scholarly journals Fire Danger Harmonization Based on the Fire Weather Index for Transboundary Events between Portugal and Spain

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1087
Author(s):  
Daniela Alves ◽  
Miguel Almeida ◽  
Domingos Xavier Viegas ◽  
Ilda Novo ◽  
M. Yolanda Luna
Keyword(s):  
Meteorological Data ◽  
Decision Support Tool ◽  
Fire Danger ◽  
Fire Intensity ◽  
Burned Area ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Support Tool ◽  
Buffer Strip

Portugal and Spain have a cross-border cooperation protocol on wildfires response for a buffer strip of 25 km for each side of the border. In spite of the success of this collaboration, there are issues to be improved, since Portuguese and Spanish authorities use different methodologies to assess the daily fire danger. A methodology to harmonize fire danger and its interpretation by the Portuguese and Spanish Civil protection authorities in the transboundary buffer strip area is hereby presented. The fire danger index used is the Canadian Fire Weather Index (FWI), which requires input from meteorological data and gives an indication of fire intensity. The fire danger class is an important decision support tool for preventing and fighting wildfires. Since the meaning of FWI values change from region-to-region according to its specific characteristics, a calibration process was performed based on statistical data of the daily FWI values, the number of fires and burned area between 2005 and 2013. The results of the FWI calibration and harmonization of the data for the five danger classes minimizes the fire danger discrepancies across the border. This methodology has the potential to be reproduced in other areas.

scholarly journals Updated Operational Implementation of the Canadian Forest Fire Weather Index System in Ireland

2021 ◽  
Author(s):  
Padraig Flattery ◽  
Klara Finkele ◽  
Paul Downes ◽  
Ferdia O'Leary ◽  
Ciaran Nugent
Keyword(s):  
Forest Fire ◽  
Index System ◽  
Weather Prediction ◽  
Fire Danger ◽  
Energy Output ◽  
Fire Intensity ◽  
Fire Weather ◽  
Reference Period ◽  
Weather Index ◽  
Fire Weather Index

<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>

Evaluation of the reliability of the high-resolution WRF fire danger forecasts in Poland

2021 ◽  
Author(s):  
Marta Gruszczynska ◽  
Alan Mandal ◽  
Grzegorz Nykiel ◽  
Tomasz Strzyzewski ◽  
Weronika Wronska ◽  
...  
Keyword(s):  
High Resolution ◽  
Forest Fires ◽  
Human Life ◽  
Meteorological Data ◽  
Fire Service ◽  
Fire Danger ◽  
Economic Losses ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index

<p>Fires negatively affect the composition and structure of fauna and flora, as well as the quality of air, soils and water. They cause economic losses and pose a risk to human life. Poland is at the forefront of European countries in terms of forest fires. Therefore, Institute of Meteorology and Water Management - National Research Institute (IMWM-NIR) implemented fire danger forecast system based on high-resolution (2.5 km) Weather Research and Forecast (WRF) model. Forecasted meteorological data are used to calculate parameters of Canadian Forest Fire Weather Index (FWI) System: Fire Weather Index (FWI), Initial Spread Index (ISI), Buildup Index (BUI), Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), and Drought Code (DC). Each parameter is presented in one of the classes corresponding to the fire danger – from low to extreme. In this way, a daily 24- and 48-hour fire danger forecasts are generated for the whole area of Poland and presented on IMWM-NIR meteorological website (meteo.imgw.pl).</p><p>In this presentation we show analyses of reliability of implemented FWI system. For this purpose, data reprocessing from March to September 2019 were made. Also data on fires occurrence on forest lands: time of occurrence, characteristics and location, from the resources of the State Fire Service were collected. Finally, for the selected period, we obtained a dataset of about 8 thousand events for which we assigned values of FWI parameters. Generally, based on our analysis, correlation between number of fires and averaged value of FWI amounted over 0.8. We found out, the correlation coefficient calculated for regions differ. The correlation is higher in central and northern Poland compared to the eastern part of the country, which also correspond to the number of fires. This may be related to the different forest structure - there is a higher proportion of broadleaf forests in the east. The comparison of 24- and 48-hour forecasts showed that they have similar reliability.</p>

scholarly journals Forest Fire Prediction in Northern Sumatera using Support Vector Machine Based on the Fire Weather Index

