Skip to main content

Advertisement

SpringerLink
Log in

The Madden–Julian oscillation in ECHAM4 coupled and uncoupled general circulation models

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

The Madden-Julian oscillation (MJO) dominates tropical variability on timescales of 30–70 days. During the boreal winter/spring, it is manifested as an eastward propagating disturbance, with a strong convective signature over the eastern hemisphere. The space–time structure of the MJO is analyzed using simulations with the ECHAM4 atmospheric general circulation model run with observed monthly mean sea-surface temperatures (SSTs), and coupled to three different ocean models. The coherence of the eastward propagation of MJO convection is sensitive to the ocean model to which ECHAM4 is coupled. For ECHAM4/OPYC and ECHO-G, models for which ~100 years of daily data is available, Monte Carlo sampling indicates that their metrics of eastward propagation are different at the 1% significance level. The flux-adjusted coupled simulations, ECHAM4/OPYC and ECHO-G, maintain a more realistic mean-state, and have a more realistic MJO simulation than the nonadjusted scale interaction experiment (SINTEX) coupled runs. The SINTEX model exhibits a cold bias in Indian Ocean and tropical West Pacific Ocean sea-surface temperature of ~0.5°C. This cold bias affects the distribution of time-mean convection over the tropical eastern hemisphere. Furthermore, the eastward propagation of MJO convection in this model is not as coherent as in the two models that used flux adjustment or when compared to an integration of ECHAM4 with prescribed observed SST. This result suggests that simulating a realistic basic state is at least as important as air–sea interaction for organizing the MJO. While all of the coupled models simulate the warm (cold) SST anomalies that precede (succeed) the MJO convection, the interaction of the components of the net surface heat flux that lead to these anomalies are different over the Indian Ocean. The ECHAM4/OPYC model in which the atmospheric model is run at a horizontal resolution of T42, has eastward propagating zonal wind anomalies and latent heat flux anomalies. However, the integrations with ECHO-G and SINTEX, which used T30 atmospheres, produce westward propagation of the latent heat flux anomalies, contrary to reanalysis. It is suggested that the differing ability of the models to represent the near-surface westerlies over the Indian Ocean is related to the different horizontal resolutions of the atmospheric model employed.

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
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  • AchutaRao K, Covey C, Doutriaux C, Fiorino M, Gleckler P, Phillips T, Sperber K, Taylor K (2004) An appraisal of coupled climate model simulations. In: Bader D (ed) UCRL-TR-202550, PCMDI, Lawrence Livermore National Laboratory, Livermore, CA

  • Fairall C, Bradley EF, Rogers DP, Edson JB, Young GS (1996) The TOGA COARE bulk flux algorithm. J Geophys Res 101:3747–3764

    Article  Google Scholar 

  • Ferranti L, Palmer TN, Molteni F, Klinker E (1990) Tropical-extratropical interaction associated with the 30–60 day oscillation and its impact on medium and extended range prediction. J Atmos Sci 47:2177–2199

    Article  Google Scholar 

  • Flatau M, Flatau PJ, Phoebus P, Niiler PP (1997) The feedback between equatorial convection and local radiative and evaporative processes: the implication for intraseasonal oscillations. J Atmos Sci 54:2373–2386

    Article  Google Scholar 

  • Gualdi S, Navarra A (1998) A study of the seasonal variability of the tropical intraseasonal oscillation. Global Atmos Ocean Syst 6:337–372

    Google Scholar 

  • Gualdi S, Navarra A, von Storch H (1997) Tropical intraseasonal oscillation appearing in operational analyses and in a family of general circulation models. J Atmos Sci 54:1185–1202

    Article  Google Scholar 

  • Gualdi S, Navarra A, Tinarelli G (1999) The interannual variability of the Madden–Julian oscillation in an ensemble of GCM simulations. Clim Dynam 15:643–658

    Article  Google Scholar 

  • Gualdi S, Guilyardi E, Navarra A, Masina S, Delecluse P (2003) The interannual variability in the tropical Indian Ocean as simulated by a CGCM. Clim Dynam 20:567–582. DOI 10.1007/s00382- 002-0295-z

    Google Scholar 

  • Guilyardi E, Madec G, Terray L (2001) The role of lateral ocean physics in the upper ocean thermal balance of a coupled ocean atmosphere GCM. Clim Dynam 17:589–599

