A study of interpolation methods for forest fire danger rating in Canada

1989 ◽  
Vol 19 (8) ◽  
pp. 1059-1066 ◽  
Author(s):  
M. D. Flannigan ◽  
B. M. Wotton

Canadian fire control agencies use either simple interpolation methods or none at all in estimating fire danger between weather stations. We compare several methods of interpolation and use the fire weather index in the North Central Region of Ontario as a case study. Our work shows that the second order least square polynomial, the smoothed cubic spline, and the weighted interpolations had the lowest residual sum of squares in our verification scheme. These methods fit the observed data at both high and low fire weather index values. The highly variable nature of the spatial distribution of summer precipitation amount is the biggest problem in interpolating between stations. This factor leads to highly variable fire weather index fields that are the most difficult to interpolate. The use of radar and (or) satellite data could help resolve precipitation patterns with greater precision. These interpolation methods could easily be implemented by fire control agencies to gain a better understanding of fire danger in the region.

2016 ◽  
Vol 16 (5) ◽  
pp. 1217-1237 ◽  
Author(s):  
Mark C. de Jong ◽  
Martin J. Wooster ◽  
Karl Kitchen ◽  
Cathy Manley ◽  
Rob Gazzard ◽  
...  

Abstract. Wildfires in the United Kingdom (UK) pose a threat to people, infrastructure and the natural environment. During periods of particularly fire-prone weather, wildfires can occur simultaneously across large areas, placing considerable stress upon the resources of fire and rescue services. Fire danger rating systems (FDRSs) attempt to anticipate periods of heightened fire risk, primarily for early-warning and preparedness purposes. The UK FDRS, termed the Met Office Fire Severity Index (MOFSI), is based on the Fire Weather Index (FWI) component of the Canadian Forest FWI System. The MOFSI currently provides daily operational mapping of landscape fire danger across England and Wales using a simple thresholding of the final FWI component of the Canadian FWI System. However, it is known that the system has scope for improvement. Here we explore a climatology of the six FWI System components across the UK (i.e. extending to Scotland and Northern Ireland), calculated from daily 2km × 2km gridded numerical weather prediction data and supplemented by long-term meteorological station observations. We used this climatology to develop a percentile-based calibration of the FWI System, optimised for UK conditions. We find this approach to be well justified, as the values of the "raw" uncalibrated FWI components corresponding to a very "extreme" (99th percentile) fire danger situation vary by more than an order of magnitude across the country. Therefore, a simple thresholding of the uncalibrated component values (as is currently applied in the MOFSI) may incur large errors of omission and commission with respect to the identification of periods of significantly elevated fire danger. We evaluate our approach to enhancing UK fire danger rating using records of wildfire occurrence and find that the Fine Fuel Moisture Code (FFMC), Initial Spread Index (ISI) and FWI components of the FWI System generally have the greatest predictive skill for landscape fire activity across Great Britain, with performance varying seasonally and by land cover type. At the height of the most recent severe wildfire period in the UK (2 May 2011), 50 % of all wildfires occurred in areas where the FWI component exceeded the 99th percentile. When all wildfire events during the 2010–2012 period are considered, the 75th, 90th and 99th percentiles of at least one FWI component were exceeded during 85, 61 and 18 % of all wildfires respectively. Overall, we demonstrate the significant advantages of using a percentile-based calibration approach for classifying UK fire danger, and believe that our findings provide useful insights for future development of the current operational MOFSI UK FDRS.


2011 ◽  
Vol 20 (8) ◽  
pp. 963 ◽  
Author(s):  
Xiaorui Tian ◽  
Douglas J. McRae ◽  
Jizhong Jin ◽  
Lifu Shu ◽  
Fengjun Zhao ◽  
...  

The Canadian Forest Fire Weather Index (FWI) system was evaluated for the Daxing'anling region of northern China for the 1987–2006 fire seasons. The FWI system reflected the regional fire danger and could be effectively used there in wildfire management. The various FWI system components were classified into classes (i.e. low to extreme) for fire conditions found in the region. A total of 81.1% of the fires occurred in the high, very high and extreme fire danger classes, in which 73.9% of the fires occurred in the spring (0.1, 9.5, 33.3 and 33.1% in March, April, May and June). Large wildfires greater than 200 ha in area (16.7% of the total) burnt 99.2% of the total burnt area. Lightning was the main ignition source for 57.1% of the total fires. Result show that forest fires mainly occurred in deciduous coniferous forest (61.3%), grass (23.9%) and deciduous broad leaved forest (8.0%). A bimodal fire season was detected, with peaks in May and October. The components of FWI system were good indicators of fire danger in the Daxing'anling region of China and could be used to build a working fire danger rating system for the region.


