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Climate Dynamics

, Volume 52, Issue 5–6, pp 2529–2543 | Cite as

MJO evolution and predictability disclosed by the RMM variant with balanced MJO variance in convection and zonal winds

  • Ping LiuEmail author
Article
  • 110 Downloads

Abstract

The all-season real-time multivariate MJO (RMM) index was designed for an equal contribution of variance from the raw anomalous OLR and zonal winds at 850 (U850) and 200 hPa (U200), whereas it represents a notably larger proportion of the MJO variance in U850 and U200 than in OLR such that the index appears more dynamical and overestimates the MJO predictability and prediction skills. The revised RMM (RMM-r) substantially enhanced the fraction in OLR and reduced that in U850, whilst the distribution remains far from a balance. A new variant (RMM-b) is derived with the constraint of representing the same percentage (about 60.5%) of the globally total MJO variance in each field. The constraint determines 9 W m− 2, 2.73 m s− 1 and 4.1 m s− 1 to scale the OLR, U850 and U200, respectively, after the interannual variability is removed from the anomalies by a regression approach. The resultant RMM-b represents 30–40% more MJO power in OLR than the RMM, particularly at zonal wavenumbers 2–3 in eastward propagation and in the Western Pacific, and closer to the RMM-r. It carries 10–15% more MJO variance in U850 at zonal wavenumber 1 than the RMM-r, closer to the RMM. It detects the real-time MJO evolution closer to the RMM-r. And it discloses the MJO predictability and prediction skills in the recent Global Ensemble Forecasting System more reasonably than the RMM-r and closer to the RMM. The RMM-b is concluded to more suitably constitute the convectively coupled nature of the MJO.

Keywords

Madden–Julian oscillation RMM RMM-r RMM-b Predictability 

Notes

Acknowledgements

This study is supported by the National Oceanic and Atmospheric Administration under the Grants NA15NWS4680015 and NA15OAR4320064. The GEFS Reforecasts and NCEP-NCAR Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Marine and Atmospheric SciencesStony Brook UniversityNew YorkUSA

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