Skip to main content

Advertisement

Log in

Simulation and prediction of the Southern Annular Mode and its influence on Australian intra-seasonal climate in POAMA

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

We assess the ability of the Predictive Ocean Atmosphere Model for Australia (POAMA) to simulate and predict the Southern Annular Mode (SAM) and its influence on Australian intra-seasonal climate using a 27-year hindcast dataset. The analysis consists of three stages: (1) prediction of the SAM, (2) simulation of SAM climate anomalies over Australia, and (3) prediction of Australian climate anomalies in association with the SAM. POAMA achieves skilful prediction of the SAM index for lead times out to about 2 weeks with little skill seen beyond 3 weeks when calculated over all hindcast start months; the inherent strong persistence of the SAM appears to be a key factor for its extended-range predictability in a dynamical forecast model. POAMA also simulates SAM climate anomalies over Australia reasonably well despite notable biases in its representation of the SAM to the south and east of the continent. The model reproduces Australian rainfall anomalies most effectively throughout June–November, and least effectively throughout March–May. Skilful prediction of the SAM index, together with realistic simulation of SAM climate anomalies over Australia, translates into more skilful forecasts of rainfall and maximum temperature at intra-seasonal timescales during austral winter and spring. When the SAM is strong in the initial conditions, there is higher skill in forecasting rainfall anomalies over eastern Australia and maximum temperature anomalies over most of the continent during June–November at lead times of 2–3 weeks, compared with when the SAM is weak. The SAM thus contributes to intra-seasonal prediction skill in the Australian region in POAMA.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Notes

  1. “Multi-week forecasts will help bridge the gap”. In: CliMag (Managing Climate Variability Newsletter), 18, December 2009. Available from the Grains Research and Development Corporation, Australia, grdc@grdc.com.au.

References

  • Alves O, Wang G, Zhong A, Smith N, Tzeitkin F, Warren G, Schiller A, Godfrey S, Meyers G (2003) POAMA: Bureau of Meteorology operational coupled model forecast system. In: Proceedings of national drought forum, Brisbane, April 2003, pp 49–56. Available from DPI Publications, Department of Primary Industries, GPO Box 46, Brisbane, QLD 4001, Australia

  • Anderson J, van den Dool H, Barnston A, Chen W, Stern W, Ploshay J (1999) Present-day capabilities of numerical and statistical models for atmospheric extratropical seasonal simulation and prediction. Bull Am Meteorol Soc 80:1349–1361

    Article  Google Scholar 

  • Barnes EA, Hartmann DL (2010) Dynamical feedbacks of the southern annular mode in winter and summer. J Atmos Sci 67:2320–2330

    Article  Google Scholar 

  • Boer GJ, Fourest S, Yu B (2001) The signature of the annular modes in the moisture budget. J Clim 14:3655–3665

    Article  Google Scholar 

  • Burgers G, Balmaseda MA, Vossepoel FC, Oldenborgh G, Leeuwen P (2002) Balanced ocean-data assimilation near the Equator. J Phys Ocean 32:2509–2519

    Article  Google Scholar 

  • Cai W, Watterson IG (2002) Modes of interannual variability of the southern hemisphere circulation simulated by the CSIRO climate model. J Clim 15:1159–1174

    Article  Google Scholar 

  • Colman R, Deschamps L, Naughton M, Rikus L, Sulaiman A, Puri K, Roff G, Sun Z, Embury G (2005) BMRC Atmospheric Model (BAM) version 3.0: comparison with mean climatology. BMRC Research Report no. 108. Bureau of Meteorology, Melbourne

    Google Scholar 

  • Fyfe JC (2003) Separating extratropical zonal wind variability and mean change. J Clim 16:863–874

    Article  Google Scholar 

  • Gillett NP, Kell TD, Jones PD (2006) Regional climate impacts of the southern annular mode. Geophys Res Lett 33:L23704. doi:10.1029/2006GL027721

    Article  Google Scholar 

  • Gong D, Wang S (1999) Definition of Antarctic oscillation index. Geophys Res Lett 26:459–462

    Article  Google Scholar 

  • Gottschalck J, Wheeler M, Weickmann K, Vitart F, Savage N, Lin H, Hendon H, Waliser D, Sperber K, Nakagawa M, Prestrelo C, Flatau M, Higgins W (2010) A framework for assessing operational Madden-Julian Oscillation forecasts: a CLIVAR MJO Working Group project. Bull Am Meteorol Soc 91:1247–1258

