Climate Dynamics

, Volume 40, Issue 7–8, pp 2035–2048 | Cite as

A regional response in mean westerly circulation and rainfall to projected climate warming over Tasmania, Australia

  • Michael R. Grose
  • Stuart P. Corney
  • Jack J. Katzfey
  • James C. Bennett
  • Gregory K. Holz
  • Christopher J. White
  • Nathaniel L. Bindoff


Coupled ocean–atmosphere general circulation models (GCMs) lack sufficient resolution to model the regional detail of changes to mean circulation and rainfall with projected climate warming. In this paper, changes in mean circulation and rainfall in GCMs are compared to those in a variable resolution regional climate model, the Conformal Cubic Atmospheric Model (CCAM), under a high greenhouse gas emissions scenario. The study site is Tasmania, Australia, which is positioned within the mid-latitude westerlies of the southern hemisphere. CCAM projects a different response in mean sea level pressure and mid-latitude westerly circulation to climate warming to the GCMs used as input, and shows greater regional detail of the boundaries between regions of increasing and decreasing rainfall. Changes in mean circulation dominate the mean rainfall response in western Tasmania, whereas changes to rainfall in the East Coast are less related to mean circulation changes. CCAM projects an amplification of the dominant westerly circulation over Tasmania and this amplifies the seasonal cycle of wet winters and dry summers in the west. There is a larger change in the strength than in the incidence of westerly circulation and rainfall events. We propose the regional climate model displays a more sensitive atmospheric response to the different rates of warming of land and sea than the GCMs as input. The regional variation in these results highlight the need for dynamical downscaling of coupled general circulation models to finely resolve the influence of mean circulation and boundaries between regions of projected increases and decreases in rainfall.


Climate change Mean circulation Southern hemisphere westerlies Surface warming Rainfall Regional climate model 



The authors would like to acknowledge J.L McGregor (CAWCR) for providing the CCAM model and assisting in running the simulations. Thanks to W.F Budd for advice and assistance in the development of the scientific approach. We thank the two anonymous referees for their considered and helpful comments. This work was supported by the Australian government’s Cooperative Research Centres Program through the Antarctic Climate and Ecosystems Cooperative Research Centre (ACE CRC). Climate Futures for Tasmania is possible with support through funding and research of a consortium of state and national partners. We acknowledge the modelling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support of this dataset is provided by the Office of Science, US Department of Energy.


