1. Estimating climate variability over the next 1-25 years Dr Scott Power Dr Scott Power IOCI, August 2005 IOCI, August 2005

2. Using history as a guide (for 2006-2024) 1911-1974 1975-2001 Data: courtesy WA Water Corp

3. Can we use climate models to provide better PDFs?

4. Australian rainfall v. NINO4 SST in BMRC Climate Model

5. Models + data provide climate predictions for 6- 12 months ahead. They exhibit some skill in predicting some things.

6. Using initial data can change PDFs (Probability Density Functions) if there is predictability Data: Courtesy Samoa Meteorology Division A prediction as a change in a PDF

7. Can we predict beyond 2006 years? BMRC CGCM ( Power et al. 1998) BMRC CGCM ( Power et al. 1998)  MOM OGCM - Pacanowski et al. 1991  L25, 2 deg by (0.5, 6 deg)  hybrid mixing (ml, Ri); see Power et al. 1995  thermodynamic sea-ice  R21 L17 “unified” AGCM - Colman (2000)  Colman 2000  spectral, Rotstayn (1999) prognostic clouds; Tiedtke (1989) convection; GW drag (Palmer et al. 1986); McAvaney & Hess (1996) BL scheme  Q, Sf flux adjusted

8. Climate models suggest that ENSO predictability is very limited beyond 1-2 years Chaos limits predictability Sensitivity of NINO4 index to small initial nudges NINO4 Time (Years 1 to 4)) BMRC CGCM (Power et al. 1998)

9. Predictability beyond 2 years is present, e.g. o ff-equatorial, deep (310m) Pacific Ocean Deep Ocean Temperature

10. Off-Equatorial, Deep Pacific Ocean - highly predictable Exhibits predictability

11. Thermohaline Circulation Power et al. (2005, in press)

12. Kick-starting forecasts with data Sea-level from satellite Subsurface Ocean Temperature Winds from satellite Courtesy Neville Smith, BMRC XBTs & moored instruments

13. IPCC model output courtesy Pandora Hope, BMRC A big step forward, but approach neglects information about initial state of climate system

14. Estimating future PDFs Approach will borrow from Approach will borrow from 1)seasonal prediction e.g. initialisation, ensembles 2)climate change projections e.g. scenarios for future CO2 emissions 3)strategic research on decadal predictability Challenging, strategic, resource intensive Challenging, strategic, resource intensive Improve models, secure obs networks Improve models, secure obs networks Requires closer collaboration between CSIRO, Bureau Requires closer collaboration between CSIRO, Bureau ACCESS timely (& exciting possibility) ACCESS timely (& exciting possibility)

16. Seamless prediction “Increasingly, decade- and century-long climate projection will become an initial-value problem requiring knowledge of the current observed state of the atmosphere, the oceans, cryosphere, and land surface to produce the best climate projections as well as state-of-the-art decadal and interannual predictions” (WCRP, 2005)

17. ACCESS Australian Climate Community Earth System Simulator Australian Climate Community Earth System Simulator  New initiative in planning stages  Bureau, CSIRO, AGO  Universities, other agencies (federal and state)

18. Thermohaline Circulation

19. Variability in model’s conveyor belt Variability in model’s Southern Ocean Temperature

20. Using initial data can change PDFs (Probability Density Functions) if there is predictability Data Courtesy Samoa Meteorology Division A prediction as a change in the PDF

21. Decadal changes in southern Indian Ocean linked with Africa

22. Decadal changes in Southern Indian Ocean linked with Australia (in Model) Research Only! Research Only!

23. Courtesy: J Arblaster (NCAR/BMRC)

24. Argo floats supply temperature, salinity, pressure, velocity information - a revolution in data acquisition Courtesy Howard Freeland, Institute of Ocean Sciences, CANADA

25. Caveat: Decadal predictability arising from Initial Conditions might be substantial in some things (e.g. deep ocean) but low in variables of more significance to humans (e.g. rainfall over land) Strategic research in this area continues

26. Provide realistic local information for Impact Studies using coarse information from Global Climate Models Statistical Downscaling Techniques: From BoM booklet: “The greenhouse effect and climate change”, 2004. Courtesy Bertrand Timbal, BMRC

27. Coordinated Observation and Prediction of the Earth System, COPES Aim: To facilitate analysis and prediction of Earth system variability and change for use in an increasing range of practical applications of direct relevance, benefit and value to society

28. Conveyor belt variability appears to precede (by 4 years) SST & possibly some Africa/Australia variability in BMRC CGCM

29. Courtesy CSIRO Climate Change Projections can help

30. Estimating future Approach will borrow from Approach will borrow from seasonal prediction (e.g. using data, ensembles) climate change projections (e.g. scenarios for future CO2 emissions) strategic research on decadal predictability Challenging, strategic, resource intensive Challenging, strategic, resource intensive Requires closer collaboration between CSIRO, Bureau & beyond – ACCESS Requires closer collaboration between CSIRO, Bureau & beyond – ACCESS Intermediate steps will be used, e.g. Intermediate steps will be used, e.g. selective/nudged climatologies use existing climate change projections strategic research on decadal prediction