Over half of Borneo is covered by tropical rainforest. This forest has an important role to play within the carbon cycle and the mitigation of climate change. However, it is also vulnerable to changes in climate through fluctuations in temperature and rainfall patterns.
Most trees in rainforests are not well adapted to withstand forest fires. The humidity of the climate and the dense canopy mean that the ground is usually damp and not suitable for combustion. This lack of natural adaptation means that, for example, many trees have relatively thin bark in comparison to the thicker bark of trees more used to experiencing natural forest fires.
Many forest fires across South East Asia are caused by human activities, for a variety of reasons. However, the climatic changes associated with an increase in global average temperature of 4 °C are projected to alter climatic conditions so that the forest fire danger risk across the region could increase.
It is the complex interaction between human ignition of fires and changes in the atmospheric conditions suitable for the perpetuation of fires that increases the risk of forest fires. In addition, any changes in the El Niño southern oscillation, which influence the amount of rainfall in the region, could potentially have a significant impact on the risk of forest fires in Borneo.
Forest fires are already a problem in the region, not just because of the destruction of the forest, but also as a result of the widespread pollution caused by the smoke plumes.
Fig 1. Difference between areas of high FFDI in 2080s and the 1961-90 baseline, i.e. the new areas moving into the high FFDI or above by the 2080s. The research for this study used the daily climate output directly from an ensemble of versions of the HadCM3 climate model 2.5° x 3.75° latitude-longitude resolution [Gordon et al., 2000; Collins et al., 2001] driven by a scenario of CO2 concentrations arising from the high A1FI emissions scenario [IPCC, 2000] (this scenario neglects feedbacks between the climate and the carbon cycle [Cox et al., 2000] and does not include dynamic vegetation [Betts et al., 2004]). The ensemble contained 17 model runs, and of these 13 showed a global average temperature rise of 4 °C or higher by the 2080s.
The combined output data from this subset of models was used to calculate the McArthur Forest Fire Danger Index Mark 5 (FFDI) (A. G. McArthur, Grassland fire danger meter Mk I, published as slide rule, 1973). It is a weather-based fire index derived empirically in southeast Australia, but subsequently used elsewhere [Golding and Betts, 2008]. The FFDI indicates the probability of a fire starting, rate of spread, intensity, and difficulty of suppression.
Fig 2. All areas of high FFDI in 2080s. Orange shading indicates where the FFDI was high in the 1961-90 baseline. Red shading indicates the regions that have crossed the high fire danger threshold by the 2080s. The index is divided into five fire danger ratings:
Low: 0-5, an index of 1 means that a fire will not burn, or burn so slowly that control presents little difficulty.
Very high: 24-50.
Extreme: 50-100, an index of 100 means that fires will burn so fast and hot that control is virtually impossible.
For the purposes of the four degree poster and Googe Earth layer, the 'high' fire danger category was selected as a threshold.
As a purely meteorological measure, it does not take account of the availability of fuel. However, areas highlighted as crossing the high fire danger threshold are currently vegetated.
Details of the methodology applied in this study: Golding, N., and R. Betts (2008), Fire risk in Amazonia due to climate change in the HadCM3 climate model: Potential interactions with deforestation, Global Biogeochem. Cycles, 22, GB4007, doi:10.1029/2007GB003166
Betts R.A., Cox P.M., Collins M., Harris P.P., Huntingford C. and Jones C.D., 2004, The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming, Theoretical and Applied Climatology, 78(1-3), 157-175.
Collins M., Tett S.F.B. and Cooper C., 2001, The internal climate variability of HadCM3, a version of the Hadley Centre coupled model without flux adjustments, Climate Dynamics, 17(1), 61-81.
Cook, K.H. & E.K. Vizy, 2007: Effects of Twenty-First-Century Climate Change on the Amazon Rain Forest, Journal of Climate, 21, 542-560.
Cox P.M., Betts R.A., Jones C.D., Spall S.A. and Totterdell I.J., 2000, Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model, Nature, 408, 184-187, doi:10.1038/35041539.
Cruz, R.V., H. Harasawa, M. Lal, S. Wu, Y. Anokhin, B. Punsalmaa, Y. Honda, M. Jafari, C. Li and N. Huu Ninh, 2007: Asia. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani, J.P., Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 469-506.
Golding, N.,and R. Betts, 2008: Fire risk in Amazonia due to climate change in the HadCM3 climate model: Potential interactions with deforestation. Global Biogeochem. Cycles,22, GB4007, doi:10.1029/2007GB003166.
Gordon C., Cooper C., Senior C.A., Banks H., Gregory J.M., Johns T.C., Mitchell J.F.B. and Wood R.A., 2000, The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments, Climate Dynamics, 16(2-3), 147-168.
IPCC, 2000, Land Use, Land-use Change, and Forestry. A Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 377 pp.
Klingaman, N.P., J. Butke, D.J. Leathers, K.R. Brinson & E. Nickl, 2008: Mesoscale Simulations of the Land Surface Effects of Historical Logging in a Moist Continental Regime, J. Applied Met and Clim., 47, 2166-2182.
Murdiyarso, D., M.Widodo and D.Suyamto, 2002: Fire risks in forest carbon project in Indonesia. J. Sci. in China, 45, Suppl. 65-74.
World Bank, 2008