Global teleconnectivity structures of the El Ni\~no-Southern Oscillation and large volcanic eruptions -- An evolving network perspective

Recent work has provided ample evidence that global climate dynamics at time-scales between multiple weeks and several years can be severely affected by the episodic occurrence of both, internal (climatic) and external (non-climatic) perturbations. Here, we aim to improve our understanding on how regional to local disruptions of the "normal" state of the global surface air temperature field affect the corresponding global teleconnectivity structure. Specifically, we present an approach to quantify teleconnectivity based on different characteristics of functional climate network analysis. Subsequently, we apply this framework to study the impacts of different phases of the El Ni\~no-Southern Oscillation (ENSO) as well as the three largest volcanic eruptions since the mid 20th century on the dominating spatiotemporal co-variability patterns of daily surface air temperatures. Our results confirm the existence of global effects of ENSO which result in episodic breakdowns of the hierarchical organization of the global temperature field. This is associated with the emergence of strong teleconnections. At more regional scales, similar effects are found after major volcanic eruptions. Taken together, the resulting time-dependent patterns of network connectivity allow a tracing of the spatial extents of the dominating effects of both types of climate disruptions. We discuss possible links between these observations and general aspects of atmospheric circulation.

[1]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[2]  J. Kurths,et al.  Temporal evolution of the spatial covariability of rainfall in South America , 2018, Climate Dynamics.

[3]  E. Guilyardi,et al.  Tropical explosive volcanic eruptions can trigger El Niño by cooling tropical Africa , 2017, Nature Communications.

[4]  S. Havlin,et al.  Network analysis reveals strongly localized impacts of El Niño , 2017, Proceedings of the National Academy of Sciences.

[5]  Marc Wiedermann,et al.  Complex Network Techniques for Climatological Data Analysis , 2017 .

[6]  Marc Wiedermann,et al.  A climate network‐based index to discriminate different types of El Niño and La Niña , 2016, 1604.04432.

[7]  Bin Wang,et al.  Global monsoon precipitation responses to large volcanic eruptions , 2016, Scientific Reports.

[8]  Jürgen Kurths,et al.  Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package. , 2015, Chaos.

[9]  Jurgen Kurths,et al.  How complex climate networks complement eigen techniques for the statistical analysis of climatological data , 2013, Climate Dynamics.

[10]  J. Kurths,et al.  Correlations between climate network and relief data , 2014 .

[11]  T. Zhou,et al.  Effects of Large Volcanic Eruptions on Global Summer Climate and East Asian Monsoon Changes during the Last Millennium: Analysis of MPI-ESM Simulations , 2014 .

[12]  Milan Paluš,et al.  Multiscale atmospheric dynamics: cross-frequency phase-amplitude coupling in the air temperature. , 2014, Physical review letters.

[13]  Shlomo Havlin,et al.  Very early warning of next El Niño , 2014, Proceedings of the National Academy of Sciences.

[14]  Jakob Runge,et al.  Quantifying the Strength and Delay of Climatic Interactions: The Ambiguities of Cross Correlation and a Novel Measure Based on Graphical Models , 2014 .

[15]  Jürgen Kurths,et al.  Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System , 2013, Entropy.

[16]  Jürgen Kurths,et al.  Disentangling different types of El Niño episodes by evolving climate network analysis. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Shlomo Havlin,et al.  Global climate network evolves with North Atlantic Oscillation phases: Coupling to Southern Pacific Ocean , 2013, 1309.1905.

[18]  H. Dijkstra Nonlinear Climate Dynamics , 2013 .

[19]  Shlomo Havlin,et al.  Improved El Niño forecasting by cooperativity detection , 2013, Proceedings of the National Academy of Sciences.

[20]  Jürgen Kurths,et al.  Node-weighted interacting network measures improve the representation of real-world complex systems , 2013, ArXiv.

[21]  Anastasios A. Tsonis,et al.  Review article "On the origins of decadal climate variability: a network perspective" , 2012 .

[22]  M. Holland,et al.  Abrupt onset of the Little Ice Age triggered by volcanism and sustained by sea‐ice/ocean feedbacks , 2012 .

[23]  S. Havlin,et al.  Climate network structure evolves with North Atlantic Oscillation phases , 2011, 1109.3633.

[24]  Jurgen Kurths,et al.  Node-weighted measures for complex networks with spatially embedded, sampled, or differently sized nodes , 2011, The European Physical Journal B.

