1. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology www.cawcr.gov.au Subseasonal prediction of extreme heat over Australia Debbie Hudson Andrew Marshall, Chris White, Oscar Alves, Harry Hendon, Matthew Wheeler, Griff Young S2S Conference 10-13 February 2014

2. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Motivation Increasing demand for subseasonal forecast guidance in Australia Large-scale impacts of heat extremes e.g. health, agriculture, infrastructure Trend towards more frequent and intense heat waves is projected to continue Recent record-breaking Australian heat waves, e.g. Summer 2013 (4 Jan) Spring 2009 (August)Summer 2009 (7 Feb) Summer 2014 (13-17 Jan)

3. January 2014 heatwave Health Bushfires Infrastructure Agriculture http://www.abc.net.au/news/2014-01-13/grape-growers-fear- heatwave-will-destroy-crops/5197208 http://www.abc.net.au/news/2014-01-16/bushfire-threat-as- australia-south-east-suffers-heatwave/5204250 http://smh.drive.com.au/roads-and- traffic/heatwave-likely-cause-of- large-crack-on-west-gate-bridge- 20140120-314w4.html http://www.abc.net.au/news/2014-01-15/fire-crews-on-alert-as- south-east-australia-sizzles-in-heatwave/5200424 http://www.theage.com.au/comment /more-power-to-the-people-as- heatwave-hits-20140116-30xir.html http://www.theage.com.au/victoria/anger-over-spike-in- deaths-during-record-victorian-heatwave-20140126- 31gxb.html http://www.sbs.com.au/news/article/201 4/01/15/heatwave-conditions-prompt- health-warning http://www.dailymail.co.uk/news/article-2539626/Widespread- heatwave-causes-bushfires-court-chaos-Australian-Open.html

4. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Subseasonal forecasting using POAMA POAMA Seasonal forecast Weather forecast Real-time: ensemble of 33 forecasts updated twice-weekly Hindcast set: 1981-2010 Ensemble (n=33) 3x every month (1 st, 11 th, 21 st ) Forecasts out to 9-months Data Assimilation Atmos/Land IC Ocean IC Coupled climate model Atmospheric Model BAM T47L17 Ocean Model ACOM2 (lat 0.5~1.5º; lon 2º; 25 lvls) 3hr OASIS Coupler Ensemble of forecasts Coupled breeding method produces perturbations for burst ensemble

5. IOD Indian Ocean Dipole MJO Madden Julian Oscillation OLR’ ENSO El Niño Southern Oscillation Blocking (split-flow) STR high (Tasman) U500 & MSLP’ SAM Southern Annular Mode MSLP EOF1 Capturing the teleconnection: large-scale drivers and heat extremes Marshall, Hudson et al. 2013 Clim Dyn White, Hudson et al. 2013 Clim Dyn

6. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Increased chance of heat extremes during El Niño POAMA: using weeks 2 and 3 of the forecast Heat extreme: weekly-mean Tmax anomaly in highest decile (above 90 th percentile) Capturing the teleconnection: ENSO Increased probability of extreme heat (observations) Probability of weekly mean Tmax exceeding the 90 th percentile, expressed as ratio to the mean probability

7. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Chance of heat extremes during negative SAM Capturing the teleconnection: SAM (-ve SAM: Equatorward shift of the mid-latitude westerly wind belt) Probability of weekly mean Tmax exceeding the 90 th percentile, expressed as ratio to the mean probability

8. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Capturing the teleconnection: MJO Examples: SON, phase 3 DJF, phase 8 OBS extreme heat prob. OBS rain prob. (Wheeler et al. 2009) POAMA extreme heat prob.

9. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Chance of heat extremes with a persistent high in the Tasman Capturing the teleconnection: persistent STR Tasman High Probability of weekly mean Tmax exceeding the 90 th percentile, expressed as ratio to the mean probability U500 & MSLP’

10. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Forecast skill: Windows of forecast opportunity associated with ENSO Skill when ENSO is strong Skill when ENSO is weak/neutral Skill better than for random forecasts Skill (SEDI score) for forecasting extreme heat Tmax above the upper decile in JJA in weeks 2 and 3 of the forecast Symmetric Extremal Dependence Index (SEDI; Ferro and Stephenson, 2011)

11. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Forecast skill: Windows of forecast opportunity associated with the SAM Skill when negative SAM Skill when SAM is weak/neutral Skill (SEDI score) for forecasting extreme heat Tmax above the upper decile in weeks 2 and 3 of the forecast Skill better than for random forecasts SON DJF Teleconnection

12. Forecast skill: Windows of forecast opportunity associated with the MJO Skill (SEDI score) for forecasting extreme heat Tmax above the upper decile in weeks 2 and 3 of the forecast JJA SON Skill when MJO phase 2 Skill when MJO is weak Teleconnection

13. Overall forecast skill ROC area: Tmax in upper quintile Fortnight 1 (week1+2) Fortnight 1.5 (week2+3) Fortnight 2 (week3+4) DJF MAM JJA SON Fort 1 SON Fort 2 SON

14. Heat extremes case studies (Hudson et al 2014, in prep) 3-16 JAN 2013 OBSERVED FORECASTS for 3 Jan-16 Jan (initialised on the 27 th Dec i.e. weeks 2 and 3) SEP 2013 OBSERVED FORECASTS for 1 Sep-30 Sep (initialised on the 22 nd Aug) Tercile Upper quintile Tercile Upper quintile

15. Heat extremes case studies (Hudson et al 2014, in prep) Attribution of heat extremes: case studies Example: Observations 8-21 Nov 2009 phase 2 phase 3 MJO SAM index (inverted) Blocking index (inverted) Persistent Tasman High (STRH) MJO STRH Blocking (-ve) (i.e. no blocking) SAM (-ve) El Nino Teleconnection with extreme heat at this time of year

16. The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Summary  Increasing demand for subseasonal forecasts of heat extremes in Australia  Approach is to Understand the large-scale climatic processes (e.g. state of the SAM) that lead to episodes of extreme heat over Australia Examine the ability of POAMA to simulate the teleconnection and predict these large-scale processes Explore and define skill of POAMA for making predictions of heat extremes, including identifying windows of forecast opportunity Trialling different heat extreme indices for forecast products  POAMA shows promising skill in subseasonal prediction of heat extremes  There are windows of forecast opportunity related to state of the large-scale drivers. Skill is related to how well the model can predict the driver and capture the teleconnection.