    Article  Google Scholar 

  • Guilyardi E, Delecluse P, Gualdi S, Navarra A (2003) Mechanisms for ENSO phase change in a coupled GCM. J Clim 16:1141–1158

    Article  Google Scholar 

  • Hendon HH (2000) Impact of air–sea coupling on the Madden–Julian oscillation in a general circulation model. J Atmos Sci 57:3939–3952

    Article  Google Scholar 

  • Hendon HH, Salby ML (1994) The life cycle of the Madden–Julian oscillation. J Atmos Sci 51:2225–2237

    Article  Google Scholar 

  • Hendon HH, Zhang C, Glick JD (1999) Interannual variation of the Madden–Julian oscillation during Austral summer. J Clim 12:2538–2550

    Article  Google Scholar 

  • Higgins RW, Schemm J-KE, Shi W, Leetma A (2000) Extreme precipitation events in the western United States related to tropical forcing. J Clim 13:793–820

    Article  Google Scholar 

  • Inness PM, Slingo JM (2003) Simulation of the Madden–Julian oscillation in a coupled general circulation model. Part I: comparison with observations and an atmosphere-only GCM. J Clim 16:345–364

    Article  Google Scholar 

  • Inness PM, Slingo JM, Woolnough SJ, Neale RB, Pope VD (2001) Organization of tropical convection in a GCM with varying vertical resolution: implications for the simulation of the Madden–Julian oscillation. Clim Dynam 17:777–793

    Article  Google Scholar 

  • Inness PM, Slingo JM, Guilyardi E, Cole J (2003) Simulation of the Madden–Julian oscillation in a coupled general circulation model. Part II: the role of the basic state. J Clim 16:365–382

    Article  Google Scholar 

  • Jones C, Weare BC (1996) The role of low-level moisture convergence and ocean latent heat fluxes in the Madden and Julian oscillation. J Clim 9:3086–3140

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Kemball-Cook S, Wang B, Fu X (2002) Simulation of the intraseasonal oscillation in the ECHAM-4 model: the impact of coupling with an ocean model. J Atmos Sci 59:1433–1453

    Article  Google Scholar 

  • Legutke S, Maier-Reimer E (1999) Climatology of the HOPE-G global ocean general circulation model. Technical Report No. 21, German Climate Computer Centre (DKRZ), Hamburg, Germany, p 90

  • Legutke S, Voss R (1999) The Hamburg atmosphere-ocean coupled circulation model ECHO-G. Technical Report No. 18, German Climate Computer Centre (DKRZ), Hamburg, Germany, p 62

  • Liess S, Bengtsson L (2004) The intraseasonal oscillation in ECHAM4. Part II: sensitivity studies. Clim Dynam 22:671–688. DOI 10.1007/s00382-004-0407-z

    Google Scholar 

  • Liess S, Bengtsson L, Arpe K (2004) The intraseasonal oscillation in ECHAM4. Part I: coupled to a comprehensive ocean model. Clim Dynam 22:653–669. DOI 10.1007/s00382-004-0406-0

    Google Scholar 

  • Madden RA, Julian PR (1971) Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J Atmos Sci 28:702–708

    Article  Google Scholar 

  • Madden RA, Julian PR (1972) Description of global-scale circulation cells in the tropics with a 40–50 day period. J Atmos Sci 29:1109–1123

    Article  Google Scholar 

  • Madden RA, Julian PR (1994) Observations of the 40–50 day tropical oscillation—a review. Mon Weather Rev 122:814–837

    Article  Google Scholar 

  • Madec G, Delecluse P, Imbard M, Levy C (1998) OPA version 8.1 ocean general circulation model reference manuel. Technical Report Note 11, LODYC/IPSL, Paris, France, p 91

  • Maloney ED, Hartmann DL (1998) Frictional moisture convergence in a composite life cycle of the Madden–Julian oscillation. J Clim 11:2387–2403

    Article  Google Scholar 

  • Matthews AJ (2004) Atmospheric response to observed intraseasonal tropical sea surface temperature anomalies. Geophys Res Lett 13:L14107. DOI 10.1029/2004GL020474

    Google Scholar 

  • McPhaden M (1999) Genesis and the evolution of the 1997–98 El Niño. Science 283:950–954

