IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v9y2018i1d10.1038_s41467-018-04881-7.html
   My bibliography  Save this article

Early-warning signals for Dansgaard-Oeschger events in a high-resolution ice core record

Author

Listed:
  • Niklas Boers

    (Imperial College
    Potsdam Institute for Climate Impact Research)

Abstract

The Dansgaard–Oeschger (DO) events, as observed in oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record, are an outstanding example of past abrupt climate transitions. Their physical cause remains debated, and previous research indicated that they are not preceded by classical early-warning signals (EWS). Subsequent research hypothesized that the DO events are caused by bifurcations of physical mechanisms operating at decadal timescales, and proposed to search for EWS in the high-frequency fluctuation levels. Here, a time series with 5-year resolution is obtained from the raw NGRIP record, and significant numbers of EWS in terms of variance and autocorrelation increases are revealed in the decadal-scale variability. Wavelet analysis indicates that the EWS are most pronounced in the 10–50-year periodicity band, confirming the above hypothesis. The DO events are hence neither directly noise-induced nor purely externally forced, which provides valuable constraints regarding potential physical causes.

Suggested Citation

  • Niklas Boers, 2018. "Early-warning signals for Dansgaard-Oeschger events in a high-resolution ice core record," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04881-7
    DOI: 10.1038/s41467-018-04881-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-018-04881-7
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-018-04881-7?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
    ---><---

    Citations

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


    Cited by:

    1. Thomas M. Bury & Daniel Dylewsky & Chris T. Bauch & Madhur Anand & Leon Glass & Alvin Shrier & Gil Bub, 2023. "Predicting discrete-time bifurcations with deep learning," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Ramos, Antônio M.T. & Casagrande, Helder L. & Macau, Elbert E.N., 2020. "Investigation on the high-order approximation of the entropy bias," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    3. Chris A. Boulton & Timothy M. Lenton & Niklas Boers, 2022. "Pronounced loss of Amazon rainforest resilience since the early 2000s," Nature Climate Change, Nature, vol. 12(3), pages 271-278, March.

    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:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04881-7. 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.