A climate network-based index to discriminate different types of El Niño and La Niña

Marc Wiedermann, Alexander Radebach, Jonathan F. Donges, Jürgen Kurths, Reik V. Donner

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49 Citations (Scopus)
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Abstract

El Ni\~no exhibits distinct Eastern Pacific (EP) and Central Pacific (CP) types which are commonly, but not always consistently, distinguished from each other by different signatures in equatorial climate variability. Here, we propose an index based on evolving climate networks to objectively discriminate between both flavors by utilizing a scalar-valued evolving climate network measure that quantifies spatial localization and dispersion in El Ni\~no's associated teleconnections. Our index displays a sharp peak (high localization) during EP events, whereas during CP events (larger dispersion) it remains close to the baseline observed during normal periods. In contrast to previous classification schemes, our approach specifically account for El Ni\~no's global impacts. We confirm recent El Ni\~no classifications for the years 1951 to 2014 and assign types to those cases were former works yielded ambiguous results. Ultimately, we study La Ni\~na episodes and demonstrate that our index provides a similar discrimination into two types.
Original languageEnglish
Pages (from-to)7176-7185
Number of pages10
JournalGeophysical Research Letters
Volume43
Issue number13
Early online date14 Jul 2016
DOIs
Publication statusPublished - 16 Jul 2016

Bibliographical note

Funded by
German Federal Ministry for Education and Research via the BMBF Young Investigators Group CoSy-CC2. Grant Number: 01LN1306A
Planetary Boundary Research Network (PB.net)
Earth League's EarthDoc
DFG
FAPESP

Acknowledgments
M.W. and R.V.D. have been supported by the German Federal Ministry for Education and Research via the BMBF Young Investigators Group CoSy-CC2 (grant 01LN1306A). J.F.D. thanks the Stordalen Foundation via the Planetary Boundary Research Network (PB.net) and the Earth League's EarthDoc program for financial support. J.K. acknowledges the IRTG 1740 funded by DFG and FAPESP. NCEP Reanalysis data are provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website http://www.esrl.noaa.gov/psd/. Parts of the analysis have been performed using the Python package pyunicorn [Donges et al., 2015b] available at https://github.com/pik-copan/pyunicorn.

Keywords

  • physics.data-an
  • physics.ao-ph

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