  1. Allan RP, Soden BJ (2008) Atmospheric warming and the amplification of precipitation extremes. Science 321:1481–1484. doi:10.1126/science.1160787 CrossRefGoogle Scholar
  2. Allen MR, Ingram WJ (2002) Constraints on future changes in climate and the hydrological cycle. Nature 419:224–232CrossRefGoogle Scholar
  3. Bennett JC, Ling FLN, Post DA, Grose MR, Corney SP, Graham B, Holz GK, Katzfey JJ, Bindoff NL (2012) High-resolution projections of surface water availability for Tasmania, Australia. Hydrol Earth Syst Sci 16:1287–1303Google Scholar
  4. Berbery EH, Fox-Rabinovitz MS (2003) Multiscale diagnosis of the North American monsoon system using a variable-resolution GCM. J Clim 16:1929–1947CrossRefGoogle Scholar
  5. Boé J, Terray L (2007) A weather-type approach to analyzing winter precipitation in france: twentieth-century trends and the role of anthropogenic forcing. J Clim 21:3118–3133CrossRefGoogle Scholar
  6. Cai WJ, Whetton PH, Karoly DJ (2003) The response of the Antarctic Oscillation to increasing and stabilized atmospheric CO2. J Clim 16:1525–1538CrossRefGoogle Scholar
  7. Chiew FHS, Kirono DGC, Kent DM, Frost AJ, Charles SP et al (2010) Comparison of runoff modelled using rainfall from different downscaling methods for historical and future climates. J Hydrol 387:10–23CrossRefGoogle Scholar
  8. Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X et al (2007) Regional climate projections. In: Solomon S, Qin D, Manning M et al (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  9. Engelbrecht FA, McGregor JL, Engelbrecht CJ (2009) Dynamics of the conformal-cubic atmospheric model projected climate-change signal over southern Africa. Int J Climatol 29:1013–1033CrossRefGoogle Scholar
  10. Fox-Rabinovitz MS, Cote J, Deque M, Dugas B, McGregor JL (2006) Variable-resolution GCMs: stretched-grid model intercomparison project (SGMIP). J Geophys Res 111:D16104. doi:10.1029/2005JD006520 CrossRefGoogle Scholar
  11. Fox-Rabinovitz MS, Côté J, Dugas B, Déqué M, McGregor JL et al (2008) Stretched-grid model inter-comparison project: decadal regional climate simulations with enhanced variable and uniform-resolution GCMs. Meteor Atmos Phys 100:159–177CrossRefGoogle Scholar
  12. Fyfe JC, Saenko OA (2006) Simulated changes in the extratropical Southern hemisphere winds and currents. Geophys Res Lett 33:L06701CrossRefGoogle Scholar
  13. Fyfe JC, Boer GJ, Flato GM (1999) The arctic and antarctic oscillations and their projected changes under global warming. Geophys Res Lett 26:1601–1604CrossRefGoogle Scholar
  14. Gerber EP, Polvani LM, Ancukiewicz D (2008) Annular mode time scales in the intergovernmental panel on climate change fourth assessment report models. Geophys Res Lett 35:L22707CrossRefGoogle Scholar
  15. Grose MR, Barnes-Keoghan I, Corney SP, White CJ, Holz GK et al (2010) Climate futures for Tasmania: general climate impacts. Antarctic Climate and Ecosystems Cooperative research Centre, HobartGoogle Scholar
  16. Grose MR, Pook MJ, McIntosh PC, Risbey JS, Bindoff NL (2012) The simulation of cutoff lows in a regional climate model: reliability and future trends. Clim Dyn 38. doi:10.1007/s00382-012-1368-2
  17. Hegerl GC, Zwiers FW, Stott PA, Kharin VV (2004) Detectability of anthropogenic changes in annual temperature and precipitation extremes. J Clim 17:3683–3700CrossRefGoogle Scholar
  18. Jones DA, Wang W, Fawcett R (2009) High-quality spatial climate datasets for Australia. Aust Meteorol Oceanog J 58:233–248Google Scholar
  19. Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  20. Katzfey JJ, McInnes KL (1996) GCM simulations of eastern Australian cutoff lows. J Clim 9:2337–2355CrossRefGoogle Scholar
  21. Katzfey JJ, McGregor JL, Nguyen KC, Thatcher M (2009) Dynamical downscaling TECHNIQUES: Impacts on regional climate change signals. World IMACS/MODSIM Congress, Cairns, pp 2377–2383Google Scholar
  22. Kendon EJ, Rowell DP, Jones RG (2010) Mechanisms and reliability of future projected changes in daily precipitation. Clim Dyn 35:489–509CrossRefGoogle Scholar
  23. Kidston J, Gerber EP (2010) Intermodel variability of the poleward shift of the austral jet stream in the CMIP3 integrations linked to biases in 20th century climatologies. Geophys Res Lett 37:L09708. doi:10.1029/2010GL042873 Google Scholar
  24. Kirono DGC, Kent DM (2010) Assessment of rainfall and potential evaporation from global climate models and its implications for Australian regional drought projection. Int J Climatol 31:1295–1308CrossRefGoogle Scholar
  25. Kushner PJ, Held IM, Delworth TL (2001) Southern hemisphere atmospheric circulation response to global warming. J Clim 14:2238–2249CrossRefGoogle Scholar
  26. Lal M, McGregor JL, Nguyen KC (2008) Very high-resolution climate simulation over Fiji using a global variable-resolution model. Clim Dyn 30:293–305CrossRefGoogle Scholar
  27. Leduc M, Laprise R (2009) Regional climate model sensitivity to domain size. Clim Dyn 32:833–854CrossRefGoogle Scholar
  28. McGregor JL (2005) C-CAM: Geometric aspects and dynamical formulation. CSIRO Atmospheric Research Technical Paper 43Google Scholar
  29. McGregor JL, Dix MR (2008) An updated description of the conformal-cubic atmospheric model. In: Hamilton K, Ohfuchi W (eds) High resolution simulation of the atmosphere and ocean. Springer, Berlin, pp 51–76CrossRefGoogle Scholar
