Literature DB >> 18643467

Climate networks around the globe are significantly affected by El Niño.

K Yamasaki1, A Gozolchiani, S Havlin.   

Abstract

The temperatures in different zones in the world do not show significant changes due to El Niño except when measured in a restricted area in the Pacific Ocean. We find, in contrast, that the dynamics of a climate network based on the same temperature records in various geographical zones in the world is significantly influenced by El Niño. During El Niño many links of the network are broken, and the number of surviving links comprises a specific and sensitive measure for El Niño events. While during non-El Niño periods these links which represent correlations between temperatures in different sites are more stable, fast fluctuations of the correlations observed during El Niño periods cause the links to break.

Year:  2008        PMID: 18643467     DOI: 10.1103/PhysRevLett.100.228501

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  23 in total

1.  Improved El Nino forecasting by cooperativity detection.

Authors:  Josef Ludescher; Avi Gozolchiani; Mikhail I Bogachev; Armin Bunde; Shlomo Havlin; Hans Joachim Schellnhuber
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-01       Impact factor: 11.205

2.  Climate network percolation reveals the expansion and weakening of the tropical component under global warming.

Authors:  Jingfang Fan; Jun Meng; Yosef Ashkenazy; Shlomo Havlin; Hans Joachim Schellnhuber
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-26       Impact factor: 11.205

3.  Very early warning of next El Niño.

Authors:  Josef Ludescher; Avi Gozolchiani; Mikhail I Bogachev; Armin Bunde; Shlomo Havlin; Hans Joachim Schellnhuber
Journal:  Proc Natl Acad Sci U S A       Date:  2014-02-10       Impact factor: 11.205

4.  Network analysis reveals strongly localized impacts of El Niño.

Authors:  Jingfang Fan; Jun Meng; Yosef Ashkenazy; Shlomo Havlin; Hans Joachim Schellnhuber
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-03       Impact factor: 11.205

5.  Network-based forecasting of climate phenomena.

Authors:  Josef Ludescher; Maria Martin; Niklas Boers; Armin Bunde; Catrin Ciemer; Jingfang Fan; Shlomo Havlin; Marlene Kretschmer; Jürgen Kurths; Jakob Runge; Veronika Stolbova; Elena Surovyatkina; Hans Joachim Schellnhuber
Journal:  Proc Natl Acad Sci U S A       Date:  2021-11-23       Impact factor: 11.205

Review 6.  The structure and dynamics of multilayer networks.

Authors:  S Boccaletti; G Bianconi; R Criado; C I Del Genio; J Gómez-Gardeñes; M Romance; I Sendiña-Nadal; Z Wang; M Zanin
Journal:  Phys Rep       Date:  2014-07-10       Impact factor: 25.600

7.  Stability of climate networks with time.

Authors:  Y Berezin; A Gozolchiani; O Guez; S Havlin
Journal:  Sci Rep       Date:  2012-09-18       Impact factor: 4.379

8.  Unraveling spurious properties of interaction networks with tailored random networks.

Authors:  Stephan Bialonski; Martin Wendler; Klaus Lehnertz
Journal:  PLoS One       Date:  2011-08-05       Impact factor: 3.240

9.  A Network of Networks Perspective on Global Trade.

Authors:  Julian Maluck; Reik V Donner
Journal:  PLoS One       Date:  2015-07-21       Impact factor: 3.240

10.  Climate dynamics: a network-based approach for the analysis of global precipitation.

Authors:  Stefania Scarsoglio; Francesco Laio; Luca Ridolfi
Journal:  PLoS One       Date:  2013-08-19       Impact factor: 3.240

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