1998 ◽  
Vol 8 (4) ◽  
pp. 217 ◽  
Author(s):  
MD Flannigan ◽  
BM Wotton ◽  
S Ziga

In Canada, many fire management agencies interpolate indexes of the Fire Weather Index System to estimate the fire danger between weather stations. Difficulties with interpolation arise because summer precipitation can be highly variable over short distances. This variability hinders the usefulness of interpolating precipitation, which is one of the inputs for the Fire Weather Index System. Precipitation estimates from the Canadian Atmospheric Environment Service radar at Upsala, Ontario, were used to determine if this will enable a more accurate measure of the fire danger over the region. Three methods of interpolation of the fire danger between weather stations were compared: first, the standard practice of interpolating fire weather indexes from weather stations to any specified location; second, interpolating the weather variables, temperature, relative humidity, wind speed and precipitation from the weather station to any specified site and then calculating the fire weather indexes; third, interpolating weather variables as in Method 2 above except using the precipitation estimate from the radar and then calculating the fire weather indexes for any specified site. Overall, results indicate that the standard procedure of interpolating the fire weather indexes performs better than the other two methods. However, there are indexes where the other methods perform best (e.g., the fine fuel moisture code is best determined by using the radar precipitation estimation method). Fire management agencies should continue to use the standard practice of interpolating fire weather indexes to estimate fire danger between weather stations. Factors influencing the performance of the radar estimated precipitation method of estimating fire danger are discussed along with potential application of precipitation radar for fire management purposes.


2021 ◽  
Author(s):  
Padraig Flattery ◽  
Klara Finkele ◽  
Paul Downes ◽  
Ferdia O'Leary ◽  
Ciaran Nugent

<p>Since 2006 the Canadian Forest Fire Weather Index System (FWI) has been used operationally at Met Éireann to predict the risk of forest fires in Ireland (Walsh, S, 2006). Although only around 11% or ca 770,000 ha of the total land area of Ireland is afforested, there are also large areas of open mountain and peatlands that are covered in grasses, dwarfshrub and larger woody shrub type vegetation which can provide ready fuel for spring wildfires, when suitable conditions arise. Following winter, much of this vegetation is either dead or has a very low live moisture content, and the flammability of this vegetation can be readily influenced by prevailing weather, most especially following prolonged dry periods. The Department of Agriculture, Food and Marine is the Forest Protection authority in Ireland and issues Fire Danger Notices as part of this work. These notices permit improved preparedness for fire responses and are based on information provided by Met Éireann on the current status of FWI and FWI components using observation data at synoptic stations and the predicted FWI for the next five days ahead based on numerical weather prediction input data.</p><p>The FWI is based on</p><ul><li>three different types of forest fuel, ie how quickly these dry out/get rewetted. These are the Fine Fuels Moisture Code (FFMC), the Duff Moisture Code (DMC) and the Drought Code (DC).</li> <li>components based on fire behaviour: the Initial Spread Index (ISI), the Build-up Index (BUI), and the Fire Weather Index (FWI) which represents fire intensity as energy output rate per unit length of fire front. It is then used to determine the Daily Severity Rating (DSR) of the fire danger. </li> </ul><p>Of these components, the FFMC and ISI components have been found to provide the most accurate indication of risk under Irish conditions, based on the fuels involved and ignition patterns observed to date.</p><p>The DSR was based on a climatology of 1971 to 2005 at the time of operational implantation of the FWI at Met Éireann. An updated climatology based on the new reference period of 1990 to 2020 will be shown as well as the change of the 98 percentiles of extreme rating using this new reference period.  </p><p><strong>Walsh, S.</strong> “Implementation in Ireland of the Canadian Forest Fire Weather Index System.” In <em>Making Science Work on the Farm. A Workshop on Decision Support Systems for Irish Agriculture</em>, 120–126. Dublin: AGMET, 2007. </p>


Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 838 ◽  
Author(s):  
Fernandes

