1. Assessing trends in observed and modelled climate extremes over Australia in relation to future projections Extremes in a changing climate, KNMI, The Netherlands, 14 th -15 th May, 2008 Lisa Alexander, Julie Arblaster and Rob Smalley

2. Aims Given that changes in climate extremes have greater impact on society and ecosystems than changes in mean climate: 1.Can global climate models adequately reproduce observed climate extremes over Australia? 2.If so, how are these extremes projected to change in the future?

3. Can models reproduce mean change? Models capture most of the overall changes except for NW temperature precip

4. Extremes indices (Frich et al., 2002) Warm nights (%) Frost days (days) Extreme temperature range (°C) Heat wave duration (days) Heavy precipitation days (days) Consecutive dry days (days) Daily intensity (mm/day) Maximum 5-day precipitation (mm) Very heavy precipitation contribution (%)

5. Observations HadEX dataset (Alexander et al., 2006) –3.75 x 2.5 gridded fields calculated from daily high quality temperature (Trewin, 1999) and precipitation (Haylock & Nicholls, 2000) –One value per grid box, per year, per index –www.hadobs.org

6. Model data Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset archived at the Program for Climate Model Diagnosis and Intercomparison (PCMDI) in California –CCSM3 (1), PCM (4), GFDL-CM2.0 (3), GFDL-CM2.1 (3) –MIROC3.2_med (3), MIROC3.2_hi (1), MRI-CGCM2.3.2 (5) –CNRM-CM3 (1) –INM-CM3.0 (1) Total 22 runs Models interpolated onto HadEX grid and masked to observational grid points

7. Temperature extreme trends observations multi-model

8. Precipitation extreme trends observations multi-model

9. R10mmRX5dayR95pT Improvements in data coverage Source: Rob Smalley

10. Extremes timeseries comparison Warm nightsFrost daysExtreme temperature range Max 5-day precipHeavy precipitation days Heat waves Daily intensityConsecutive dry daysVery heavy precip contib Difference in definition Some over or underestimate of actual variable amount for some or all model runs All model runs capture trend and interannual variability well

11. Decadal trends 1957-1999 for Australia Individually most models get the correct sign of trend (except for CDD) 0.26 (-0.58/1.23)0.60 ±0.12Very heavy precipitation contribution 1.04 (-1.68/3.36)-0.14 ±0.15Consecutive dry days 0.02 (-0.06/0.13)0.04 ±0.02Simple daily intensity 0.32 (-1.37/2.32)0.42 ±0.33Maximum 5-day precipitation -0.06 (-0.79/0.89)0.28 ±0.06Heavy precipitation days 0.26 (-0.31/0.91)7.05 ±0.33Heat wave duration 0.04 (-0.29/0.31)-0.19 ±0.02Extreme temperature range -0.19 (-1.46/0.22)-0.89 ±0.07Frost days 1.15 (0.48/1.87)1.11 ±0.06Warm nights Multi-modelObsIndex

12. Measuring model trend uncertainty Warm nightsFrost daysExtreme temperature range Heavy precipitation daysMax 5-day precip Daily intensityConsecutive dry daysVery heavy precip contib Heat waves

13. Pattern similarity Warm nightsFrost daysExtreme temperature range Heat wavesHeavy precipitation daysMax 5-day precip Daily intensityConsecutive dry daysVery heavy precip contib

14. Verification using improved data coverage R10mm RX5day R95pT poor Pattern correlation with data using Taylor diagram. Climate models for 1980-1999 compared with observations O: cnrm, O: gfdl cm2.0, O: inmcm3.0, O: gfdl cm2.1, O: miroc3.2hi, O: miroc3.2med, O: pcm1, O: mri-cgcm2.3.2, O: ccsm 3.0 Other symbols indicate more than one model run for each model

15. Anthropogenic versus natural forcing Two models (CCSM/PCM) have output from different forcings Results show that some temperature extremes are inconsistent with natural-only forcings

16. Interim conclusions Trends in and interannual variability of warm nights are very well captured by all models Within uncertainty ranges the multi-model trends overlap with observations (except for heat wave duration because of differences in definition) However caution is required when interpreting some of the model projections

17. Low population growth, less fossil fuel use IPCC future emissions scenarios We use B1, A1B and A2 High population growth, intensive fossil fuel use

18. Timeseries 1870-2099

19. Future projections: 2080-2099 minus 1980-1999 Multi-model agreement across most of Australia for large significant increases in warm nights and heat waves Little agreement on the significance of projected changes in precipitation extremes

20. Changes scale with strength of emissions 1.420.520.80Very heavy precipitation contribution 1.190.584.11Consecutive dry days 1.090.761.01Simple daily intensity 1.490.610.3Maximum 5-day precipitation -0.540.790.17Heavy precipitation days 1.400.500.3Heat wave duration 2.140.58-0.53Extreme temperature range 1.150.860.45Frost days 1.110.650.86Warm nights A2/A1BB1/A1BAust/Global (A1B)Index

21. Conclusions (I) obs/model comparison Generally global climate models are able to simulate the magnitude of observed trends of climate extremes and interannual variability over Australia, particularly for temperature extremes BUT some indices are not well reproduced Very few models showed significant skill at reproducing the observed spatial pattern of trends Two models with output from different forcings showed that some changes in temperature indices were consistent with an anthropogenic response

22. Conclusions (II) future projections Multi-model agreement for substantial increases in warm nights and heatwaves and decreases in frosts projected by the end of the century irrespective of scenario used Much longer dry spells interspersed with periods of increased precipitation BUT much less inter-model agreement In general, the magnitude of changes in both temperature and precipitation indices were found to scale with strength of emissions But more work is required to improve both the observational coverage and the robustness of projections Alexander and Arblaster (2008), Int. J. Climatol. (in press)