IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v566y2019i7744d10.1038_s41586-018-0872-x.html
   My bibliography  Save this article

Complex networks reveal global pattern of extreme-rainfall teleconnections

Author

Listed:
  • Niklas Boers

    (Imperial College
    Potsdam Institute for Climate Impact Research)

  • Bedartha Goswami

    (Potsdam Institute for Climate Impact Research)

  • Aljoscha Rheinwalt

    (University of Potsdam)

  • Bodo Bookhagen

    (University of Potsdam)

  • Brian Hoskins

    (Imperial College
    University of Reading)

  • Jürgen Kurths

    (Potsdam Institute for Climate Impact Research
    Humboldt University
    Saratov State University)

Abstract

Climatic observables are often correlated across long spatial distances, and extreme events, such as heatwaves or floods, are typically assumed to be related to such teleconnections1,2. Revealing atmospheric teleconnection patterns and understanding their underlying mechanisms is of great importance for weather forecasting in general and extreme-event prediction in particular3,4, especially considering that the characteristics of extreme events have been suggested to change under ongoing anthropogenic climate change5–8. Here we reveal the global coupling pattern of extreme-rainfall events by applying complex-network methodology to high-resolution satellite data and introducing a technique that corrects for multiple-comparison bias in functional networks. We find that the distance distribution of significant connections (P

Suggested Citation

  • Niklas Boers & Bedartha Goswami & Aljoscha Rheinwalt & Bodo Bookhagen & Brian Hoskins & Jürgen Kurths, 2019. "Complex networks reveal global pattern of extreme-rainfall teleconnections," Nature, Nature, vol. 566(7744), pages 373-377, February.
  • Handle: RePEc:nat:nature:v:566:y:2019:i:7744:d:10.1038_s41586-018-0872-x
    DOI: 10.1038/s41586-018-0872-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-018-0872-x
    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/s41586-018-0872-x?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. Midhuna Thayyil Mandodi & D. R. Pattanaik, 2023. "The dependence of Indian winter precipitation extreme on the North Atlantic Oscillation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(2), pages 1869-1885, June.
    2. Hu, Yuntong & Xiao, Fuyuan, 2022. "A novel method for forecasting time series based on directed visibility graph and improved random walk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    3. Shixue Li & Tomonori Sato & Tetsu Nakamura & Wenkai Guo, 2023. "East Asian summer rainfall stimulated by subseasonal Indian monsoonal heating," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    4. Felix M. Strnad & Jakob Schlör & Ruth Geen & Niklas Boers & Bedartha Goswami, 2023. "Propagation pathways of Indo-Pacific rainfall extremes are modulated by Pacific sea surface temperatures," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    5. Yifei Yang & Sichen Tao & Haichuan Yang & Zijing Yuan & Zheng Tang, 2023. "Dynamic Complex Network, Exploring Differential Evolution Algorithms from Another Perspective," Mathematics, MDPI, vol. 11(13), pages 1-16, July.
    6. Zeng, Jie & Xiong, Yong & Liu, Feiyang & Ye, Junqing & Tang, Jinjun, 2022. "Uncovering the spatiotemporal patterns of traffic congestion from large-scale trajectory data: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    7. Alok Bhardwaj & Robert J. Wasson & Winston T. L. Chow & Alan D. Ziegler, 2021. "High-intensity monsoon rainfall variability and its attributes: a case study for Upper Ganges Catchment in the Indian Himalaya during 1901–2013," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2907-2936, February.
    8. Alves Xavier, Sílvio Fernando & Xavier, Érika Fialho Morais & Jale, Jader Silva & Stosic, Tatijana & Santos, Carlos Antonio Costa dos, 2021. "Multiscale entropy analysis of monthly rainfall time series in Paraíba, Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    9. Zexi Shen & Qiang Zhang & Vijay P. Singh & Yadu Pokhrel & Jianping Li & Chong-Yu Xu & Wenhuan Wu, 2022. "Drying in the low-latitude Atlantic Ocean contributed to terrestrial water storage depletion across Eurasia," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    10. Xu, Guiqiong & Meng, Lei, 2023. "A novel algorithm for identifying influential nodes in complex networks based on local propagation probability model," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    11. Phong V. V. Le & James T. Randerson & Rebecca Willett & Stephen Wright & Padhraic Smyth & Clément Guilloteau & Antonios Mamalakis & Efi Foufoula-Georgiou, 2023. "Climate-driven changes in the predictability of seasonal precipitation," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    12. Amanda de O. Regueira & Henderson Silva Wanderley, 2022. "Changes in rainfall rates and increased number of extreme rainfall events in Rio de Janeiro city," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3833-3847, December.
    13. Kaiwen Li & Ming Wang & Kai Liu, 2021. "The Study on Compound Drought and Heatwave Events in China Using Complex Networks," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    14. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    15. Xijin Wang & Fenghua Xie & Zhongshi Zhang & Stefan Liess & Keyan Fang & Chenxi Xu & Feng Shi, 2021. "Complex network of synchronous climate events in East Asian tree-ring data," Climatic Change, Springer, vol. 165(3), pages 1-14, April.
    16. Antonio Samuel Alves da Silva & Ikaro Daniel de Carvalho Barreto & Moacyr Cunha-Filho & Rômulo Simões Cezar Menezes & Borko Stosic & Tatijana Stosic, 2022. "Spatial and Temporal Variability of Precipitation Complexity in Northeast Brazil," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    17. Nico Wunderling & Frederik Wolf & Obbe A. Tuinenburg & Arie Staal, 2022. "Network motifs shape distinct functioning of Earth’s moisture recycling hubs," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    18. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    19. Hu, Yuntong & Xiao, Fuyuan, 2022. "An efficient forecasting method for time series based on visibility graph and multi-subgraph similarity," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    20. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    21. Somnath Mondal & Ashok K. Mishra & Ruby Leung & Benjamin Cook, 2023. "Global droughts connected by linkages between drought hubs," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

    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:566:y:2019:i:7744:d:10.1038_s41586-018-0872-x. 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.