    Article  Google Scholar 

  • Hall A, Visbeck M (2002) Synchronous variability in the southern hemisphere atmosphere, sea ice, and ocean resulting from the annular mode. J Clim 15:3043–3057

    Article  Google Scholar 

  • Hartmann DL, Lo F (1999) Wave-driven zonal flow vacillation in the southern hemisphere. J Atmos Sci 55:1303–1315

    Article  Google Scholar 

  • Haylock MR, Peterson TC, Alves LM, Ambrizzi T, Anunciacao YMT, Baez J, Barros VR, Berlato MA, Bidegain M, Coronel G, Corradi V, Garcia VJ, Grimm AM, Karoly D, Marengo JA, Marino MB, Moncunill DF, Nechet D, Quintana J, Rebello E, Rusticucci M, Santos JL, Trebejo I, Vincent LA (2006) Trends in total and extreme South American rainfall in 1960–2000 and links with sea surface temperature. J Clim 19:1490–1512

    Article  Google Scholar 

  • Hendon HH, Liebmann B (1990) The intraseasonal (30–50 day) oscillation of the Australian summer monsoon. J Atmos Sci 47:2909–2924

    Article  Google Scholar 

  • Hendon HH, Thompson DWJ, Wheeler MC (2007) Australian rainfall and surface temperature variations associated with the southern hemisphere annular mode. J Clim 20:2452–2467

    Article  Google Scholar 

  • Hendon HH, Lim E, Wang G, Alves O, Hudson D (2009) Prospects for predicting two flavors of El Niño. Geophys Res Lett 36:L19793. doi:10.1029/2009GL040100

    Article  Google Scholar 

  • Hudson D, Alves O, Hendon HH, Wang G (2011a) The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST. Clim Dyn 36:1155–1171

    Article  Google Scholar 

  • Hudson D, Alves O, Hendon HH, Marshall AG (2011b) Bridging the gap between weather and seasonal forecasting: intraseasonal forecasting for Australia. Q J R Meteorol Soc 137:673–689

    Article  Google Scholar 

  • Jones DA, Weymouth G (1997) An Australian monthly rainfall dataset. Technical Report 70. Bureau of Meteorology, Melbourne

    Google Scholar 

  • Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds B, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471

    Article  Google Scholar 

  • Karoly DJ (1990) The role of transient eddies in the low-frequency zonal variations in the southern hemisphere circulation. Tellus 42A:41–50

    Google Scholar 

  • Kidson JW (1988) Indices of the southern hemisphere zonal wind. J Clim 1:183–194

    Article  Google Scholar 

  • Kidson JW, Watterson IG (1999) The structure and predictability of the “high-latitude mode” in the CSIRO9 general circulation model. J Atmos Sci 56:3859–3873

    Article  Google Scholar 

  • Kuroda Y, Kodera K (1998) Interannual variability in the troposphere and stratosphere and stratosphere of the southern hemisphere winter. J Geophys Res 103:13787–13799

    Article  Google Scholar 

  • Kushner PJ, Held IM, Delworth TL (2001) Southern hemisphere atmospheric circulation response to global warming. J Clim 14:2238–2249

    Article  Google Scholar 

  • L’Heureux ML, Thompson DWJ (2006) Observed relationships between the El Niño-Southern Oscillation and the extratropical zonal-mean circulation. J Clim 19:276–287

    Article  Google Scholar 

  • Lim E-P, Hendon HH, Hudson D, Wang G, Alves O (2009) Dynamical forecast of inter-El Niño variations of tropical SST and Australian spring rainfall. Mon Weather Rev 137:3796–3810

    Article  Google Scholar 

  • Lim E-P, Hendon HH, Anderson DLT, Charles A, Alves O (2011) Dynamical, statistical-dynamical and multi-model ensemble forecasts of Australian spring season rainfall. Mon Weather Rev 139:958–975

    Article  Google Scholar 

  • Lorenz DJ, Hartmann DL (2001) Eddy-zonal flow feedback in the southern hemisphere. J Atmos Sci 58:3312–3327

    Article  Google Scholar 

  • Manabe S, Holloway JL (1975) The seasonal variation of the hydrological cycle as simulated by a global model of the atmosphere. J Geophys Res 80:1617–1649

    Article  Google Scholar 

  • Marshall GJ (2003) Trends in the southern annular mode from observations and reanalyses. J Clim 16:4134–4143

    Article  Google Scholar 

  • Marshall AG, Hudson D, Wheeler MC, Hendon HH, Alves O (2011) Assessing the simulation and prediction of rainfall associated with the MJO in the POAMA seasonal forecast system. Clim Dyn. doi:10.1007/s00382-010-0948-2

