Future fire danger climatology for Tasmania, Australia, using a dynamically downscaled regional climate model

• Published in: International journal of wildland fire Vol. 23; no. 3; pp. 309 - 321
• Main Authors: Fox-Hughes, Paul, Harris, Rebecca, Lee, Greg, Grose, Michael, Bindoff, Nathan
• Format: Journal Article
• Language: English
• Published: Roslyn CSIRO Publishing 01.01.2014; CSIRO
• Subjects: autumn; climate; Climate change; Climate models; Climate science; Climatology; Daily Values; Emissions; fire hazard; Fire hazards; fire weather; Forest & brush fires; Forest fires; Growth models; Humidity; Precipitation; Prescribed fire; Rain; Regions; sea level; seasonal variation; Seasonal variations; spring; Tasmania; Temperature; Wind; Tasmania; Australia; United States > US; Tasmania Australia
• ISSN: 1049-8001; 1448-5516
• DOI: 10.1071/WF13126

Daily values of McArthur Forest Fire Danger Index were generated at ~10-km resolution over Tasmania, Australia, from six dynamically downscaled CMIP3 climate models for 1961–2100, using a high (A2) emissions scenario. Multi-model mean fire danger validated well against observations for 2002–2012, with 99th percentile fire dangers having the same distribution and largely similar values to those observed over the same time. Model projections showed a broad increase in fire danger across Tasmania, but with substantial regional variation – the increase was smaller in western Tasmania (district mean cumulative fire danger increasing at 1.07 per year) compared with parts of the east (1.79 per year), for example. There was also noticeable seasonal variation, with little change occurring in autumn, but a steady increase in area subject to springtime 99th percentile fire danger from 6% in 1961–1980 to 21% by 2081–2100, again consistent with observations. In general, annually accumulated fire danger behaved similarly. Regional mean sea level pressure patterns resembled observed patterns often associated with days of dangerous fire weather. Days of elevated fire danger displaying these patterns increased in frequency during the simulated twenty-first century: in south-east Tasmania, for example, the number of such events detected rose from 101 (across all models) in 1961–1980 to 169 by 2081–2100. Correspondence of model output with observations and the regional detail available suggest that these dynamically downscaled model data are useful projections of future fire danger for landscape managers and the community.