气候变化领域集成服务门户(CCPortal): Downscaling fire weather extremes from historical and projected climate models

CCPortal

DOI	10.1007/s10584-020-02865-5
	Downscaling fire weather extremes from historical and projected climate models
	Jain P.; Tye M.R.; Paimazumder D.; Flannigan M.
发表日期	2020
ISSN	0165-0009
英文摘要	An important aspect of predicting future wildland fire risk is estimating fire weather—weather conducive to the ignition and propagation of fire—under realistic climate change scenarios. Because the majority of area burned occurs on a few days of extreme fire weather, this task should be able to resolve fire weather extremes. In this paper, we present a statistical downscaling procedure based on distribution based scaling (DBS) to bias correct the Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System, as calculated from modeled climate data. Our study area is western Canada (British Columbia and Alberta) and we consider both an historical control period (1990–2000) and three future time periods (2020–2030, 2050–2060, and 2080–2090). The historical data used to calibrate the DBS procedure comprises weather station data and weather from the North American Regional Reanalysis (NARR), whereas the future climate projections are the output of three regional climate models, corresponding to different model parameterizations and downscaled from the NCAR Community Earth System Model under the RCP 8.5 scenario. By fitting a truncated Weibull distribution to observed and modeled FWI values, our method is able to reproduce historical extremes in fire weather indices as determined by the distribution of annual potential spread days, which are defined as days with FWI values greater than 19. Moreover, by calibrating the DBS procedure with gridded reanalysis data as well as station observations, we are able to project future spread day distributions over the entire study area. The results of this study show the DBS procedure leads to a greater number of projected annual spread days at most locations compared with estimates using the uncorrected model output, and that all three RCM models show positive increases in potential annual spread days for the 2050–2060 and 2080–2090 time periods. © 2020, Crown.
英文关键词	Index-Spread days-Statistical downscaling-Bias correction- Climate change; Weather; Wildfires-Fire
语种	英语
scopus关键词	Climate change; Deforestation; Earth (planet); Fires; Risk perception; Weibull distribution; British Columbia; Climate change scenarios; Earth system model; Fire weather index; Future climate projections; Regional climate models; Statistical downscaling; Weather stations; Climate models
来源期刊	Climatic Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/147290
作者单位	Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Edmonton, AB, Canada; Department of Renewable Resources, University of Alberta, Edmonton, AB, Canada; Mesoscale & Microscale Meteorology Laboratory, National Center for Atmospheric Research, Boulder, CO, United States; AIG, American International Group, Catastrophe Management and Analytics Center of Excellence, Philadelphia, PA, United States
推荐引用方式 GB/T 7714	Jain P.,Tye M.R.,Paimazumder D.,et al. Downscaling fire weather extremes from historical and projected climate models[J],2020.
APA	Jain P.,Tye M.R.,Paimazumder D.,&Flannigan M..(2020).Downscaling fire weather extremes from historical and projected climate models.Climatic Change.
MLA	Jain P.,et al."Downscaling fire weather extremes from historical and projected climate models".Climatic Change (2020).