A Markov chain model of day to day changes in the Canadian forest fire weather index

1999 ◽  
Vol 9 (4) ◽  
pp. 265 ◽  
Author(s):  
David L. Martell
Keyword(s):  
Markov Chain ◽  
Forest Fire ◽  
Markov Chain Model ◽  
Weather Data ◽  
Fire Season ◽  
Chain Model ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Weather Stations

A Markov chain is used to model day to day changes in the Fire Weather Index (FWI) component of the Canadian Forest Fire Weather Index System. The results of statistical analyses of 26 years (1963 through 1988) of fire weather data recorded at 15 fire weather stations located across the province of Ontario suggest that it is reasonable to partition the fire season into three subseasons and model day to day changes in the Fire Weather Index class within each subseason as a Markov chain of order 1.

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.

Relationships between the moisture content of fine woody fuels in lodgepole pine slash and the Fine Fuel Moisture Code of the Canadian Forest Fire Weather Index System

1988 ◽  
Vol 18 (1) ◽  
pp. 128-131 ◽  
Author(s):  
R. Trowbridge ◽  
M. C. Feller
Keyword(s):  
Moisture Content ◽  
Forest Fire ◽  
Index System ◽  
Lodgepole Pine ◽  
Fire Season ◽  
Fire Weather ◽  
Fuel Moisture ◽  
Weather Index ◽  
Fire Weather Index ◽  
Moisture Contents

Unsuccessful attempts to ignite slash resulting from the mechanical knocking down of lodgepole pine in west central British Columbia led to a short-term investigation of the relationship between the Fine Fuel Moisture Code of the Canadian Forest Fire Weather Index System and the moisture content of various fine fuel components <1 cm in diameter. Of the types of fuel sampled, the moisture contents of B.C. Forest Service fuel moisture sticks and aged slash were similar to, and well correlated (r = 0.79 and 0.81, respectively) with, the equivalent moisture content calculated from the Fine Fuel Moisture Code. The Fine Fuel Moisture Code was not designed to relate to the moisture content of uncured fuels. Thus, the moisture contents of fresh living slash (material from knocked down trees still attached to living roots) and of fresh dead slash (material unattached to living trees that had not yet experienced a complete fire season in which to fully cure) were poorly correlated with moisture content (r = 0.16 and 0.42, respectively). The moisture content of the progressively curing, needle-bearing fresh dead slash was relatively high at the beginning of the fire season, but became similar to the moisture content during the first half of July. This suggests that the Fine Fuel Moisture Code can also be used to predict the moisture content of such fine slash after these fuels have cured for approximately 3 months during the snow-free period.

scholarly journals Development of Google Earth Engine Fire Weather Index Calculator for Indonesian Fire Danger Rating System

2021 ◽  
Vol 936 (1) ◽  
pp. 012040
Author(s):  
J S Matondang ◽  
H Sanjaya ◽  
R Arifandri
Keyword(s):  
Google Earth ◽  
Fire Danger ◽  
Rating System ◽  
Weather Data ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Weather Stations ◽  
Google Earth Engine ◽  
Fire Danger Rating System

Abstract Tropical peatlands make up almost ten percent of the land surface in Indonesia, making peat fires detrimental not only for global atmospheric carbon levels, but also to public health and socioeconomic activities in the region. Indonesian Fire Danger Rating System (FDRS) was developed based on the Canadian Forest Fire Weather Index System (CFFWIS), using three different fuel codes and three indices representing fire behaviour. Daily Fire Weather Index (FWI) calculation is done by the Meteorological Climatological and Geophysical Agency (BMKG) with data from its synoptic weather stations network. Distribution of such weather stations are sparse, therefore this paper reports on the development of Fire Weather Index calculator on Google Earth Engine, using high resolution weather data, provided by weather model and remote-sensing open datasets. The resulting application is capable of generating daily maps of FWI components to be used by the Indonesian Fire Danger Rating System.

scholarly journals Temporal variations and change in forest fire danger in Europe for 1960–2012

2014 ◽  
Vol 14 (6) ◽  
pp. 1477-1490 ◽  
Author(s):  
A. Venäläinen ◽  
N. Korhonen ◽  
O. Hyvärinen ◽  
N. Koutsias ◽  
F. Xystrakis ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
National Level ◽  
Temporal Variations ◽  
Fire Danger ◽  
Fire Season ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Current Season ◽  
Forest Fire Danger

Abstract. Understanding how fire weather danger indices changed in the past and how such changes affected forest fire activity is important in a changing climate. We used the Canadian Fire Weather Index (FWI), calculated from two reanalysis data sets, ERA-40 and ERA Interim, to examine the temporal variation of forest fire danger in Europe in 1960–2012. Additionally, we used national forest fire statistics from Greece, Spain and Finland to examine the relationship between fire danger and fires. There is no obvious trend in fire danger for the time period covered by ERA-40 (1960–1999), whereas for the period 1980–2012 covered by ERA Interim, the mean FWI shows an increasing trend for southern and eastern Europe which is significant at the 99% confidence level. The cross correlations calculated at the national level in Greece, Spain and Finland between total area burned and mean FWI of the current season is of the order of 0.6, demonstrating the extent to which the current fire-season weather can explain forest fires. To summarize, fire risk is multifaceted, and while climate is a major determinant, other factors can contribute to it, either positively or negatively.