  30. Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT et al (2007a) Global climate projections. In: Solomon S, Qin D, Manning M et al (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  31. Meehl GA, Covey AC, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007b) The WCRP CMIP3 multi-model dataset: a new era in climate change research. Bull Am Met Soc 88:1383–1394CrossRefGoogle Scholar
  32. Meneghini B, Simmonds I, Smith IN (2007) Association between Australian rainfall and the southern annular mode. Int J Climatol 27:109–121CrossRefGoogle Scholar
  33. Nakićenović N, Swart R (2000) Special report on emissions scenarios. A special report of working group III of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  34. Nguyen KC, McGregor JL (2009) Modelling the Asian summer monsoon using CCAM. Clim Dyn 32:219–236CrossRefGoogle Scholar
  35. Nguyen KC, Katzfey JJ, McGregor JL (2011) Global 60 km simulations with CCAM: evaluation over the tropics. Clim Dyn. doi:10.1007/s00382-011-1197-8
  36. Pall P, Allen MR, Stone DA (2007) Testing the Clausius-Clapeyron constraint on changes in extreme precipitation under CO2 warming. Clim Dyn 28:351–363CrossRefGoogle Scholar
  37. Pook MJ, Risbey J, McIntosh P (2010) East coast lows, atmospheric blocking and rainfall: a Tasmanian perspective. IOP Conf Ser Earth Environ Sci 11:012011CrossRefGoogle Scholar
  38. Post DA, Chiew FHS, Teng J, Viney NR, Ling FLN et al (2012) A robust methodology for conducting large-scale assessments of current and future water availability and use: a case study in Tasmania, Australia. J Hydrol 412–413:233–245CrossRefGoogle Scholar
  39. Randall DA, Wood R, Bony S, Colman R, Fichefet T et al (2007) Climate models and their evaluation. In: Solomon S, Qin D, Manning M et al (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  40. Reynolds RW (1988) A real-time global sea surface temperature analysis. J Clim 1:75–86CrossRefGoogle Scholar
  41. Risbey JS, Pook MJ, McIntosh PC, Wheeler MC, Hendon HH (2009) On the remote drivers of rainfall variability in Australia. Mon Weath Rev 137:3233–3253CrossRefGoogle Scholar
  42. Scaife AA, Woollings T, Knight J, Martin G, Hinton T (2010) Atmospheric blocking and mean biases in climate models. J Clim 23:6143–6152CrossRefGoogle Scholar
  43. Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture-climate interactions in a changing climate: a review. Earth-Sci Rev 99:125–161CrossRefGoogle Scholar
  44. Simmonds I, Hope P (1998) Seasonal and regional responses to changes in Australian soil moisture conditions. Int J Climatol 10:1105–1139CrossRefGoogle Scholar
  45. Smith I, Chandler E (2009) Refining rainfall projections for the Murray Darling Basin of south-east Australia—the effect of sampling model results based on performance. Clim Change 102:377–393CrossRefGoogle Scholar
  46. Thatcher M, McGregor JL (2008) Using a scale-selective filter for dynamical downscaling with the conformal cubic atmospheric model. Mon Weather Rev 137:1742–1752CrossRefGoogle Scholar
  47. Thatcher M, McGregor JL (2011) A technique for dynamically downscaling daily-averaged GCM datasets using the conformal cubic atmospheric model. Mon Weath Rev 139:79–95CrossRefGoogle Scholar
  48. van Ulden AP, van Oldenborgh GJ (2006) Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for climate change in Central Europe. Atmos Chem Phys 6:863–881CrossRefGoogle Scholar
  49. Watterson IG (2008) Calculation of probability density functions for temperature and precipitation change under global warming. J Geophys Res Atmos 113:D12106CrossRefGoogle Scholar
  50. Watterson IG, McGregor JL, Nguyen KC (2008) Changes in extreme temperatures of Australasian summer simulated by CCAM under global warming, and the roles of winds and land-sea contrasts. Aust Meteorol Mag 57:195–212Google Scholar
  51. Whetton PH, Katzfey JJ, Hennessy KJ, Wu X, McGregor JL, Nguyen KC (2001) Developing scenarios of climate change for Southeastern Australia: an example using regional climate model output. Clim Res 16:181–201CrossRefGoogle Scholar
  52. Whetton PH, Macadam I, Bathols J, O’Grady J (2007) Assessment of the use of current climate patterns to evaluate regional enhanced greenhouse response patterns of climate models. Geophys Res Lett 34:L14701CrossRefGoogle Scholar
  53. Yin JH (2005) A consistent poleward shift of storm tracks in simulations of 21st century climate. Geophys Res Lett 32:L18701CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Michael R. Grose
    • 1
  • Stuart P. Corney
    • 1
  • Jack J. Katzfey
    • 2
  • James C. Bennett
    • 3
    • 4
  • Gregory K. Holz
    • 1
  • Christopher J. White
    • 1
    • 5
  • Nathaniel L. Bindoff
    • 1
    • 3
    • 6
  1. 1.Antarctic Climate and Ecosystems Cooperative Research Centre (ACE CRC)University of TasmaniaHobartAustralia
  2. 2.Centre for Australian Weather and Climate Research (CAWCR)CSIRO Marine and Atmospheric ResearchAspendaleAustralia
  3. 3.Institute of Marine and Antarctic Studies (IMAS)University of TasmaniaHobartAustralia
  4. 4.CSIRO Land and WaterHighett MelbourneAustralia
  5. 5.Centre for Australian Weather and Climate Research (CAWCR)Bureau of Meteorology, c/o CSIRO Marine and Atmospheric Research, Castray EsplanadeHobartAustralia
  6. 6.Centre for Australian Weather and Climate Research (CAWCR)CSIRO Marine and Atmospheric ResearchHobartAustralia

Personalised recommendations