  • Meinke H, Stone RC (2005) Seasonal and inter-annual climate forecasting: the new tool for increasing preparedness to climate variability and change in agricultural planning and operations. Clim Change 70:221–253

    Article  Google Scholar 

  • Meneghini B, Simmonds I, Smith IN (2007) Association between Australian rainfall and the southern annular mode. Int J Climatol 27:109–121

    Article  Google Scholar 

  • Mo KC, White GH (1985) Teleconnections in the southern hemisphere. Mon Weather Rev 113:22–37

    Article  Google Scholar 

  • Nordeng T-E (1994) Extended versions of the convective parameterization scheme at ECMWF and their impact upon the mean climate and transient activity of the model in the tropics. Research Department Technical Memorandum No. 206, ECMWF, Shinfield Park Reading RG2 9AX, UK

  • Oke PR, Schiller A, Griffin DA, Brassington GB (2005) Ensemble data assimilation for an eddy-resolving ocean model of the Australian region. Q J R Meteorol Soc 131:3301–3311

    Article  Google Scholar 

  • Rashid H, Hendon HH, Wheeler M, Alves O (2010) Prediction of the Madden-Julian Oscillation with the POAMA dynamical seasonal prediction system. Clim Dyn 36:649–661

    Google Scholar 

  • Reason CJC, Rouault M (2005) Links between Antarctic Oscillation and winter rainfall over western South Africa. Geophys Res Lett 32:L07705. doi:10.1029/2005GL022419

    Article  Google Scholar 

  • Renwick J, Thompson DWJ (2006) The southern annular mode and New Zealand climate. Water Atmos 14:24–25

    Google Scholar 

  • Risbey JS, Pook MJ, McIntosh PC, Wheeler MC, Hendon HH (2009) On the remote drivers of rainfall variability in Australia. Mon Weather Rev 137:3233–3253

    Article  Google Scholar 

  • Robinson WA (1991) The dynamics of the zonal index in a simple model of the atmosphere. Tellus 43A:295–305

    Google Scholar 

  • Rogers JC, van Loon H (1982) Spatial variability of sea level pressure and 500 mb height anomalies over the southern hemisphere. Mon Weather Rev 110:1375–1392

    Article  Google Scholar 

  • Schiller A, Godfrey JS, McIntosh P, Meyers G (1997) A global ocean general circulation model climate variability studies. CSIRO Marine Research Report No. 227

  • Schiller A, Godfrey JS, McIntosh PC, Meyers G, Smith NR, Alves O, Wang G, Fiedler R (2002) A new version of the Australian community ocean model for seasonal climate prediction. CSIRO Marine Research Report No. 240

  • Sen Gupta A, England MH (2006) Coupled ocean–atmosphere–ice response to variations in the southern annular mode. J Clim 19:3677–3692

    Article  Google Scholar 

  • Sen Gupta A, England MH (2007) Coupled ocean–atmosphere feedback in the southern annular mode. J Clim 20:4457–4486

    Article  Google Scholar 

  • Silvestri GE, Vera CS (2003) Antarctic oscillation signal on precipitation anomalies over southeastern South America. Geophys Res Lett 30:2115. doi:10.1029/2003GL018277

    Article  Google Scholar 

  • Smith NR, Blomley JE, Meyers G (1991) A univariate statistical interpolation scheme for subsurface thermal analyses in the tropical oceans. Prog Oceanogr 28:219–256

    Article  Google Scholar 

  • Spillman C, Alves O (2009) Dynamical seasonal prediction of summer sea surface temperatures in the Great Barrier Reef. Coral Reefs 28:197–206

    Article  Google Scholar 

  • Stockdale TN (1997) Coupled ocean–atmosphere forecasts in the presence of climate drift. Mon Weather Rev 125:809–818

    Article  Google Scholar 

  • Thompson DWJ, Wallace JM (1998) The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys Res Lett 25:1297–1300

    Article  Google Scholar 

  • Thompson DWJ, Wallace JM (2000) Annular modes in the extratropical circulation. Part I: month-to-month variability. J Clim 13:1000–1016

    Article  Google Scholar 

  • Tiedke M (1989) A comprehensive mass flux scheme for cumulus parameterisation in large-scale models. Mon Weather Rev 117:1779–1800

    Article  Google Scholar 

  • Toth Z, Peña M, Vintzileos A (2007) Bridging the gap between weather and climate forecasting: research priorities for intraseasonal prediction. Bull Am Meteorol Soc 88:1427–1429

