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
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
From January 1, 2014, the basic stations of meteorological observation countries have changed from small evaporation observations to large-scale evaporation observations. National general weather stations have cancele...From January 1, 2014, the basic stations of meteorological observation countries have changed from small evaporation observations to large-scale evaporation observations. National general weather stations have canceled observations on evaporation, but small evaporation is very important for forest fire risk prediction. In order to make the prediction of forest fire risk level objectively, weather data in Putian City, China and the multi-linear regression analysis method is used to calculate the daily evaporation amount in the more advanced SPSS16.0 software (English version), and the data of the last 5 years of each site are selected and fitted. Results showed that we accurately calculated the evaporation of the next day to make up for the lack of data due to the adjustment of the evaporation observation project. According to the forest fire risk weather index corresponding to many meteorological factors such as evaporation, temperature, humidity, sunshine and wind speed, the forest fire risk meteorological grade standard was designed to make a more accurate forest fire risk grade forecast.展开更多
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.
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.
文摘From January 1, 2014, the basic stations of meteorological observation countries have changed from small evaporation observations to large-scale evaporation observations. National general weather stations have canceled observations on evaporation, but small evaporation is very important for forest fire risk prediction. In order to make the prediction of forest fire risk level objectively, weather data in Putian City, China and the multi-linear regression analysis method is used to calculate the daily evaporation amount in the more advanced SPSS16.0 software (English version), and the data of the last 5 years of each site are selected and fitted. Results showed that we accurately calculated the evaporation of the next day to make up for the lack of data due to the adjustment of the evaporation observation project. According to the forest fire risk weather index corresponding to many meteorological factors such as evaporation, temperature, humidity, sunshine and wind speed, the forest fire risk meteorological grade standard was designed to make a more accurate forest fire risk grade forecast.