scholarly journals Attribution of the Australian bushfire risk to anthropogenic climate change

2020 ◽  
Author(s):  
Geert Jan van Oldenborgh ◽  
Folmer Krikken ◽  
Sophie Lewis ◽  
Nicholas J. Leach ◽  
Flavio Lehner ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Southern Annular Mode ◽  
Warming Trend ◽  
Anthropogenic Climate Change ◽  
Fire Season ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index

Abstract. Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically-based index of fire weather, the Fire Weather Index, long-term observations of heat and drought, and eleven large ensembles of state-of-the-art climate models. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor two due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the likelihood of extreme heat could be larger. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season September–February. The observations, however, show a weak drying trend in the annual mean. Finally, we find large trends in the Fire Weather Index in the ERA5 reanalysis, and a smaller but significant increase by at least 30 % in the models. The trend is mainly driven by the increase of temperature extremes and hence also likely underestimated. For the 2019/20 season more than half of the July–December drought was driven by record excursions of the Indian Ocean dipole and Southern Annular Mode. These factors are included in the analysis. The study reveals the complexity of the 2019/20 bushfire event, with some, but not all drivers showing an imprint of anthropogenic climate change.

scholarly journals Verification of WRF modelled fire weather in the 2009–10 New Zealand fire season

2014 ◽  
Vol 23 (1) ◽  
pp. 34 ◽  
Author(s):  
C. C. Simpson ◽  
H. G. Pearce ◽  
A. P. Sturman ◽  
P. Zawar-Reza
Keyword(s):  
New Zealand ◽  
Weather Conditions ◽  
Model Error ◽  
Dew Point ◽  
Fire Season ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Wind Speeds ◽  
Air Temperatures ◽  
Weather Stations

The Weather Research and Forecasting (WRF) mesoscale model was used to simulate the fire weather conditions for the 2009–10 wildland fire season in New Zealand. The suitability of WRF to simulate the high-end fire weather conditions for this period was assessed through direct comparison with observational data taken from 23 surface and two upper-air stations located across New Zealand. The weather variables and fire weather indices considered in the verification were the 1200 hours NZST air temperature, relative humidity, wind speed and direction, 24-h rainfall, New Zealand Fire Weather Index (FWI) and Continuous Haines Index (CHI). On observed high-end fire weather days, the model under-predicted the air temperatures and relative humidities, and over-predicted the wind speeds and 24-h rainfall at most weather stations. The results demonstrated that although WRF is suitable for modelling the air temperatures, there are issues with modelling the wind speeds and rainfall quantities. The model error in the wind speeds and 24-h rainfall contributed significantly towards the model under-prediction of the FWI on observed high-end fire weather days. In addition, the model was not suitable for predicting the number of high-end fire weather days at most weather stations, which represents a serious operational limitation of the WRF model for fire management applications. Finally, the modelled CHI values were only in moderate agreement with the observed values, principally due to the model error in the dew point depression at 850hPa.

The Canadian Forest Fire Weather Index System as a predictor of total soil moisture content as estimated by the Thornthwaite water balance

1985 ◽  
Vol 15 (6) ◽  
pp. 1194-1195
Author(s):  
Robert S. McAlpine ◽  
Thomas G. Eiber
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Water Balance ◽  
Forest Fire ◽  
Index System ◽  
Soil Moisture Content ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Total Soil

Weather data from Upsala and Atikokan, Ontario, were used to determine the Canadian Forest Fire Weather Index System values and to calculate the soil moisture for two soil types using the Thornthwaite water balance. The Duff Moisture Code and the Drought Code were found to give excellent correlations with the total soil moisture content under most weather patterns.

scholarly journals Fire Weather Index Implementation in the Alpine Area

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Daniele Cane ◽  
Nadia Ciccarelli ◽  
Renata Pelosini
Keyword(s):  
Forest Fire ◽  
Fire Weather ◽  
Mountain Areas ◽  
Weather Index ◽  
Local Conditions ◽  
Fire Weather Index ◽  
Fire Propagation ◽  
A New Technique ◽  
Definition Of ◽  
Piedmont Region

Piedmont region is located in North-Western Italy and is surrounded by the alpine chain and by the Apennines. The region is covered by a wide extension of forests, mainly in its mountain areas (the forests cover 36% of the regional territory). In the period 1997–2007, Piedmont gained interest by an average of 378 wildfire events per year, covering an average of 1767 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. We applied the Fire Weather Index FWI (Van Wagner, 1987) to the Piedmont region on warning areas previously defined for fire management purposes (Cane et al., 2008). Here we present a new technique for the definition of thresholds in order to obtain alert levels more suited with the local conditions of the forest fire warning areas. We describe also the implementation of the prognostic FWI prediction system, involving the use of good forecasts of weather parameters at the station locations obtained by the Multimodel SuperEnsemble postprocessing technique.

First order multivariate Markov chain model for generating annual weather data for Hong Kong

2011 ◽  
Vol 43 (9) ◽  
pp. 2371-2377 ◽  
Author(s):  
Hongxing Yang ◽  
Yutong Li ◽  
Lin Lu ◽  
Ronghui Qi
Keyword(s):  
Hong Kong ◽  
Markov Chain ◽  
Markov Chain Model ◽  
Weather Data ◽  
Chain Model ◽  
First Order
Sign in / Sign up

Export Citation Format

Share Document