Boreal summer intraseasonal phases identified by nonlinear multivariate empirical orthogonal function-based self-organizing map (ESOM) analysis

  • Jung Eun Chu
  • , Bin Wang
  • , June Yi Lee
  • , Kyung Ja Ha

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

This study develops an empirical orthogonal function (EOF)-based self-organizing map (SOM) (ESOM) analysis to identify the nonlinear characteristics of the boreal summer intraseasonal oscillation (BSISO), which involves interactions between the summer mean circulation and the convectively coupled equatorial waves, which make BSISO evolution more complex than the Madden-Julian oscillation. The method utilizes the first five principal components of the outgoing longwave radiation (OLR) and the zonal wind at 850 hPa (U850) and has the advantages of filtering out uncertainties from noise and being free from mathematical restrictions, such as orthogonality and linearity. The ESOM analysis enables the detection of BSISO over the Asian summer monsoon region with eight phases. The four most distinguishable phases represent 1) a pair of stationary patterns with a dipole between the eastern Indian Ocean and the Philippine Sea (phases 1 and 5) and 2) a pair of propagating patterns with a northwest-southeast-tilted rain belt structure (phases 3 and 7). Phases 1 and 5 show an alternating seesaw oscillation throughout the summer with a 30-60-day period, whereas phases 3 and 7 peak in mid-June and early June denoting the monsoon rainy season and premonsoon period of Asian summer monsoon. ESOM captures that phases 1 and 5 happen more frequently and last longer than phases 3 and 7, whereas multivariate EOF analysis fails to describe this nonlinear occurrence. Phases 3 and phase 7 display distinct asymmetries in convective activity over the eastern Indian Ocean related to the relatively slow-growing and fast-decaying convective activity. The relationship with large-scale SST forcing is also discussed.

Original languageEnglish
Pages (from-to)3513-3528
Number of pages16
JournalJournal of Climate
Volume30
Issue number10
DOIs
StatePublished - May 1 2017
Externally publishedYes

Funding

This work was supported by the National Research Foundation of Korea (NRF) through a Global Research Laboratory (GRL) grant (MEST 2011-0021927). Jung-Eun Chu was supported by the Fostering Core Leaders of the Future Basic Science Program funded by funded by the NRF (NRF-2013H1A8A1004201).

Keywords

  • Asia
  • Empirical orthogonal functions
  • Intraseasonal variability
  • Monsoons
  • Neural networks
  • Oscillations

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