Forest fire management relies on the fire danger rating to optimize its suite of activities. Limiting fire size is the fire management target whenever minimizing burned area is the primary goal, such as in the Mediterranean Basin. Within the region, wildfire incidence is especially acute in Portugal, a country where fire-influencing anthropogenic and landscape features vary markedly within a relatively small area. This study establishes daily fire weather thresholds associated to transitions to increasingly larger fires for individual Portuguese regions (2001–2011 period), using the national wildfire and Canadian fire weather index (FWI) databases and logistic regression. FWI thresholds variation in relation to population density, topography, land cover, and net primary production (NPP) metrics is examined through regression and cluster analysis. Larger fires occur under increasingly higher fire danger. Resistance to fire spread (the fire-size FWI thresholds) varies regionally following biophysical gradients, and decreases under more complex topography and when NPP and occupation by flammable forest or by shrubland increase. Three main clusters synthesize these relationships and roughly coincide with the western north-central, eastern north-central and southern parts of the country. Quantification of fire-weather relationships can be improved through additional variables and analysis at other spatial scales.


2021 ◽  
Author(s):  
Andri Purwandani ◽  
Marina C. G. Frederik ◽  
Reni Sulistyowati ◽  
Lena Sumargana ◽  
Fanny Meliani ◽  
...  

1999 ◽  
Vol 9 (3) ◽  
pp. 183 ◽  
Author(s):  
Laura L. Bourgeau-Chavez ◽  
Eric S. Kasischke ◽  
Mark D. Rutherford

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.


2017 ◽  
Vol 47 (12) ◽  
pp. 1646-1658 ◽  
Author(s):  
P. Jain ◽  
M.D. Flannigan

Spatial interpolation of fire weather variables from station data allow fire danger indices to be mapped continuously across the landscape. This information is crucial to fire management agencies, particularly in areas where weather data are sparse. We compare the performance of several standard interpolation methods (inverse distance weighting, spline, and geostatistical interpolation methods) for estimating output from the Canadian Fire Weather Index (FWI) system at unmonitored locations. We find that geostatistical methods (kriging) generally outperform the other methods, particularly when elevation is used as a covariate. We also find that interpolation of the input meteorological variables and the previous day’s moisture codes to unmonitored locations followed by calculation of the FWI output variables is preferable to first calculating the FWI output variables and then interpolating, in contrast to previous studies. Alternatively, when the previous day’s moisture codes are estimated from interpolated weather, rather than directly interpolated, errors can accumulate and become large. This effect is particularly evident for the duff moisture code and drought moisture code due to their significant autocorrelation.


2021 ◽  
Author(s):  
Anasuya Barik ◽  
Somnath Baidya Roy

<p>The Canadian Forest Fire Danger Rating System (CFFDRS) is used to assess and predict the fire behavior in various forest ecosystems all over the world. The Fire Weather Index (FWI) module of the CFFDRS models the relationship between meteorology and forest fires. It was observed in our earlier study that the values of the FWI and its related parameters were considerably different from the other countries that use the model for their operational fire weather simulation. In this study we evaluate the model performance over Indian climate for a period of 10 years 1996-2005 under various weather scenarios. The daily meteorological data from ECMWF’s ERA5 reanalysis has been used as inputs to the fire model and the active fire data from MODIS Terra and Aqua satellites over the study period has been used to evaluate the capability of model to simulate fire danger. As India has many different climatic zones, we evaluated the behavior fire model parameters over 5 forest zones namely Himalayan, Deciduous, Western Ghats, Thorn forests and North Eastern forests based on the Roy et al. 2016 Land Use Land Cover data and Koppen climatic zones.  The analysis was narrowed down over only the forest areas of the zones so as to remove any chances of including the non-forest fires detected by the satellite. Results show that the FWI shows a strong correlation with forest fires if the model is correctly spun up and appropriately calibrated. A spin up time of minimum 60 days was found to be appropriate for stabilization of FWI components like Duff Moisture Code (DMC) and Drought Code (DC). Sensitivity studies showed that temperature and relative humidity are the key controlling factors of forest fires over India and that the parameters depict high interannual seasonality due to relatively lower values during the Indian monsoon season.</p><p>This study is one of the first attempts to use fire models to simulate fire behavior over India. It can serve as a launchpad for further work on fire hazard prediction and effects of climate change on fire hazard in India.</p>


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