Skip to main content

Advertisement

SpringerLink
Log in

Simulation and prediction of blocking in the Australian region and its influence on intra-seasonal rainfall in POAMA-2

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

We assess the depiction and prediction of blocking at 140°E and its impact on Australian intra-seasonal climate variability in the Bureau of Meteorology’s dynamical intra-seasonal/seasonal forecast model Predictive Ocean Atmosphere Model for Australia version 2 (POAMA-2). The model simulates well the strong seasonality of blocking but underestimates its strength and frequency increasingly with lead time, particularly after the first fortnight of the hindcast, in connection with the model’s drifting basic state. POAMA-2 reproduces well the large-scale structure of weekly-mean blocking anomalies and associated rainfall anomalies over Australia; the depiction of total blocking in POAMA-2 may be improved with the reduction of biases in the distribution of Indian Ocean rainfall via a tropical-extratropical wave teleconnection linking blocking activity at 140°E with tropical variability near Indonesia. POAMA-2 demonstrates the ability to skilfully predict the daily blocking index out to 16 days lead time for the ensemble mean hindcast, surpassing the average predictive skill of the individual hindcast members (5 days), the skill obtained from persistence of observed (2 days), and the decorrelation timescale of blocking (3 days). This skilful prediction of the blocking index, together with effective simulation of blocking rainfall anomalies, translates into higher skill in forecasting rainfall in weeks 2 and 3 over much of Australia when blocking is high at the initial time of the hindcast, compared to when the blocking index is small. POAMA-2 is thus capable of providing forecast skill for blocking rainfall on the intra-seasonal timescale to meet the needs of Australian farming communities, whose management practises often rely upon decisions being made a few weeks ahead.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

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

Similar content being viewed by others

Notes

  1. Available at ftp://ftp.cpc.ncep.noaa.gov/cwlinks/norm.daily.aao.index.b790101.current.ascii.

  2. Available at http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml.

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 JL (1993) The climatology of blocking in a numerical forecast model. J Clim 6:1041–1056

    Article  Google Scholar 

  • Charney JG, DeVore JG (1979) Multiple flow equilibria in the atmosphere and blocking. J Atmos Sci 36:1205–1216

    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) version3.0: comparison with mean climatology. BMRC Research Report no. 108, Bur. Met., Melbourne, Australia

  • Coughlan M (1983) A comparative climatology of blocking action in the two hemispheres. Aust Met Mag 31:3–13

    Google Scholar 

  • D’Andrea F, Tibaldi S, Blackburn M, Boer G, Déqué M, Dix MR, Dugas B, Ferranti L, Iwasaki T, Kitoh A, Pope V, Randall D, Roeckner E, Straus D, Stern W, Van den Dool H, Williamson D (1998) Northern Hemisphere atmospheric blocking as simulated by 15 atmospheric general circulation models in the period 1979–1988. Clim Dyn 14:385–407

    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 Amer Meteorol Soc 91:1247–1258

    Article  Google Scholar 

  • 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 39:445–459

    Article  Google Scholar 

  • Hopkins LC, Holland GJ (1997) Australian heavy-rain days and associated east coast cyclones: 1958–92. J Clim 10:621–635

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Hudson D, Marshall AG, Alves O (2011c) Intraseasonal forecasting of the 2009 summer and winter Australian heat waves using POAMA. Weather Forecast 26:257–279

    Article  Google Scholar 

  • Hudson D, Marshall AG, Yin Y, Alves O, Hendon HH (2013) Improving intraseasonal prediction with a new ensemble generation strategy. Mon Weather Rev. doi:10.1175/MWR-D-13-00059.1

  • Jones DA, Wang W, Fawcett R (2009) High-quality spatial climate data-sets for Australia. Aust Meteorol Oceanogr J 58:233–248

    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 (1989) Southern Hemisphere circulation features associated with El Nino-Southern Oscillation events. J Clim 2:1239–1251

    Article  Google Scholar 

  • Katzfey JJ, McInnes KL (1996) GCM simulations of eastern Australian cutoff lows. J Clim 9:2337–2355

    Article  Google Scholar 

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

    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 AG, Hudson D, Wheeler MC, Hendon HH, Alves O (2012a) Simulation and prediction of the Southern Annular Mode and its influence on Australian intra-seasonal climate in POAMA. Clim Dyn 38:2483–2502

    Article  Google Scholar 

  • Marshall AG, Hudson D, Wheeler MC, Hendon HH, Alves O (2012b) Evaluating key drivers of Australian intra-seasonal climate variability in POAMA-2: a progress report. CAWCR Res Lett 7:10–16

    Google Scholar 

  • Matsueda M, Mizuta R, Kusunoki S (2009) Future change in wintertime atmospheric blocking simulated using a 20-km-mesh atmospheric global circulation model. J Geophys Res 114:D12114. doi:10.1029/2009JD011919

    Article  Google Scholar 

  • McIntosh P, Pook M, Risbey J, Hope P, Wang G, Alves O (2008) Australia’s regional climate drivers. Tech Rep, Land and Water Australia, Canberra 48 pp

    Google Scholar 

  • 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 Chang 70:221–253

    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 Dept Technical Memorandum No. 206, ECMWF, Shinfield Park Reading RG2 9AX, UK

  • O’Kane TJ, Risbey JS, Frankze C, Horenko I, Monselesan DP (2012) Changes in the meta-stability of the mid-latitude Southern Hemisphere circulation and the utility of non-stationary cluster analysis and split flow blocking indices as diagnostic tools. J Atmos Sci. doi:10.1175/JAS-D-12-028.1

  • 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 

  • Petoukhov V, Rahmstorf S, Petri S, Schellnhuber HJ (2013) Quasiresonant amplification of planetary waves and recent Northern Hemisphere weather extremes. PNAS. doi:10.1073/pnas.1222000110

