Abstract
We present an assessment of the impact of future climate change on two key drivers of fire risk in Australia, fire weather and fuel load. Fire weather conditions are represented by the McArthur Forest Fire Danger Index (FFDI), calculated from a 12-member regional climate model ensemble. Fuel load is predicted from net primary production, simulated using a land surface model forced by the same regional climate model ensemble. Mean annual fine litter is projected to increase across all ensemble members, by 1.2 to 1.7 t ha−1 in temperate areas, 0.3 to 0.5 t ha−1 in grassland areas and 0.7 to 1.1 t ha−1 in subtropical areas. Ensemble changes in annual cumulative FFDI vary widely, from 57 to 550 in temperate areas, −186 to 1372 in grassland areas and −231 to 907 in subtropical areas. These results suggest that uncertainty in FFDI projections will be underestimated if only a single driving model is used. The largest increases in fuel load and fire weather are projected to occur in spring. Deriving fuel load from a land surface model may be possible in other regions, when this information is not directly available from climate model outputs.
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References
Abramowitz G, Leuning R, Clark M, Pitman AJ (2008) Evaluating the performance of land surface models. J Clim 21:5468–5481
Archibald S, Roy D, Van Wilgen B, Scholes R (2009) What limits fire? An examination of drivers of burnt area in southern Africa. Glob Chang Biol 15:613–630
Bedia J, Herrera S, Martín D, et al. (2013) Robust projections of Fire Weather Index in the Mediterranean using statistical downscaling. Clim Chang 120(1–2):229–247
Bishop CH, Abramowitz G (2013) Climate model dependence and the replicate Earth paradigm. Clim Dyn 41:885–900
Bradstock RA (2010) A biogeographic model of fire regimes in Australia: contemporary and future implications. Glob Ecol Biogeogr 19:145–158
Cai W, Cowan T, Raupach M (2009) Positive Indian Ocean dipole events precondition Southeast Australia bushfires. Geophys Res Lett 36:L19710
Clarke H, Smith PL, Pitman AJ (2011) Regional signatures of future fire weather over eastern Australia from global climate models. Int J Wildland Fire 20:550–562
Clarke H, Lucas C, Smith P (2012) Changes in Australian fire weather between 1973 and 2010. Int J Climatol 33:931–944
Clarke H, Evans JP, Pitman AJ (2013) Fire weather simulation skill by the weather research and forecasting (WRF) model over south-East Australia from 1985 to 2009. Int J Wildland Fire 22:739–756
CSIRO and Bureau of Meteorology (2015) Climate Change in Australia Information for Australia’s Natural Resource Management Regions: Technical Report. CSIRO and Bureau of Meteorology, Australia
Donohue RJ, Roderick ML, McVicar TR, Farquhar GD (2013) Impact of CO2 fertilization on maximum foliage cover across the globe’s warm, arid environments. Geophys Res Lett 40:3031–3035
Eliseev AV, Mokhov II, Chernokulsky AV (2014) An ensemble approach to simulate CO2 emissions from natural fires. Biogeosciences 11:3205–3223
Evans JP, McCabe MF (2010) Regional climate simulation over Australia’s Murray–darling basin: a multi-temporal assessment. J Geophys Res 115:D14114
Evans J, Ekström M, Ji F (2012) Evaluating the performance of a WRF physics ensemble over south-East Australia. Clim Dyn 39(6):1241–1258
Evans JP, Ji F, Lee C, et al. (2014) Design of a regional climate modeling projection ensemble experiment – NARCliM. Geosci Model Dev 7:621–629
Flannigan MD, Krawchuk MA, De Groot WJ, et al. (2009) Implications of changing climate for global wildland fire. Int J Wildland Fire 18:483–507
Fox-Hughes P, Harris RMB, Lee G, et al. (2014) Future fire danger climatology for Tasmania, Australia, using a dynamically downscaled regional climate model. Int J Wildland Fire 23:309–321
Friedlingstein P, Andrew RM, Rogelj J, et al. (2014) Persistent growth of CO2 emissions and implications for reaching climate targets. Nat Geosci 7(10):709–715
Gibson RK, Bradstock RA, Penman TD, et al. (2014) Changing dominance of key plant species across a Mediterranean climate region: implications for fuel types and future fire regimes. Plant Ecol 215:83–95
Griffiths D (1999) Improved formula for the drought factor in McArthur’s Forest fire danger meter. Aust For 62:202–206
Grose M, Fox-Hughes P, Harris RMB, Bindoff N (2014) Changes to the drivers of fire weather with a warming climate – a case study of southeast Tasmania. Climatic Change.
