IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v559y2018i7715d10.1038_s41586-018-0252-6.html
   My bibliography  Save this article

El Niño–Southern Oscillation complexity

Author

Listed:
  • Axel Timmermann

    (Institute for Basic Science (IBS)
    Pusan National University
    University of Hawaii at Manoa)

  • Soon-Il An

    (Yonsei University)

  • Jong-Seong Kug

    (Pohang University of Science and Technology (POSTECH))

  • Fei-Fei Jin

    (University of Hawaii at Manoa)

  • Wenju Cai

    (CSIRO Oceans and Atmosphere
    Ocean University of China and Qingdao National Laboratory for Marine Science and Technology
    CSIRO Oceans and Atmosphere)

  • Antonietta Capotondi

    (University of Colorado
    NOAA Earth System Research Laboratory)

  • Kim M. Cobb

    (Georgia Tech)

  • Matthieu Lengaigne

    (Sorbonne Universités/UPMC-CNRS-IRD-MNHN)

  • Michael J. McPhaden

    (Pacific Marine Environmental Laboratory/NOAA)

  • Malte F. Stuecker

    (University of Washington
    University Corporation for Atmospheric Research)

  • Karl Stein

    (Institute for Basic Science (IBS)
    Pusan National University)

  • Andrew T. Wittenberg

    (Geophysical Fluid Dynamics Laboratory/NOAA)

  • Kyung-Sook Yun

    (Institute for Basic Science (IBS)
    Pusan National University)

  • Tobias Bayr

    (GEOMAR Helmholtz Centre for Ocean Research)

  • Han-Ching Chen

    (National Taiwan University)

  • Yoshimitsu Chikamoto

    (Utah State University)

  • Boris Dewitte

    (Centro de Estudios Avanzado en Zonas Áridas (CEAZA)
    Laboratoire d’Etudes en Géophysique et Océanographie Spatiale)

  • Dietmar Dommenget

    (Monash University)

  • Pamela Grothe

    (University of Mary Washington)

  • Eric Guilyardi

    (Laboratoire d’Océanographie et du Climat: Expérimentation et Approches Numériques (LOCEAN), IRD/UPMC/CNRS/MNHN
    University of Reading)

  • Yoo-Geun Ham

    (Chonnam National University)

  • Michiya Hayashi

    (University of Hawaii at Manoa)

  • Sarah Ineson

    (Met Office Hadley Centre)

  • Daehyun Kang

    (Ulsan National Institute of Science and Technology)

  • Sunyong Kim

    (Pohang University of Science and Technology (POSTECH))

  • WonMoo Kim

    (APEC Climate Center)

  • June-Yi Lee

    (Institute for Basic Science (IBS)
    Pusan National University)

  • Tim Li

    (University of Hawaii at Manoa
    University of Hawaii at Manoa)

  • Jing-Jia Luo

    (Australian Bureau of Meteorology)

  • Shayne McGregor

    (Monash University)

  • Yann Planton

    (Laboratoire d’Océanographie et du Climat: Expérimentation et Approches Numériques (LOCEAN), IRD/UPMC/CNRS/MNHN)

  • Scott Power

    (Australian Bureau of Meteorology)

  • Harun Rashid

    (CSIRO Oceans and Atmosphere)

  • Hong-Li Ren

    (China Meteorological Administration)

  • Agus Santoso

    (University of New South Wales)

  • Ken Takahashi

    (Instituto Geofisico del Peru)

  • Alexander Todd

    (University of Exeter College of Engineering, Mathematics and Physical Sciences)

  • Guomin Wang

    (Australian Bureau of Meteorology)

  • Guojian Wang

    (CSIRO Oceans and Atmosphere)

  • Ruihuang Xie

    (Chinese Academy of Sciences)

  • Woo-Hyun Yang

    (Pohang University of Science and Technology (POSTECH))

  • Sang-Wook Yeh

    (Hanyang University)

  • Jinho Yoon

    (Gwangju Institute of Science and Technology)

  • Elke Zeller

    (Institute for Basic Science (IBS)
    Pusan National University)

  • Xuebin Zhang

    (CSIRO Ocean and Atmosphere)

Abstract

El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño–Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.

Suggested Citation

  • Axel Timmermann & Soon-Il An & Jong-Seong Kug & Fei-Fei Jin & Wenju Cai & Antonietta Capotondi & Kim M. Cobb & Matthieu Lengaigne & Michael J. McPhaden & Malte F. Stuecker & Karl Stein & Andrew T. Wit, 2018. "El Niño–Southern Oscillation complexity," Nature, Nature, vol. 559(7715), pages 535-545, July.
    • Handle: RePEc:nat:nature:v:559:y:2018:i:7715:d:10.1038_s41586-018-0252-6
    DOI: 10.1038/s41586-018-0252-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-018-0252-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/s41586-018-0252-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yiling Liu & Markus. G. Donat & Matthew. H. England & Lisa. V. Alexander & Annette L. Hirsch & Carlos Delgado-Torres, 2023. "Enhanced multi-year predictability after El Niño and La Niña events," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    2. Wei, Yu & Zhang, Jiahao & Chen, Yongfei & Wang, Yizhi, 2022. "The impacts of El Niño-southern oscillation on renewable energy stock markets: Evidence from quantile perspective," Energy, Elsevier, vol. 260(C).
    3. Wei, Yu & Zhang, Jiahao & Bai, Lan & Wang, Yizhi, 2023. "Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model," Renewable Energy, Elsevier, vol. 202(C), pages 289-309.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:559:y:2018:i:7715:d:10.1038_s41586-018-0252-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.