Hierarchical structure of the Madden-Julian oscillation in infrared brightness temperature revealed through nonlinear Laplacian spectral analysis

Dimitrios Giannakis, Wen Wen Tung, Andrew J. Majda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The convection-coupled tropical atmospheric motions are highly nonlinear and multiscaled, and play a major role in weather and climate predictability in both the tropics and mid-latitudes. In this work, nonlinear Laplacian spectral analysis (NLSA) is applied to extract spatiotemporal modes of variability in tropical dynamics from satellite observations. Blending qualitative analysis of dynamical systems, singular spectrum analysis (SSA), and spectral graph theory, NLSA has been shown to capture intermittency, rare events, and other nonlinear dynamical features not accessible through classical SSA. Applied to 1983-2006 satellite infrared brightness temperature data averaged over the global tropical belt, the method reveals a wealth of spatiotemporal patterns, most notably the 30-90-day Madden-Julian oscillation (MJO). Using the Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment period as an example, representative modes associated with the MJO are reconstructed. The recovered modes augment Nakazawa's classical hierarchical structure of intraseasonal variability with intermediate modes between the fundamental MJO envelope and super cloud clusters.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 Conference on Intelligent Data Understanding, CIDU 2012
Pages55-62
Number of pages8
DOIs
StatePublished - 2012
Event2012 Conference on Intelligent Data Understanding, CIDU 2012 - Boulder, CO, United States
Duration: Oct 24 2012Oct 26 2012

Publication series

NameProceedings - 2012 Conference on Intelligent Data Understanding, CIDU 2012

Other

Other2012 Conference on Intelligent Data Understanding, CIDU 2012
Country/TerritoryUnited States
CityBoulder, CO
Period10/24/1210/26/12

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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