Skip to main content
Log in

MJO structure associated with the higher-order CEOF modes

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

The real-time multivariate Madden–Julian oscillation (RMM; MJO) index has been widely employed to monitor the amplitude, phase, and time evolution of MJO events, as the index is formulated from the leading two combined-empirical orthogonal function (CEOF) modes of daily anomalous OLR and 850- and 200-hPa zonal winds, and the modes describe the MJO dynamics well. These two CEOF modes, however, are known to dominate in power spectra at zonal wavenumber one and may underestimate the power and structure at wavenumbers 2–5 where many MJO events are also prominent. This study approximated a baseline for MJO by applying band-pass filters to daily anomalies on 30–100 day periods and at 1–5 eastward propagating waves, as slightly different bands led to the same conclusions. Following the procedures to develop the RMM index, the daily anomalous data were derived and subjected to the CEOF analysis with all modes archived for diagnosis. Different numbers of the leading modes were compared in explained variance, standard deviation (STD), and wavenumber power spectra to describe the overall MJO magnitude and structure, and on the Hovmöller diagrams to represent the evolution of three distinct MJO events. Results show that the two leading CEOF modes explain only a small portion of the power spectra at wavenumbers 2–5. This spectral leakage notably reduces the MJO amplitude, particularly of the OLR in the western Pacific. The CEOF modes 3–10 can withhold power sufficiently such that the anomalies reconstructed by the first 10 modes contribute most of the baseline variance; their structures agree well with the baseline by constituting nearly the same proportion in the region from the central Indian Ocean to the dateline and by providing more complete evolutions of the three MJO events on the Hovmöller diagrams. Meanwhile, these modes introduce a notable amount of power for the equatorial Rossby and Kelvin waves that are partially embedded in the evolution of MJO. The first 50 of the total 432 CEOF modes retain all variance of the baseline MJO, while those higher than 10 contain less information and more noise and can be discarded. Furthermore, this study indicated that the longitudinal STD of the reconstructed anomalies detects the MJO phases and magnitudes in the western Pacific with more physical meaning and in better agreement with the Hovmöller diagrams than the RMM-like amplitude. The results provide an integral figure of the MJO structure from the CEOF analysis and a more robust RMM framework for monitoring the MJO’s evolution in real time and for validating its numerical forecast and simulations.

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

References

  • Drosdowsky W, Chambers LE (2001) Near-global sea surface temperature anomalies as predictors of Australian seasonal rainfall. J Clim 14:1677–1687

    Article  Google Scholar 

  • Gottschalck J et al (2010) A framework for assessing operational Madden–Julian oscillation forecasts. Bull Am Meteorol Soc 91:1247–1258

    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 JG (1999) Interannual variation of the Madden–Julian oscillation during Austral summer. J Clim 12:2538–2550

    Article  Google Scholar 

  • Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–470

    Article  Google Scholar 

  • Kiladis GN, Straub KH, Haertel PT (2005) Zonal and vertical structure of the Madden–Julian oscillation. J Atmos Sci 62:2790–2809

    Article  Google Scholar 

  • Kim D et al (2009) Application of MJO simulation diagnostics to climate models. J Clim 22:6413–6436

    Article  Google Scholar 

  • Knutson TR, Weickmann KM (1987) 30–60 day atmospheric oscillations: composite life cycles of convection and circulation anomalies. Mon Weather Rev 115:1407–1436

    Article  Google Scholar 

  • Lau KM, Chan PH (1985) Aspects of the 40–50 day oscillation during the northern winter as inferred from outgoing long-wave radiation. Mon Weather Rev 113:1889–1909

    Article  Google Scholar 

  • Liebmann B, Smith CA (1996) Description of a complete (interpolated) outgoing longwave radiation dataset. Bull Am Meteorol Soc 77:1275–1277

    Google Scholar 

  • Liu P, Wang B, Sperber KR, Li T, Meehl GA (2005) MJO in the NCAR CAM2 with the Tiedtke convective scheme. J Clim 18:3007–3020

    Article  Google Scholar 

  • Liu P et al (2009) An MJO simulated by the NICAM at 14-km and 7-km resolutions. Mon Weather Rev 137:3254–3268

    Article  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 

  • 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 

  • Rayner NA et al (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108:4407. doi:10.1029/2002JD002670

    Article  Google Scholar 

  • Roundy PE (2012a) The spectrum of convectively coupled Kelvin waves and the Madden–Julian oscillation in regions of low-level easterly and westerly background flow. J Atmos Sci 69:2107–2111

    Article  Google Scholar 

  • Roundy PE (2012b) Observed structure of convectively coupled waves as a function of equivalent depth: Kelvin waves and the Madden–Julian oscillation. J Atmos Sci 69:2097–2106

    Article  Google Scholar 

  • Roundy PE, Schreck CJ III, Janiga MA (2009) Contributions of convectively coupled equatorial Rossby waves and Kelvin waves to the real-time multivariate MJO indices. Mon Weather Rev 137:469–478

    Article  Google Scholar 

  • Slingo JM et al (1996) Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject. Clim Dyn 12:325–357

    Article  Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

  • Straub KH (2013) MJO initiation in the real-time multivariate MJO index. J Clim 26:1130–1151

    Article  Google Scholar 

  • The NCAR command language (version 6.1.1) [software], 2013. UCAR/NCAR/CISL/VETS, Boulder, CO. http://dx.doi.org/10.5065/D6WD3XH5

  • Wang B (1988) Dynamics of tropical low frequency waves: an analysis of moist Kelvin waves. J Atmos Sci 45:2051–2065

    Article  Google Scholar 

  • Wang B, Rui H (1990) Dynamics of the coupled moist Kelvin–Rossby wave on an equatorial β-plane. J Atmos Sci 47:397–413

    Article  Google Scholar 

  • Webster PJ, Lukas R (1992) TOGA COARE: the coupled ocean-atmosphere response experiment. Bull Am Meteorol Soc 73:1377–1416

    Article  Google Scholar 

  • Wheeler M, Hendon HH (2004) An all-season real-time multivariate MJO index: development of an index for monitoring and prediction. Mon Weather Rev 132:1917–1932

    Article  Google Scholar 

  • Wheeler M, Kiladis GN (1999) Convectively coupled equatorial waves: analysis of clouds and temperature in the wavenumber-frequency domain. J Atmos Sci 56:374–399

    Article  Google Scholar 

  • Yanai M, Chen B, Tung WW (2000) The Madden–Julian oscillation observed during the TOGA COARE IOP: global view. J Atmos Sci 57:2374–2396

    Article  Google Scholar 

  • Zhang C (2005) Madden–Julian oscillation. Rev Geophys 43:RG2003. doi:10.1029/2004RG000158

    Google Scholar 

  • Zhang C, Gottschalck J, Maloney ED, Moncrieff MW, Vitart F, Waliser DE, Wang B, Wheeler MC (2013) Cracking the MJO nut. Geophys Res Lett 40:1223–1230

    Article  Google Scholar 

Download references

Acknowledgments

This research is partially supported by the Office of Sciences of the U.S. Department of Energy to Stony Brook University. Interpolated OLR data and the zonal winds are provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/. The manuscript has benefited substantially from the constructive comments made by the anonymous reviewers. Useful comments also came from Drs. Melanie A. Wolfe Pitt and Christopher Wolfe.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ping Liu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liu, P. MJO structure associated with the higher-order CEOF modes. Clim Dyn 43, 1939–1950 (2014). https://doi.org/10.1007/s00382-013-2017-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-013-2017-0

Keywords

Navigation