    Article  PubMed  Google Scholar 

  • McPhaden M (2004) Evolution of the 2002/03 El Niño. Bull Amer Meteorol Soc 85:677–695

    Article  Google Scholar 

  • Min S-K, Legutke S, Hense A, Kwon W-T (2004) Climatology and internal variability in a 1000-year control simulation with the coupled climate model ECHO-G. Technical Report No. 2, Model and Data Group, Max Planck Institute for Meteorology, Hamburg, Germany, p 67

  • Mo KC, Higgins RW (1996) Large-scale atmospheric moisture transport as evaluated in the NCEP/NCAR and NASA/DAO reanalyses. J Clim 9:1531–1545

    Article  Google Scholar 

  • Mo KC, Higgins RW (1998) Tropical influences on California precipitation. J Clim 11:412–430

    Article  Google Scholar 

  • Murakami T (1988) Intraseasonal atmospheric teleconnection patterns during Northern Hemisphere winter. J Clim 1:117–131

    Article  Google Scholar 

  • Nordeng TE (1994) Extended versions of the convective parameterizations scheme at ECMWF and their impact on the mean and transient activity of the model in the tropics. ECMWF Tech. Memo. 206, ECMWF, Reading, UK, p 41

  • Oberhuber J (1993a) Simulation of the Atlantic circulation with a coupled sea ice-mixed layer-isopycnal general circulation model. Part I: model description. J Phys Oceanogr 22:808–829

    Article  Google Scholar 

  • Oberhuber J (1993b) The OPYC ocean general circulation model. Tech. Rep. No. 7, Deutsches Klimarechenzentrum GmbH, Hamburg, Germany, p 127

  • Pan HL, Wu WS (1994) Implementing a mass-flux convection parameterization package for the NMC medium-range forecast model. In: Proceedings of the 10th conference on numerical weather prediction, Portland/Oregon. American Meteorological Society, pp 96–98

  • Randall D, Khairoutdinov M, Arakawa A, Grabowski W (2003) Breaking the cloud parameterization deadlock. Bull Amer Meteorol Soc 84:1547–1564

    Article  Google Scholar 

  • Rayner NA, Parker DE, Frich P, Horton EB, Folland CK, Alexander LV (2000) SST and sea-ice fields for ERA-40. In: Proceedings of the 2nd WCRP international conference on reanalyses. Reading, August 1999, WCRP-109, WMO/TD-985, pp 18–21

  • Reynolds RW, Smith TM (1994) Improved global sea surface temperature analyses using optimum interpolation. J Clim 7:929–948

    Article  Google Scholar 

  • Roeckner E, Arpe K, Bengtsson L, Christoph M, Claussen M, Dumenil L, Esch M, Giorgetta M, Schlese U, Schulzweida U (1996) The atmospheric general circulation model ECHAM-4: model description and simulation of present-day climate. Rep. No. 218, Max Planck Institute for Meteorology, Hamburg, Germany, p 90

  • Shinoda T, Hendon HH (1998) Mixed layer modeling of intraseasonal variability in the tropical western Pacific and Indian oceans. J Clim 11:2668–2684

    Article  Google Scholar 

  • Shinoda T, Hendon HH, Glick J (1999) Intraseasonal surface fluxes in the tropical western Pacific and Indian Oceans from NCEP reanalyses. Mon Weather Rev 127:678–693

    Article  Google Scholar 

  • Slingo JM (1987) The development and verification of a cloud prediction scheme for the ECMWF model. Q J R Meteorol Soc 113:899–927

    Article  Google Scholar 

  • Slingo JM, Sperber KR, Boyle JS, Ceron J-P, Dix M, Dugas B, Ebisuzaki W, Fyfe J, Gregory D, Gueremy J-F, Hack J, Harzallah A, Inness P, Kitoh A, Lau WK-M, McAvaney B, Madden R, Matthews A, Palmer TN, Park C-K, Randall D, Renno N (1996) Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject. Clim Dynam 12:325–357

    Article  Google Scholar 

  • Slingo JM, Rowell DP, Sperber KR, Nortley F (1999) On the predictability of the interannual behaviour of the Madden–Julian oscillation and its relationship with El Niño. Q J R Meteorol Soc 125:583–609

