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Estimating climate variability over the next 1-25 years

Estimating climate variability over the next 1-25 years. Dr Scott Power IOCI, August 2005. Using history as a guide (for 2006-2024). 1911-1974 1975-2001. Data: courtesy WA Water Corp. Can we use climate models to provide better PDFs?. Australian rainfall v. NINO4 SST in BMRC Climate Model.

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Estimating climate variability over the next 1-25 years

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  1. Estimating climate variability over the next 1-25 years • Dr Scott Power • 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 A prediction as a change in a PDF Data: Courtesy Samoa Meteorology Division

  7. Can we predict beyond 2006 years? • 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 Sensitivity of NINO4 index to small initial nudges NINO4 Chaos limits predictability Time (Years 1 to 4)) BMRC CGCM (Power et al. 1998)

  9. Predictability beyond 2 years is present, e.g. off-equatorial, deep (310m) Pacific Ocean <……………. 100 years ………….….> Deep Ocean Temperature

  10. Off-Equatorial, Deep Pacific Ocean - highly predictable • <…………………….. 13 years …………...……….> Exhibits predictability

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

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

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

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

  15. 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)

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

  17. Thermohaline Circulation

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

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

  20. Decadal changes in southern Indian Ocean linked with Africa

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

  22. Courtesy: J Arblaster (NCAR/BMRC)

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

  24. 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

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

  26. 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

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

  28. Climate Change Projections can help Courtesy CSIRO

  29. Estimating future • 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 • Requires closer collaboration between CSIRO, Bureau & beyond – ACCESS • Intermediate steps will be used, e.g. selective/nudged climatologies use existing climate change projections strategic research on decadal prediction

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