals The Hot-Dry-Windy Index: A New Fire Weather Index

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 279 ◽  
Author(s):  
Alan Srock ◽  
Joseph Charney ◽  
Brian Potter ◽  
Scott Goodrick
Keyword(s):  
Multiple Scales ◽  
Wildland Fire ◽  
Meteorological Data ◽  
Fire Behavior ◽  
Weather Conditions ◽  
Meteorological Variables ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Complex Interactions

Fire weather indices are commonly used by fire weather forecasters to predict when weather conditions will make a wildland fire difficult to manage. Complex interactions at multiple scales between fire, fuels, topography, and weather make these predictions extremely difficult. We define a new fire weather index called the Hot-Dry-Windy Index (HDW). HDW uses the basic science of how the atmosphere can affect a fire to define the meteorological variables that can be predicted at synoptic-and meso-alpha-scales that govern the potential for the atmosphere to affect a fire. The new index is formulated to account for meteorological conditions both at the Earth’s surface and in a 500-m layer just above the surface. HDW is defined and then compared with the Haines Index (HI) for four historical fires. The Climate Forecast System Reanalysis (CFSR) is used to provide the meteorological data for calculating the indices. Our results indicate that HDW can identify days on which synoptic-and meso-alpha-scale weather processes can contribute to especially dangerous fire behavior. HDW is shown to perform better than the HI for each of the four historical fires. Additionally, since HDW is based on the meteorological variables that govern the potential for the atmosphere to affect a fire, it is possible to speculate on why HDW would be more or less effective based on the conditions that prevail in a given fire case. The HI, in contrast, does not have a physical basis, which makes speculation on why it works or does not work difficult because the mechanisms are not clear.

scholarly journals Sensitivity of fire weather index to different reanalysis products in the Iberian Peninsula

2012 ◽  
Vol 12 (3) ◽  
pp. 699-708 ◽  
Author(s):  
J. Bedia ◽  
S. Herrera ◽  
J. M. Gutiérrez ◽  
G. Zavala ◽  
I. R. Urbieta ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Iberian Peninsula ◽  
Fire Spread ◽  
Early Warning Systems ◽  
Fire Danger ◽  
General Tendency ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Effective Prevention

Abstract. Wildfires are a major concern on the Iberian Peninsula, and the establishment of effective prevention and early warning systems are crucial to reduce impacts and losses. Fire weather indices are daily indicators of fire danger based upon meteorological information. However, their application in many studies is conditioned to the availability of sufficiently large climatological time series over extensive geographical areas and of sufficient quality. Furthermore, wind and relative humidity, important for the calculation of fire spread and fuel flammability parameters, are relatively scarce data. For these reasons, different reanalysis products are often used for the calculation of surrogate fire danger indices, although the agreement with those derived from observations remains as an open question to be addressed. In this study, we analyze this problem focusing on the Canadian Fire Weather Index (FWI) – and the associated Seasonal Severity Rating (SSR) – and considering three different reanalysis products of varying resolutions on the Iberian Peninsula: NCEP, ERA-40 and ERA-Interim. Besides the inter-comparison of the resulting FWI/SSR values, we also study their correspondence with observational data from 7 weather stations in Spain and their sensitivity to the input parameters (precipitation, temperature, relative humidity and wind velocity). As a general result, ERA-Interim reproduces the observed FWI magnitudes with better accuracy than NCEP, with lower/higher correlations in the coast/inland locations. For instance, ERA-Interim summer correlations are above 0.5 in inland locations – where higher FWI magnitudes are attained – whereas the corresponding values for NCEP are below this threshold. Nevertheless, departures from the observed distributions are generally found in all reanalysis, with a general tendency to underestimation, more pronounced in the case of NCEP. In spite of these limitations, ERA-Interim may still be useful for the identification of extreme fire danger events. (e.g. those above the 90th percentile value) and for the definition of danger levels/classes (with level thresholds adapted to the observed/reanalysis distributions).

scholarly journals An assessment of fire occurrence regime and performance of Canadian fire weather index in south central Siberian boreal region

2014 ◽  
Vol 2 (7) ◽  
pp. 4711-4742 ◽  
Author(s):  
T. Chu ◽  
X. Guo
Keyword(s):  
Large Scale ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
Fire Weather ◽  
Fire Occurrence ◽  
Weather Index ◽  
Fire Weather Index ◽  
Central Siberia ◽  
South Central ◽  
Fire Activity

