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 Modelling fire frequency and area burned across phytoclimatic regions in Spain using reanalysis data and the Canadian Fire Weather Index System

2013 ◽  
Vol 1 (5) ◽  
pp. 4891-4924 ◽  
Author(s):  
J. Bedia ◽  
S. Herrera ◽  
J. M. Gutiérrez
Keyword(s):  
Fire Regimes ◽  
Fire Frequency ◽  
Reanalysis Data ◽  
Climate Impacts ◽  
Burned Area ◽  
Fire Weather ◽  
Fire Occurrence ◽  
Weather Index ◽  
Fire Weather Index ◽  
Area Burned

Abstract. We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990–2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter–annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness of ERA-Interim reanalysis data for the reconstruction of historical fire-climate relationships at the scale of analysis. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable.

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.

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.

Calibration of the Fire Weather Index over Mediterranean Europe based on fire activity retrieved from MSG satellite imagery

2014 ◽  
Vol 23 (7) ◽  
pp. 945 ◽  
Author(s):  
Carlos C. DaCamara ◽  
Teresa J. Calado ◽  
Sofia L. Ermida ◽  
Isabel F. Trigo ◽  
Malik Amraoui ◽  
...  
Keyword(s):  
Land Surface ◽  
Relative Number ◽  
Fire Risk ◽  
Fire Danger ◽  
Weather Data ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Fire Activity ◽  
Mediterranean Europe

Here we present a procedure that allows the operational generation of daily maps of fire danger over Mediterranean Europe. These are based on integrated use of vegetation cover maps, weather data and fire activity as detected by remote sensing from space. The study covers the period of July–August 2007 to 2009. It is demonstrated that statistical models based on two-parameter generalised Pareto (GP) distributions adequately fit the observed samples of fire duration and that these models are significantly improved when the Fire Weather Index (FWI), which rates fire danger, is integrated as a covariate of scale parameters of GP distributions. Probabilities of fire duration exceeding specified thresholds are then used to calibrate FWI leading to the definition of five classes of fire danger. Fire duration is estimated on the basis of 15-min data provided by Meteosat Second Generation (MSG) satellites and corresponds to the total number of hours in which fire activity is detected in a single MSG pixel during one day. Considering all observed fire events with duration above 1h, the relative number of events steeply increases with classes of increasing fire danger and no fire activity was recorded in the class of low danger. Defined classes of fire danger provide useful information for wildfire management and are based on the Fire Risk Mapping product that is being disseminated on a daily basis by the EUMETSAT Satellite Application Facility on Land Surface Analysis.

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.

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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