AFAC 2006 page 536. Climate-Change Impacts on fire-weather in SE Australia Kevin Hennessy, Principal Research Scientist, CSIRO

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1 AFAC 2006 page 536 Climate-Change Impacts on fire-weather in SE Australia Kevin Hennessy, Principal Research Scientist, CSIRO

2 AFAC 2006 page 537 Climate change impacts on fire-weather risk in south-east Australia Kevin Hennessy Climate Impacts & Risk Group CSIRO Marine and Atmospheric Research Aspendale, Vic, Australia AFAC conference 12 August

3 AFAC 2006 page 538 Outline Fire risk in Australia Impacts on fire weather risk by 2020 and 2050 Uncertainties and research priorities

4 AFAC 2006 page 539 Outline Fire risk in Australia Impacts on fire weather risk by 2020 and 2050 Uncertainties and research priorities

5 AFAC 2006 page 540 Average cost of extreme weather In Australia, 87% of economic losses due to natural disasters are caused by weather-related events From 1967 to 1999, these losses averaged $942 million per year (in 1999 dollars), mostly due to floods, severe storms and cyclones Losses due to fire averaged $77 million per year and accounted for most deaths and injuries State/Terr. Flood Severe Cyclones Earthquakes Bushfires Landslides Total storms NSW QLD NT VIC WA SA TAS ACT Total % total BTE Data (2001) from Bureau of Transport Economics (2001)

6 AFAC 2006 page 541 Fire impacts The Black Friday fires in Victoria (1939), the 1967 fires in Tasmania, and the Ash Wednesday fires in Victoria and South Australia (1983) have each killed more than 60 people From , there were 224 firerelated deaths, 4505 injuries and $2.475 billion in damages McMichael et al. (2003)

7 AFAC 2006 page 542 Insured losses from fire: Date Location Original cost* $m Feb 1967 Hobart TAS 14 Feb 1977 Western VIC 9 Feb 1980 Adelaide Hills SA 13 Feb 1983 VIC 138 Feb 1983 SA 38 Sep 1984 NSW 25 Feb 1987 Southern TAS 7 Jan 1990 VIC 10 Oct 1991 Central coast NSW 12 Jan 1994 Sydney NSW 59 Jan 1997 Ferny Creek VIC 10 Dec 1997 Sydney NSW 3 Dec 2001 Sydney NSW 69 Oct 2002 Sydney NSW 19 Jan 2003 Northeast VIC 12 Southeast NSW Jan 2003 Canberra ACT 342 Jan 2005 Eyre Peninsula SA 27 * cost at time of event, not adjusted for inflation

8 AFAC 2006 page 543 Top 20 insured losses from 1967 to Top 20 insured losses Insured loss in $millions Cyclone Larry $350 m Hailstorm Sydney Apr 1999 Earthquake Newcastle Dec 1989 Cyclone Darwin Dec 1974 Hailstorm Sydney March 1990 Bushfire Canberra Jan 2003 Cyclone Brisbane Jan 1974 Bushfires Vic SA Feb 1983 Hailstorm Brisbane Jan 1985 Hailstorm Sydney Jan t h 7t h Hail, wind, flood SE Aus Feb 2005 Hailstorm Sydney Oct 1986 Cyclone WA NT QLD March 1973 Cyclone Townsville Dec 1971 Floods NSW Nov 1984 Hailstorm Sydney Nov 1976 Floods/Hail Melbourne Dec 2003 Hailstorm Sydney Feb 1992 Hailstorm Armidale Sep 1996 Bushfire Hobart Feb 1967 Floods Sydney Apr 1974 Hail accounts for 34% of losses. Source:

9 AFAC 2006 page 544 Fire risk in Australia Fire risk is influenced by a number of factors including weather, fuels, ignition, terrain, land management and suppression The CSIRO-BoM study assesses potential changes to one of these factors, fire-weather risk, associated with climate change The most important weather variables are temperature, humidity, wind-speed and rainfall

10 AFAC 2006 page 545 Seasonal pattern of fire danger

11 AFAC 2006 page 546 Outline Fire risk in Australia Impacts on fire weather risk by 2020 and 2050 Uncertainties and research priorities

12 AFAC 2006 page 547 Report published in Feb

13 AFAC 2006 page 548 Greenhouse gas scenarios Since south-east Australia has become hotter and drier since 1950, it s likely that fire-weather risk has increased Fire-weather risk from is being reconstructed by the Bushfire CRC and BoM Warmer and drier conditions are expected to continue due to increases in greenhouse gases over the next century

14 AFAC 2006 page 549 Global warming: o C by 2020, o C by 2050

15 AFAC 2006 page 550 Simulated changes in mean and variability This study included simulated changes in the mean and variability of daily temperature, rainfall, humidity and wind-speed Changes in daily decile values for each calendar month were applied to observed daily data from Observed daily temperature and rainfall data were considered high quality Observed daily humidity data were acceptable at most sites Observed wind data were not homogenised, so there were some jumps and missing data