    Google Scholar 

  • Pezza AB, van Rensch P, Cai W (2012) Severe heat waves in Southern Australia: synoptic climatology and large scale connections. Clim Dyn 38:209–224

    Article  Google Scholar 

  • Pook MJ (1994) Atmospheric blocking in the Australasian region in the Southern Hemisphere winter. PhD thesis, University of Tasmania, 168 pp

  • Pook MJ, Gibson T (1999) Atmospheric blocking and storm tracks during SOP-1 of the FROST Project. Aust Meteor Mag 48:51–60

    Google Scholar 

  • Pook MJ, McIntosh PC, Meyers GA (2006) The synoptic decomposition of cool-season rainfall in the Southeastern Australian cropping region. J Appl Meteor Climatol 45:1156–1170

    Article  Google Scholar 

  • Pook MJ, Risbey J, McIntosh P (2010) East coast lows, atmospheric blocking and rainfall: a Tasmanian perspective. IOP Conf Ser Earth Environ Sci 11:012011. doi:10.1088/1755-1315/11/1/012011

    Article  Google Scholar 

  • Pook MJ, Risbey J, McIntosh P, Ummenhofer C, Marshall AG, Meyers GA (2013) The seasonal cycle of blocking and associated physical mechanisms in the Australian region and relationship with rainfall. Mon Weather Rev. doi:10.1175/MWR-D-13-00040.1

  • Qi L, Leslie LM, Zhao SX (1999) Cut-off low pressure systems over southern Australia: climatology and case study. Int J Climatol 19:1633–1649

    Article  Google Scholar 

  • Raphael MN (2004) A zonal wave 3 index for the Southern Hemisphere. Geophys Res Lett 31:L23212. doi:10.1029/2004GL020365

    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. doi:10.1007/s00382-010-0754-x

    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 

  • Scaife AA, Knight JR (2008) Ensemble simulations of the cold European winter of 2005–2006. Q J R Meteorol Soc 134:1647–1659

    Article  Google Scholar 

  • Scaife AA, Woollings T, Knight J, Martin G, Hinton T (2010) Atmospheric blocking and mean biases in climate models. J Clim 23:6143–6152

    Article  Google Scholar 

  • Scaife AA, Copsey D, Gordon C, Harris C, Hinton T, Keeley S, O’Neill A, Roberts M, Williams K (2011) Improved Atlantic winter blocking in a climate model. Geophys Res Lett 38:L23703. doi:10.1029/2011GL049573

    Article  Google Scholar 

  • Schalge B, Blender R, Fraedrich K (2011) Blocking detection based on synoptic filters. Adv Meteorol ID 717812:11 pp. doi:10.1155/2011/717812

    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

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

    Article  Google Scholar 

  • Tibaldi S, Molteni F (1990) On the operational predictability of blocking. Tellus 42A:343–365

    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, Mo KC (1985) Blocking in the Southern Hemisphere. Mon Wea Rev 113:3–21

    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

  • van Loon H (1956) Blocking action in the Southern Hemisphere: part 1. Notos 5:171–175

    Google Scholar 

  • van Loon H, Jenne RL (1972) The zonal harmonic standing waves in the Southern Hemisphere. J Geophys Res 77:992–1003

    Article  Google Scholar 

  • 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 6:863–881

    Article  Google Scholar 

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

    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, Bur. Met., Melbourne, Australia

  • Watson JS, Colucci SJ (2002) Evaluation of ensemble predictions of blocking in the NCEP global spectral model. Mon Wea Rev 130:3008–3021

    Article  Google Scholar 

  • Wiedenmann JM, Lupo AR, Mokhov II, Tikhonova EA (2002) The climatology of blocking anticyclones for the northern and southern hemispheres: block intensity as a diagnostic. J Clim 15:3459–3473

    Article  Google Scholar 

  • Woollings T, Charlton-Perez A, Ineson S, Marshall AG, Masato G (2010) Associations between stratospheric variability and tropospheric blocking. J Geophys Res 115:D06108. doi:10.1029/2009JD012742

    Google Scholar 

  • Yin Y, Alves O, Oke PR (2011) An ensemble ocean data assimilation system for seasonal prediction. Mon Weather Rev 139:786–808

    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, Bur. Met., Melbourne, Australia

  • Zidikheri M, Frederiksen J, O’Kane T (2007) Multiple equilibria and midlatitude atmospheric blocking: a re-examination. World Sci Lect Notes Complex Syst 6:59–86

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Managing Climate Variability Program of Grains Research and Development Corporation. Thanks to Drs. Peter McIntosh, James Risbey, Terry O’Kane, Kay Shelton, Meelis Zidikheri and Jorgen Frederiksen for useful discussions throughout the course of this work. The AWAP data were provided by the South Eastern Australian Climate Initiative (SEACI) in Australia, and the NNR1 data were provided by the NOAA/CIRES Climate Diagnostics Center in Boulder (USA).

Author information

Authors and Affiliations

  1. Centre for Australian Weather and Climate Research, Melbourne/Hobart, Australia

    A. G. Marshall, D. Hudson, H. H. Hendon, M. J. Pook, O. Alves & M. C. Wheeler

Authors
  1. A. G. Marshall
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D. Hudson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. H. H. Hendon
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. J. Pook
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. O. Alves
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. C. Wheeler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. G. Marshall.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Marshall, A.G., Hudson, D., Hendon, H.H. et al. Simulation and prediction of blocking in the Australian region and its influence on intra-seasonal rainfall in POAMA-2. Clim Dyn 42, 3271–3288 (2014). https://doi.org/10.1007/s00382-013-1974-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-013-1974-7

Keywords

Search

Navigation