Hasson AEA, Mills GA, Timbal B, Walsh K (2009) Assessing the impact of climate change on extreme fire weather events over southeastern Australia. Clim Res 39:159–172
Haverd V, Cuntz M (2010) Soil-litter-Iso a one-dimensional model for coupled transport of heat, water and stable isotopes in soil with a litter layer and root extraction. J. Hydrology 388:438–455
Haverd V, Raupach MR, Briggs PR, et al. (2013) Multiple observation types reduce uncertainty in Australia’s terrestrial carbon and water cycles. Biogeosciences 10:2011–2040
Hutchinson MF, McIntyre S, Hobbs RJ, Stein JL, Garnett S, Kinloch J (2005) Integrating a global agro-climatic classification with bioregional boundaries in Australia. Glob Ecol Biogeogr 14:197–212
Jiang X, Rauscher S, Ringler T, et al. (2013) Projected future changes in vegetation in western North America in the twenty-first century. J Clim 26:3672–3687
Jones D, Wang W, Fawcett W (2009) High-quality spatial climate data-sets for Australia. Aust Meteorol Mag 58:233–248
Kala J, Decker M, Exbrayat J-F, et al. (2014) Influence of leaf area index prescriptions on simulations of heat, moisture, and carbon fluxes. J Hydrometeorol 15:489–503
Keetch JJ, Byram GM (1968) A drought index for forest fire control. Research Paper SE-38. USDA Forest Service, Ashville, NC
Kindermann GE, McAllum I, Fritz S, Obersteiner M (2008) A global forest growing stock, biomass and carbon map based on FAO statistics. Silva Fennica 42:387–396
King KJ, de Ligt RM, Cary GJ (2011) Fire and carbon dynamics under climate change in south eastern Australia: insights from FullCAM and FIRESCAPE modelling. Int J Wildland Fire 20:563–577
King KJ, Cary GJ, Gill AM, Moore AD (2012) Implications of changing climate and atmospheric CO2 for grassland fire in south-East Australia: insights using the GRAZPLAN grassland simulation model. Int J Wildland Fire 21:695–708
Kloster S, Mahowald N, Randerson J, Lawrence P (2012) The impacts of climate, land use, and demography on fires during the twenty-first century simulated by CLM–CN. Biogeosciences 9:509–525
Kumar SV, Peters-Lidard CD, Eastman JL, Tao W-K (2008) An integrated high- resolution hydrometeorological modeling testbed using LIS and WRF. Environ Model Softw 23:169–181
Lehtonen I, Ruosteenoja K, Venäläinen A, Gregow H (2014) The projected twenty-first century forest fire risk in Finland under different greenhouse gas scenarios. Boreal. Environ Res 19:127–139
Loepfe L, Martinez-Vilalta J, Piñol J (2012) Management alternatives to offset climate change effects on Mediterranean fire regimes in NE Spain. Clim Chang 115:693–707
Lucas C, Hennessy K, Mills G, Bathols J (2007) Bushfire weather in south-east Australia: recent trends and projected climate change impacts. Bushfire CRC and CSIRO, Melbourne
Luke R, McArthur A (1978) Bush fires in Australia. Australian Government Publishing Service, Canberra
Lung T, Dosio A, Becker W, et al. (2013) Assessing the influence of climate model uncertainty on EU-wide climate change impact indicators. Clim Chang 120:211–227
Luo L, Tang Y, Zhong S, et al. (2013) Will future climate favor more erratic wildfires in the western United States? J Appl Meteorol Climatol 52:2410–2417
Matthews E (1997) Global litter production, pools, and turnover times: estimates from measurement data and regression models. J Geophys Res 102:18771–18800
Matthews S, Sullivan AL, Watson P, Williams RJ (2012) Climate change, fuel and fire behaviour in a eucalypt forest. Glob Chang Biol 18:3212–3223
McArthur AG (1967) Fire behaviour in eucalypt forests. Commonwealth of Australia Forest and Timber Bureau Leaflet No. 107. Commonwealth of Australia, Canberra
Meehl GA, Covey C, Delworth T, et al. (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394
Mori AS, Johnson EA (2013) Assessing possible shifts in wildfire regimes under a changing climate in mountainous landscapes. For Ecol Manag 310:875–886
Noble IR, Barry GAV, Gill AM (1980) McArthur’s fire danger meters expressed as equations. Aust J Ecol 5:201–203
Norby RJ, Zak DR (2011) Ecological lessons from free-air CO2 enrichment (FACE) experiments. Annu Rev Ecol Evol Syst 42:181–203
