Identification of the Madden–Julian Oscillation With Data-Driven Koopman Spectral Analysis

Benjamin R. Lintner, Dimitrios Giannakis, Max Pike, Joanna Slawinska

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, is commonly identified using the realtime multivariate MJO (RMM) index based on joint empirical orthogonal function (EOF) analysis of near-equatorial upper and lower level zonal winds and outgoing longwave radiation. Here, in place of conventional EOFs, we apply an operator-theoretic formalism based on dynamic systems theory (the Koopman operator) to extract an analog to RMM that exhibits certain features that refine the characterization and predictability of the MJO. In particular, the spectrum of Koopman operator eigenfunctions, with eigenvalues corresponding to mode periods, contains a leading intraseasonal mode with period of ∼50 days. Moreover, the amplitude of this leading intraseasonal eigenfunction exhibits a seasonal modulation clearly peaked in boreal winter. Finally, the phase space formed by the complex Koopman MJO eigenfunction exhibits a smoother temporal evolution and higher degree of autocorrelation than RMM, which may contribute to enhanced predictive skill.

Original languageEnglish (US)
Article numbere2023GL102743
JournalGeophysical Research Letters
Volume50
Issue number10
DOIs
StatePublished - May 28 2023

All Science Journal Classification (ASJC) codes

  • Geophysics
  • General Earth and Planetary Sciences

Keywords

  • Koopman operator
  • Madden-Julian Oscillation
  • climate data analysis
  • climate variability
  • data analysis: algorithms and implementation
  • spectral analysis
  • tropical dynamics

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