    Article  Google Scholar 

  • Trenberth KE (1979) Interannual variability of the 500 mb zonal-mean flow in the southern hemisphere. Mon Weather Rev 107:1515–1524

    Article  Google Scholar 

  • Uppala SM, Kallberg PW, Simmons AJ, Andrae U, Da Costa Bechtold V, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131:2961–3012

    Article  Google Scholar 

  • Valcke S, Terray L, Piacentini A (2000) OASIS 2.4 Ocean Atmospheric Sea Ice Soil user’s guide, version 2.4. CERFACS technical report, CERFACS TR/CMGC/00-10, 85 pp

  • Vitart F (2004) Monthly forecasting at ECMWF. Mon Weather Rev 132:2761–2779

    Article  Google Scholar 

  • Vitart F, Molteni F (2010) Simulation of the Madden-Julian Oscillation and its teleconnections in the ECMWF forecast system. Q J R Meteorol Soc 136:842–855

    Article  Google Scholar 

  • Vitart F, Buizza R, Balmaseda MA, Balsamo G, Bidlot J-R, Bonet A, Fuentes M, Hofstadler A, Molteni F, Palmer TN (2008) The new VarEPS-monthly forecasting system: a first step towards seamless prediction. Q J R Meteorol Soc 134:1789–1799

    Article  Google Scholar 

  • Wang G, Alves O, Smith N (2005) BAM3.0 tropical surface flux simulation and its impact on SST drift in a coupled model. BMRC Research Report No. 107. Bureau of Meteorology, Melbourne

    Google Scholar 

  • Wang G, Alves O, Hudson D, Hendon HH, Liu G, Tseitkin F (2008) SST skill assessment from the new POAMA-1.5 System. BMRC Research Letters No. 8:2–6. Bureau of Meteorology, Melbourne

    Google Scholar 

  • Watterson IG (2000) Southern midlatitude zonal wind vacillation and its interaction with the ocean in GCM simulations. J Clim 13:562–578

    Article  Google Scholar 

  • Watterson IG (2001) Zonal wind vacillation and its interaction with the ocean: implications for interannual variability and predictability. J Geophys Res 106:23965–23975

    Article  Google Scholar 

  • Yang X, Chang EKM (2007) Eddy-zonal flow feedback in the southern hemisphere winter and summer. J Atmos Sci 64:3091–3112

    Article  Google Scholar 

  • Yang X-Y, Wang D, Wang J, Huang RX (2007) Connection between the decadal variability in the Southern Ocean circulation and the southern annular mode. Geophys Res Lett 34:L16604. doi:10.1029/2007GL030526

    Article  Google Scholar 

  • Zhao M, Hendon HH (2009) Representation and prediction of the Indian Ocean dipole in the POAMA seasonal forecast model. Q J R Meteorol Soc 135:337–352

    Article  Google Scholar 

  • Zhong A, Alves O, Hendon H, Rikus L (2006) On aspects of the mean climatology and tropical interannual variability in the BMRC Atmospheric Model (BAM 3.0). BMRC Research Report No. 121. Bureau of Meteorology, Melbourne

    Google Scholar 

  • Zhou T, Yu R (2004) Sea-surface temperature induced variability of the southern annular mode in an atmospheric general circulation model. Geophys Res Lett 31:L24206. doi:10.1029/2004GL021473

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Managing Climate Variability Program of Grains Research and Development Corporation. We would like to thank Drs. Eun-Pa Lim, James Risbey, Li Shi and Peter McIntosh for reviewing an earlier version of the manuscript and providing useful comments. Thanks also to Drs. Mike Pook, Jaclyn Brown and Gary Meyers for useful discussions throughout the course of this work, and to the two anonymous reviewers for suggested revisions to the manuscript. Robert Fawcett and Andrew Charles provided the NCC rainfall data used in this study. The NNR1 dataset was provided by the NOAA/OAR/ESRL PSD in Boulder, Colorado, USA, from their web site at http://www.esrl.noaa.gov/psd/. The ERA-40 data was provided by the ECMWF in Reading, UK, from their website at http://data.ecmwf.int/data/.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrew G. Marshall.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Marshall, A.G., Hudson, D., Wheeler, M.C. et al. Simulation and prediction of the Southern Annular Mode and its influence on Australian intra-seasonal climate in POAMA. Clim Dyn 38, 2483–2502 (2012). https://doi.org/10.1007/s00382-011-1140-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-011-1140-z

Keywords

Navigation