2020 ◽  
Author(s):  
Darwis Robinson Manalu ◽  
Muhammad Zarlis ◽  
Herman Mawengkang ◽  
Opim Salim Sitompul
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Meteorological Data ◽  
Burned Area ◽  
Support Vector ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Data Mining Approach ◽  
Prevention Activity

Forest fires are a major environmental issue, creating economical and ecological damage while dangering human lives. The investigation and survey for forest fire had been done in Aek Godang, Northern Sumatera, Indonesia. There is 26 hotspot in 2017 close to Aek Godang, North Sumatera, Indonesia. In this study, we use a data mining approach to train and test the data of forest fire and the Fire Weather Index (FWI) from meteorological data. The aim of this study to predict the burned area and identify the forest fire in Aek Godang areas, North Sumatera. The result of this study indicated that Fire fighting and prevention activity may be one reason for the observed lack of correlation. The fact that this dataset exists indicates that there is already some effort going into fire prevention.

scholarly journals Calibration and evaluation of the Canadian Forest Fire Weather Index (FWI) System for improved wildland fire danger rating in the United Kingdom

2016 ◽  
Vol 16 (5) ◽  
pp. 1217-1237 ◽  
Author(s):  
Mark C. de Jong ◽  
Martin J. Wooster ◽  
Karl Kitchen ◽  
Cathy Manley ◽  
Rob Gazzard ◽  
...  
Keyword(s):  
United Kingdom ◽  
Fire Severity ◽  
Weather Prediction ◽  
Fire Danger ◽  
Fire Weather ◽  
Rating Systems ◽  
Weather Index ◽  
Fire Weather Index ◽  
The United Kingdom ◽  
The Uk

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.

Wildfires and the Canadian Forest Fire Weather Index system for the Daxing'anling region of China

2011 ◽  
Vol 20 (8) ◽  
pp. 963 ◽  
Author(s):  
Xiaorui Tian ◽  
Douglas J. McRae ◽  
Jizhong Jin ◽  
Lifu Shu ◽  
Fengjun Zhao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Coniferous Forest ◽  
Northern China ◽  
Fire Danger ◽  
Fire Season ◽  
Fire Weather ◽  
Burnt Area ◽  
Weather Index ◽  
Fire Weather Index

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.

A Study on the Interpolation of Fire Danger Using Radar Precipitation Estimates

1998 ◽  
Vol 8 (4) ◽  
pp. 217 ◽  
Author(s):  
MD Flannigan ◽  
BM Wotton ◽  
S Ziga
Keyword(s):  
Index System ◽  
Fire Management ◽  
Fire Danger ◽  
The Other ◽  
Fire Weather ◽  
Weather Variables ◽  
Weather Index ◽  
Fire Weather Index ◽  
Precipitation Estimates ◽  
Weather Stations

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.

scholarly journals Variation in the Canadian Fire Weather Index Thresholds for Increasingly Larger Fires in Portugal

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 838 ◽  
Author(s):  
Fernandes
Keyword(s):  
Fire Management ◽  
Net Primary Production ◽  
Spatial Scales ◽  
Fire Danger ◽  
Fire Weather ◽  
Fire Size ◽  
Weather Index ◽  
Fire Weather Index ◽  
North Central ◽  
Forest Fire Management

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.

Reanalysis of ECMWF data for updating the Fire Weather Index for the Indonesia Fire Danger Rating System (InaFDRS)

2021 ◽  
Author(s):  
Andri Purwandani ◽  
Marina C. G. Frederik ◽  
Reni Sulistyowati ◽  
Lena Sumargana ◽  
Fanny Meliani ◽  
...  
Keyword(s):  
Fire Danger ◽  
Rating System ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Fire Danger Rating System

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.

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