Abstract. Wildfire is the dominant natural disturbance in Eurasian boreal region, which acts as a major driver of the global carbon cycle. An effectiveness of wildfire management requires suitable tools for fire prevention and fire risk assessment. This study aims to investigate fire occurrence patterns in relation to fire weather conditions in the remote south central Siberia region. The Canadian Fire Weather Index derived from large-scale meteorological reanalysis data was evaluated with respects to fire regimes during 14 consecutive fire seasons in south central Siberian environment. All the fire weather codes and indices, including the Fine Fuel Moisture Code (FFMC), the Duff Moisture Code (DMC), the Drought Code (DC), the Buildup Index (BUI), the Initial Spread Index (ISI), and the Fire Weather Index (FWI), were highly reflected inter-annual variation of fire activity in south central Siberia. Even though human-caused fires were major events in Russian boreal forest including south central Siberia, extreme fire years were strongly correlated with ambient weather conditions (e.g. Arctic Oscillation, air temperature, relative humidity and wind), showing by in-phase (or positive linear relationship) and significant wavelet coherence between fire activity and DMC, ISI, BUI, and FWI. Time series observation of 14 fire seasons showed that there was an average of about 3 months lags between the peaks of fire weather conditions and fire activity, which should take into account when using coarse scale fire weather indices in the assessment of fire danger in the study area. The results are expected to contribute to a better reconstruction and prediction of fire activity using large-scale reanalysis data in remote regions in which station data are very few.

scholarly journals Fire Weather Index application in north-western Italy

2008 ◽  
Vol 2 (1) ◽  
pp. 77-80 ◽  
Author(s):  
D. Cane ◽  
N. Ciccarelli ◽  
F. Gottero ◽  
A. Francesetti ◽  
F. Pelfini ◽  
...  
Keyword(s):  
Forest Fires ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Fire Weather ◽  
Mountain Areas ◽  
Data Set ◽  
Weather Index ◽  
Fire Weather Index ◽  
North Western ◽  
Piedmont Region

Abstract. Piedmont region is located in North-Western Italy and is surrounded by the alpine chain and by the Appennines. The region is covered by a wide extension of forests, mainly in its mountain areas (the forests cover 36% of the regional territory). Forested areas are interested by wildfire events. In the period 1997–2005 Piedmont was interested by an average 387 forest fires per year, covering an average 1926 ha of forest per year. Meteorological conditions like long periods without precipitation contribute to create favourable conditions to forest fire development, while the fire propagation is made easier by the foehn winds, frequently interesting the region in winter and spring particularly. The meteorological danger index FWI (Fire Weather Index) was developed by Van Wagner (1987) for the Canadian Forestry Service, providing a complete description of the behaviour of the different forest components in response to the changing weather conditions. We applied the FWI to the Piedmont region on warning areas previously defined for fire management purposes. The meteorological data-set is based on the data of the very-dense non-GTS network of weather stations managed by Arpa Piemonte. The thresholds for the definition of a danger scenarios system were defined comparing historical FWI data with fires occurred on a 5 years period. The implementation of a prognostic FWI prediction system is planned for the early 2008, involving the use of good forecasts of weather parameters at the station locations obtained by the Multimodel SuperEnsemble post-processing technique.

scholarly journals Fire prediction with logistic regression on territory of Bosnia and Herzegovina

2021 ◽  
Vol 1208 (1) ◽  
pp. 012033
Author(s):  
Mursel Musabašić ◽  
Denis Mušić ◽  
Elmir Babović
Keyword(s):  
Logistic Regression ◽  
Index System ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Supervised Machine Learning ◽  
Fire Weather ◽  
Fire Behaviour ◽  
Weather Index ◽  
Fire Weather Index ◽  
User Input

Abstract The Canadian Fire Weather Index system [1] has been used worldwide by many countries as classic approach in fire prediction. It represents system that account for the effects of fuel moisture and weather conditions on fire behaviour. It numerical outputs are based on calculation of four meteorological elements: air temperature, relative humidity, wind speed and precipitation in last 24h. In this paper meteorological data in combination with Canadian Fire Weather Index system (CFWI) components is used as input to predict fire occurrence using logistic regression model. As logistic regression is a supervised machine learning method it’s based on user input in the form of dataset. Dataset is collected using NASA GES DISC Giovanni web-based application in the form of daily area-averaged time series in period of 31.7.2010 to 31.7.2020, it’s analysed and pre-processed before it is used as input for logit model. CFWI components values are not imported but calculated in run-time based on pre-processed meteorological data. As a result of this research windows application was developed to assist fire managers and all those involved in studying the fire behaviour.

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