    Article  Google Scholar 

  • Sperber KR (2003) Propagation and the vertical structure of the Madden–Julian oscillation. Mon Wea Rev 131:3018–3037

    Article  Google Scholar 

  • Sperber KR (2004a) Madden-Julian variability in NCAR CAM2.0 and CCSM2.0. Clim Dynam 23:259–278. DOI 10.1007/s00382-004-0447-4

    Google Scholar 

  • Sperber KR (2004b) The Madden–Julian oscillation. Chapter 6.4 in an appraisal of coupled climate model simulations. In: Bader D (ed) UCRL-TR-202550, PCMDI, Lawrence Livermore National Laboratory, Livermore, CA, pp 146–158

  • Sperber KR, Slingo JM, Inness PM, Lau WK-M (1997) On the maintenance and initiation of the intraseasonal oscillation in the NCEP/NCAR reanalysis and in the GLA and UKMO AMIP simulations. Clim Dynam 13:769–795

    Article  Google Scholar 

  • Stendel M, Arpe K (1997) Evaluation of the hydrological cycle in reanalyses and observations. Report No. 228, Max-Planck-Institut für Meteorologie, Hamburg, Germany, p 52

  • Stendel M, Roeckner E (1998) Impacts of horizontal resolution in simulated climate statistics in ECHAM4. Max Planck Institute for Meteorology, Rep. No. 253, p 57

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

    Article  Google Scholar 

  • Tokioka T, Yamazaki K, Kitoh A, Ose T (1988) The equatorial 30–60 day oscillation and the Arakawa–Schubert penetrative cumulus parameterization. J Meteorol Soc Jpn 66:883–900

    Google Scholar 

  • Valcke S, Terray L, Piacentini A, (2000) The OASIS coupler user guide, Version 2.4. Technical report TR/CMGC/00–10, CERFACS, France, p 77

  • Waliser DE, Lau K-M, Kim J-H (1999) The influence of coupled sea surface temperatures on the Madden–Julian oscillation: a model perturbation experiment. J Atmos Sci 56:333–358

    Article  Google Scholar 

  • Wang WQ, Schlesinger ME (1999) The dependence on convective parameterization of the tropical intraseasonal oscillation simulated by the UIUC 11-layer atmospheric GCM. J Clim 12:1423–1457

    Article  Google Scholar 

  • Weickmann KM, Lussky GR, Kutzbach JE (1985) Intraseasonal (30–60 day) fluctuations of outgoing longwave radiation and 250 mb streamfunction during northern winter. Mon Weather Rev 113:941–961

    Article  Google Scholar 

  • Woolnough SJ, Slingo JM, Hoskins BJ (2000) The relationship between convection and sea surface temperature on intraseasonal timescales. J Clim 13:2086–2104

    Article  Google Scholar 

  • Woolnough SJ, Slingo JM, Hoskins BJ (2001) The organization of tropical convection by intraseasonal sea surface temperature anomalies. Q J R Meteorol Soc 127:887–907

    Article  Google Scholar 

  • Xie P, Arkin P (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Amer Meteorol Soc 78:2539–2558

    Article  Google Scholar 

Download references

Acknowledgements

K. R. Sperber thanks Dr. B. Santer (PCMDI) for helpful discussions regarding Monte Carlo sampling. This work was performed under the auspices of the U.S. Department of Energy Office of Science, Climate Change Prediction Program by University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48.

Author information

Authors and Affiliations

  1. Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, P.O. Box 808, L-103, Livermore, CA, 94550, USA

    Kenneth R. Sperber

  2. National Institute of Geophysics and Volcanology, Via Gobetti 101, 40129, Bologna, Italy

    Silvio Gualdi

  3. Models and Data Group, Max Planck Institute of Meteorology, Bundesstrasse 58, 20146, Hamburg, Germany

    Stephanie Legutke & Veronika Gayler

Authors
  1. Kenneth R. Sperber
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Silvio Gualdi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stephanie Legutke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Veronika Gayler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kenneth R. Sperber.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sperber, K.R., Gualdi, S., Legutke, S. et al. The Madden–Julian oscillation in ECHAM4 coupled and uncoupled general circulation models. Clim Dyn 25, 117–140 (2005). https://doi.org/10.1007/s00382-005-0026-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-005-0026-3

Keywords

Search

Navigation