We evaluated the spatial and temporal patterns of forest fires in two fire seasons (March to June and September to November) from 1996 to 2010 in Jilin Province, China, using the Canadian Forest Fire Weather Index Sys...We evaluated the spatial and temporal patterns of forest fires in two fire seasons (March to June and September to November) from 1996 to 2010 in Jilin Province, China, using the Canadian Forest Fire Weather Index System. Fire data were obtained from the Provincial Fire Agency, and historical climate records of daily weather observations were collected from 36 weather stations in Jilin and its neighboring provinces. A linear regression model was used to analyze linear trends between climate and fire weather indices with time treated as an independent variable. Correlation analysis was used to detect correlations between fire frequency, areas burned, and fire weather indices. A thin-plate smooth spline model was used to interpolate the point data of 36 weather stations to generate a surface covering the whole province. Our analyses indicated fire frequency and areas burned were significantly correlated with fire weather indices. Overall, the Canadian Forest Fire Weather Index System appeared to be work well for determining the fire danger rating in Jilin Province. Also, our analyses indicated that in the forthcoming decades, the overall fire danger in March and April should decrease across the province, but the chance of a large fire in these months would increase. The fire danger in the fall fire season would increase in the future, and the chance of large fire would also increase. Historically, because most fires have occurred in the spring in Jilin Province, such a shift in the future fire danger between the two fire seasons would be beneficial for the province's fire management.展开更多
Daxing’anling is a key region for forest fire prevention in China. Assessing changes in fire risk in the future under multiple climatic scenarios will contribute to our understanding of the influences of climate chan...Daxing’anling is a key region for forest fire prevention in China. Assessing changes in fire risk in the future under multiple climatic scenarios will contribute to our understanding of the influences of climate change for the region and provide a reference for applying adaptive measures for fire management. This study analyzed the changes in fire weather indices and the fire season under four climate scenarios (RCP2.6, RCP4.5, RCP6.0, RCP8.5) for 2021-2050 using data from five global climate models together with observation data. The results showed that the analog data could project the average state of the climate for a given period but were not effective for simulating extreme weather conditions. Compared with the baseline period (1971-2000), the period 2021-2050 was predicted to have an increase in average temperature of 2.02-2.65 °C and in annual precipitation 25.4-40.3 mm, while the fire weather index (FWI) was predicted to increase by 6.2-11.2% and seasonal severity rating (SSR) by 5.5-17.2%. The DMC (Duff moisture code), ISI (initial spread index), BUI (build-up index), FWI and SSR were predicted to increase significantly under scenarios RCP4.5, RCP6.0, and RCP8.5. Furthermore, days with high or higher fire danger rating were predicted to be prolonged by 3-6 days, with the change in the southern region being greater under scenarios RCP4.5, RCP6.0, and RCP8.5.展开更多
Introduction:The Canadian Forest Fire Danger Rating System(CFFDRS)is a globally known wildland fire risk assessment system,and two major components,the fire weather index system and the fire behavior prediction system...Introduction:The Canadian Forest Fire Danger Rating System(CFFDRS)is a globally known wildland fire risk assessment system,and two major components,the fire weather index system and the fire behavior prediction system,have been extensively used both nationally and internationally to aid operational wildland fire decision making.Methods:In this paper,we present an overview of an R package cffdrs,which is developed to calculate components of the CFFDRS,and highlight some of its functionality.In particular,we demonstrate how these functions could be used for large data analysis.Results and Discussion:With this cffdrs package,we provide a portal for not only a collection of R functions dealing with all available components in CFFDRS but also a platform for various additional developments that are useful for the understanding of fire occurrence and behavior.This is the first time that all relevant CFFDRS methods are incorporated into the same platform,which can be accessed by both the management and research communities.展开更多
基金financially supported by the National Natural Science Foundation of China(31470497)Project 2013-158,Jilin Provincial Education Department+1 种基金Project 2013-007,Jilin Provincial Forestry Departmentsupported by the Program for New Century Excellent Talents in the University(NCET-12-0726)
文摘We evaluated the spatial and temporal patterns of forest fires in two fire seasons (March to June and September to November) from 1996 to 2010 in Jilin Province, China, using the Canadian Forest Fire Weather Index System. Fire data were obtained from the Provincial Fire Agency, and historical climate records of daily weather observations were collected from 36 weather stations in Jilin and its neighboring provinces. A linear regression model was used to analyze linear trends between climate and fire weather indices with time treated as an independent variable. Correlation analysis was used to detect correlations between fire frequency, areas burned, and fire weather indices. A thin-plate smooth spline model was used to interpolate the point data of 36 weather stations to generate a surface covering the whole province. Our analyses indicated fire frequency and areas burned were significantly correlated with fire weather indices. Overall, the Canadian Forest Fire Weather Index System appeared to be work well for determining the fire danger rating in Jilin Province. Also, our analyses indicated that in the forthcoming decades, the overall fire danger in March and April should decrease across the province, but the chance of a large fire in these months would increase. The fire danger in the fall fire season would increase in the future, and the chance of large fire would also increase. Historically, because most fires have occurred in the spring in Jilin Province, such a shift in the future fire danger between the two fire seasons would be beneficial for the province's fire management.
基金financially supported by the National Natural Science Foundation of China(31270695)the National Science and Technology Support Plan(2012BAC19B02)
文摘Daxing’anling is a key region for forest fire prevention in China. Assessing changes in fire risk in the future under multiple climatic scenarios will contribute to our understanding of the influences of climate change for the region and provide a reference for applying adaptive measures for fire management. This study analyzed the changes in fire weather indices and the fire season under four climate scenarios (RCP2.6, RCP4.5, RCP6.0, RCP8.5) for 2021-2050 using data from five global climate models together with observation data. The results showed that the analog data could project the average state of the climate for a given period but were not effective for simulating extreme weather conditions. Compared with the baseline period (1971-2000), the period 2021-2050 was predicted to have an increase in average temperature of 2.02-2.65 °C and in annual precipitation 25.4-40.3 mm, while the fire weather index (FWI) was predicted to increase by 6.2-11.2% and seasonal severity rating (SSR) by 5.5-17.2%. The DMC (Duff moisture code), ISI (initial spread index), BUI (build-up index), FWI and SSR were predicted to increase significantly under scenarios RCP4.5, RCP6.0, and RCP8.5. Furthermore, days with high or higher fire danger rating were predicted to be prolonged by 3-6 days, with the change in the southern region being greater under scenarios RCP4.5, RCP6.0, and RCP8.5.
文摘Introduction:The Canadian Forest Fire Danger Rating System(CFFDRS)is a globally known wildland fire risk assessment system,and two major components,the fire weather index system and the fire behavior prediction system,have been extensively used both nationally and internationally to aid operational wildland fire decision making.Methods:In this paper,we present an overview of an R package cffdrs,which is developed to calculate components of the CFFDRS,and highlight some of its functionality.In particular,we demonstrate how these functions could be used for large data analysis.Results and Discussion:With this cffdrs package,we provide a portal for not only a collection of R functions dealing with all available components in CFFDRS but also a platform for various additional developments that are useful for the understanding of fire occurrence and behavior.This is the first time that all relevant CFFDRS methods are incorporated into the same platform,which can be accessed by both the management and research communities.
