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Ian Smith May 21 2009

Current issues with climate change projections. Ian Smith May 21 2009. 14% of Australia. Over 2 million people. The Murray-Darling Basin. 1million sq. km. O’Reilly’s. Major river systems Murray River 2530 km Darling River 2740 km. Basin characteristics.

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Ian Smith May 21 2009

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  1. Current issues with climate change projections Ian Smith May 21 2009

  2. 14% of Australia Over 2 million people The Murray-Darling Basin 1million sq. km

  3. O’Reilly’s • Major river systems • Murray River 2530 km • Darling River 2740 km

  4. Basin characteristics

  5. Average yearly rainfall in the MDB

  6. River Murray Inflows “…an appalling start to 2009…lowest 3 months of water flows on record…rain in the northwest were not enough to offset climate extremes in the southern regions…extreme temperatures .. The correlation between inflows and rainfall is now broken…algal blooms…critical human needs not guaranteed…”

  7. Understanding observed changes in runoff Percent difference (1997-2006 relative to 1895-2006) Rainfall Runoff Rainfall

  8. January to March 2009 rainfall deciles

  9. April 2006 to March 2009 36-month rainfall deciles

  10. Matching observed trends Role of: GH gases ? Aerosols ? Ozone ? Land cover change ? Natural variability ? Other ? SUMMER AUTUMN

  11. Regional climate drivers Expansion of tropics Weaker trade winds Shift in the Sub-Tropical Ridge Weaker westerlies

  12. High-Resolution Climate Projections and Impacts

  13. Ranking GCMs Climate projections • Rankings based on simulations of present day climate • There are models which consistently perform relatively well, and also models which consistently underperform • Provides a basis for better weighting, if not excluding, some model results when forming projections • There is (but not always) evidence of clustering in the projected changes from better performing models

  14. Assessment of GCMs • Ranking of (AR4) GCM performance to improve of regional climate change projections and impacts. • There are models which consistently perform relatively well, and also models which consistently underperform • Provides a basis for better weighting, if not excluding, some model results when forming projections • There is (but not always) evidence of clustering in the projected changes from better performing models

  15. Relating local-scaleweather & climate to large-scaleatmospheric variables(modelled or observed)

  16. Getting from GCM coarse scale results (100 to 200 km**2)to catchment scales. 100km

  17. GCMs cannot represent regional scale features that drive local climate

  18. Solution 1: Statistical downscaling. WINDS (U,V) GEOPOTENTIAL HEIGHT (Z) RELATIVE HUMIDITY (RH) TEMPERATURE (T) Rainfall = f(T,RH,Z,U,….)

  19. Solution 2: Dynamical downscaling.

  20. Downscaling can be complicated…

  21. Integration of historical climate data with projection information Natural variability PDF for natural variability and model greenhouse signal uncertainty 2050 climate projection rainfall rainfall 1900 2008 2100 1900 2008 2100 Sample obs Currently We need

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