Pechony O, Shindell DT (2010) Driving forces of global wildfires over the past millennium and the forthcoming century. Proc Natl Acad Sc USA 107(45):19167–19170
Penman TD, York A (2010) Climate and recent fire history affect fuel loads in eucalyptus forests: implications for fire management in a changing climate. For Ecol Manag 260:1791–1797
Price OF, Penman TD, Bradstock RA, Boer MM, Clarke H (2015) Biogeographical variation in the potential effectiveness of prescribed fire in South-Eastern Australia. J Biogeogr 42:2234–2245
Raupach MR, Haverd V, Briggs PR (2013) Sensitivities of the Australian terrestrial water and carbon balances to climate change and variability. Agric For Meteorol 182–183:277–291
Rienecker MM, Suarez MJ, Gelaro R, et al. (2011) MERRA - NASA's Modern-Era Retrospective Analysis for Research and Applications. J Clim 24:3624–3648
Roberts G, Wooster MJ, Lagoudakis E (2008) Annual and diurnal African biomass burning temporal dynamics. Biogeosci Discuss 5:3623–3663
Skamarock WC, Klemp JB, Dudhia J, et al. (2008) A Description of the Advanced Research WRF Version 3. NCAR Technical Note, NCAR, Boulder, CO, USA
Stern H, de Hoedt G, Ernst J (1999) Objective classification of Australian climates. Aust. Meteorol. Mag. 49:87–96
Thomas PB, Watson PJ, Bradstock RA, et al. (2014) Modelling surface fine fuel dynamics across climate gradients in eucalypt forests of South-Eastern Australia. Ecography 37:1–11
van Wagner CE (1987) Development and Structure of the Canadian Forest Fire Weather Index System. Technical Report 35. Canadian Forestry Service, Ottawa, ON
Wang YP, Law RM, Pak B (2010) A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere. Biogeosciences 7:2261–2282
Wang YP, Kowalczyk E, Leuning R, et al. (2011) Diagnosing errors in a land surface model (CABLE) in the time and frequency domains. J Geophys Res 116:G01034
Williams AAJ, Karoly DJ, Tapper N (2001) The sensitivity of Australian fire danger to climate change. Clim Chang 49:11–191
Williamson GJ, Prior LD, Grose MR, et al. (2014) Projecting canopy cover change in Tasmanian eucalypt forests using dynamically downscaled regional climate models. Reg Environ Chang 14:1373–1386
Acknowledgments
This study was supported by the ARC Centre of Excellence for Climate System Science (CE110001028) and by the NCI National Facility at the Australian National University, Australia. Regional climate data have been provided by the NARCLiM project funded by NSW Government Office of Environment and Heritage, University of New South Wales Climate Change Research Centre, ACT Government Environment and Sustainable Development Directorate and other project partners. Jason Evans was funded by the ARC Future Fellowship FT110100576.
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An erratum to this article is available at http://dx.doi.org/10.1007/s10584-016-1823-x.
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ESM 1
Change from 1990 to 2009 to 2060–2079 for the GCMs considered, numbered by independence rank (from Evans et al. 2014). Models selected are MIROC3.2-medres (1), ECHAM5 (5), CCCM3.1 (9) and CSIRO-Mk3.0 (12). (GIF 234 kb)
ESM 2
Scatterplots of BIOS2 mean annual NPP and mean annual fine litter from the same year (left) and the next year (right), in each climate zone. (GIF 144 kb)
ESM 3
(DOCX 15 kb)
ESM 4
Change in mean annual fine litter from each ensemble member (GIF 402 kb)
ESM 5
Change in mean annual cumulative FFDI from each ensemble member (GIF 165 kb)
ESM 6
Present and future mean monthly fine litter (a-c) and FFDI (d-f) in temperate, grassland and subtropical climate zones. Unbroken line shows multimodel mean, dotted lines show ensemble minimum and maximum values. (GIF 369 kb)
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Clarke, H., Pitman, A.J., Kala, J. et al. An investigation of future fuel load and fire weather in Australia. Climatic Change 139, 591–605 (2016). https://doi.org/10.1007/s10584-016-1808-9
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DOI: https://doi.org/10.1007/s10584-016-1808-9