16 AFAC 2006 page 551 Impacts on fire weather risk in south-east Australia were assessed for 2020 and 2050 at 17 sites Site selection was limited by availability of data for all 4 variables

17 AFAC 2006 page 552 Climate change scenarios for 17 sites were generated using 2 CSIRO climate models Model selection criteria: good simulation of mean temperature, rainfall and MSLP; availability of daily data at fine resolution, e.g. 50 km Two climate change simulations were suitable: CCAM driven by the CSIRO Mark2 GCM, and CCAM driven by the CSIRO Mark3 GCM The mean warming is o C by 2020 and o C by 2050 CCAM Mark2: rainfall decreases except in autumn in northern Vic and southern NSW, humidity decreases in spring and summer and increases in autumn and winter, wind-speed decreases CCAM Mark3: rainfall decreases in spring-summer and increases in autumn-winter, humidity decreases, wind-speed increases

18 AFAC 2006 page 553 Fire danger indices McArthur Mark 5 Forest Fire Danger Index (FFDI; Noble et al,, 1980) is defined as: FFDI = 2exp(0.987logD T V H) where: H = relative humidity from 0-100% T = air temperature o C V = average wind-speed 10 metres above the ground, in metres per second D = drought factor in the range 0-10

19 AFAC 2006 page 554 Canberra FFDI

20 AFAC 2006 page 555 Canberra FFDI > 50 (Total fire ban) The average from is 2.2 days

21 AFAC 2006 page 556 Average no. of days with extreme forest fire danger in 2020 and 2050 Site Present CCAM (Mark2) CCAM (Mark3) 2020 low 2020 high 2050 low 2050 high 2020 low 2020 high 2050 low 2050 high Canberra Bourke Cabramurra Cobar Coffs Harbour Nowra Richmond Sydney Wagga Williamtown Bendigo Laverton Melbourne Mildura Sale Hobart Launceston The frequency of extreme FFDI days generally increases 10-40% by 2020, and % by 2050 (no change in Tas)

22 AFAC 2006 page 557 Average no. of days with very high or extreme forest fire danger in 2020 and 2050 Site Present CCAM (Mark2) CCAM (Mark3) 2020 low 2020 high 2050 low 2050 high 2020 low 2020 high 2050 low 2050 high Canberra Bourke Cabramurra Cobar Coffs Harbour Nowra Richmond Sydney Wagga Williamtown Bendigo Laverton Melbourne Mildura Sale Hobart Launceston The combined frequencies of very high and extreme FFDI generally increase 4-25% by 2020, and 15-70% by 2050

23 AFAC 2006 page 558 Monthly-average forest fire danger index for Melbourne in 2020 and 2050 In 2020 and 2050, the curves move upward, indicating higher fire danger, particularly in spring, summer and autumn. Periods suitable for prescribed burning are likely to move toward winter

24 AFAC 2006 page 559 Fire danger indices The McArthur Mark 4 Grassland Fire Danger Index (GFDI; Purton, 1982) is defined as: GFDI=10 x where x = [ log 10 (Q) (100-C) T V RH] and Q is fuel quantity (t/ha) C is curing factor (0-100%) T is temperature (Celsius) V is wind speed (km/hr) RH is relative humidity (%) [we assume a standard 4.5 t/ha] [we assume 100% fully cured]

25 AFAC 2006 page 560 Days with very high or extreme grass fire danger in 2020 and 2050 Site Present CCAM (Mark2) CCAM (Mark3) 2020 low 2020 high 2050 low 2050 high 2020 low 2020 high 2050 low 2050 high Canberra Bourke Cabramurra Cobar Coffs Harbour Nowra Richmond Sydney Wagga Williamtown Bendigo Laverton Melbourne Mildura Sale Hobart Launceston The combined frequencies of very high and extreme GFDI generally increase 0-20% by 2020, and 5-40% by 2050

26 AFAC 2006 page 561 Outline Fire risk in Australia Impacts on fire weather risk by 2020 and 2050 Uncertainties and research priorities

27 AFAC 2006 page 562 Uncertainties Quality of observed daily wind and humidity data at most sites in Australia The effect of scenarios based on other climate models Assessment of year-to-year variability in FFDI and GFDI, including extremes Changes in ignition (natural and anthropogenic) Changes in fuel load, allowing for carbon dioxide fertilization on vegetation Potential impacts on biodiversity, water yield and quality from fire affected catchments, forestry, greenhouse gas emissions, emergency management and insurance.

28 AFAC 2006 page 563 Research priorities Testing and rehabilitation of observed humidity and wind data (supported by Bushfire CRC and BoM) Creation of regional climate change scenarios from other models (up to 23 available) Fine scale fire modelling that captures vegetation and terrain features and fire management, e.g. using FIRESCAPE (proposed for Sydney basin) Hydrological and ecological modelling to assess impacts on water and biodiversity Using satellite remote sensing to monitor the extent and nature of fire, recovery of vegetation after fire, and greenhouse gas emissions from fire (workshop on 5-9 June in Canberra)