Prediction of the Madden-Julian oscillation: A review

Hyemi Kim, Frédéric Vitart, Duane E. Waliser

Research output: Contribution to journalReview articlepeer-review

125 Scopus citations

Abstract

There has been an accelerating interest in forecasting the weather and climate within the subseasonal time range. The Madden-Julian oscillation (MJO), an organized envelope of tropical convection, is recognized as one of the leading sources of subseasonal predictability. This review synthesizes the latest progress regarding the MJO predictability and prediction. During the past decade, the MJO prediction skill in dynamical prediction systems has exceeded the skill of empirical predictions. Such improvement has been mainly attributed to more observations and computer resources, advances in theoretical understanding, and improved numerical models aided in part by multinational efforts through field campaigns and multimodel experiments. The state-of-the-art dynamical forecasts have shown MJO prediction skill up to 5 weeks. Prediction skill can be extended by improving the ensemble generation approach tailored for MJO prediction and by averaging multiensembles or multimodels. MJO prediction skill can be influenced by the tropical mean state and lowfrequency climate mode variations, as well as by the extratropical circulation. MJO prediction skill is proven to be sensitive to model physics, ocean-atmosphere coupling, and quality of initial conditions, while the impact of the model resolution seems to be marginal. Remaining challenges and recommendations on new research avenues to fully realize the predictability of the MJO are discussed.

Original languageEnglish
Pages (from-to)9425-9443
Number of pages19
JournalJournal of Climate
Volume31
Issue number23
DOIs
StatePublished - 1 Dec 2018

Bibliographical note

Funding Information:
Constructive and valuable comments from three anonymous reviewers are greatly appreciated. Kim was supported by NSF Grant AGS-1652289, NOAA Grant NA16OAR4310070, and the KMAR&DProgramGrant KMI2018-03110. D. Waliser's contributions were carried out on behalf of the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA, including support from the NASA Modeling, Analysis and Prediction Program.

Funding Information:
Acknowledgments. Constructive and valuable comments from three anonymous reviewers are greatly appreciated. Kim was supported by NSF Grant AGS-1652289, NOAA Grant NA16OAR4310070, and the KMA R&D Program Grant KMI2018-03110. D. Waliser’s contributions were carried out on behalf of the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA, including support from the NASA Modeling, Analysis and Prediction Program.

Publisher Copyright:
© 2018 American Meteorological Society.

Keywords

  • Climate models
  • Climate prediction
  • Intraseasonal variability

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