[25]  Nitesh V. Chawla,et al.  Multivariate and multiscale dependence in the global climate system revealed through complex networks , 2012, Climate Dynamics.

[26]  Vipin Kumar,et al.  Discovering Dynamic Dipoles in Climate Data , 2011, SDM.

[27]  Milan Paluš,et al.  Discerning connectivity from dynamics in climate networks , 2011 .

[28]  L. D. Costa,et al.  Community structure and dynamics in climate networks , 2011 .

[29]  Jürgen Kurths,et al.  Investigating the topology of interacting networks - Theory and application to coupled climate subnetworks , 2011, ArXiv.

[30]  Mark A. Cane,et al.  The El Niño-Southern Oscillation Phenomenon , 2010 .

[31]  G. North,et al.  Empirical Orthogonal Functions: The Medium is the Message , 2009 .

[32]  Toshio Yamagata,et al.  Climate change: The El Niño with a difference. , 2009, Nature.

[33]  Potsdam,et al.  Complex networks in climate dynamics. Comparing linear and nonlinear network construction methods , 2009, 0907.4359.

[34]  Nitesh V. Chawla,et al.  An exploration of climate data using complex networks , 2009, SensorKDD '09.

[35]  A. Voldoire,et al.  Influence of ENSO on the West African Monsoon: Temporal Aspects and Atmospheric Processes , 2009 .

[36]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[37]  Norbert Marwan,et al.  The backbone of the climate network , 2009, 1002.2100.

[38]  S. Havlin,et al.  Pattern of climate network blinking links follows El Niño events , 2008 .

[39]  Geli Wang,et al.  On the Role of Atmospheric Teleconnections in Climate , 2008 .

[40]  A. Tsonis,et al.  Topology and predictability of El Niño and La Niña networks. , 2008, Physical review letters.

[41]  S. Havlin,et al.  Climate networks around the globe are significantly affected by El Niño. , 2008, Physical review letters.

[42]  Allan J. Clarke,et al.  An Introduction to the Dynamics of El Nino and the Southern Oscillation , 2008 .

[43]  Martin Rosvall,et al.  Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.

[44]  Réka Albert,et al.  Near linear time algorithm to detect community structures in large-scale networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[45]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[46]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[47]  Paul J. Roebber,et al.  What Do Networks Have to Do with Climate , 2006 .

[48]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[49]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[50]  Matthieu Latapy,et al.  Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..

[51]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[52]  D. Maraun,et al.  Epochs of phase coherence between El Niño/Southern Oscillation and Indian monsoon , 2005 .

[53]  A. Gámez,et al.  Nonlinear dimensionality reduction in climate data , 2004 .

[54]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[55]  J. Turner The El Niño–southern oscillation and Antarctica , 2004 .

[56]  M. Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[57]  J. Neelin,et al.  Tropical drought regions in global warming and El Niño teleconnections , 2003 .

[58]  Klaus Fraedrich,et al.  Scaling of atmosphere and ocean temperature correlations in observations and climate models. , 2003, Physical review letters.

[59]  M. Hoerling,et al.  ENSO variability, teleconnections and climate change , 2001 .

[60]  Kevin E. Trenberth,et al.  Indices of El Niño Evolution , 2001 .

[61]  W. Collins,et al.  The NCEP–NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation , 2001 .

[62]  H. Storch,et al.  Statistical Analysis in Climate Research , 2000 .

[63]  A. Robock Volcanic eruptions and climate , 2000 .

[64]  T. Wigley,et al.  Global patterns of ENSO‐induced precipitation , 2000 .

[65]  D. E. Harrison,et al.  El Niño‐Southern Oscillation sea surface temperature and wind anomalies, 1946–1993 , 1998 .

[66]  Kevin E. Trenberth,et al.  The Definition of El Niño. , 1997 .

[67]  M. McCormick,et al.  Atmospheric effects of the Mt Pinatubo eruption , 1995, Nature.

[68]  R. Heikes,et al.  Numerical Integration of the Shallow-Water Equations on a Twisted Icosahedral Grid , 1995 .

[69]  C. Ropelewski,et al.  Global and Regional Scale Precipitation Patterns Associated with the El Niño/Southern Oscillation , 1987 .

[70]  E. Rasmusson,et al.  Variations in Tropical Sea Surface Temperature and Surface Wind Fields Associated with the Southern Oscillation/El Niño , 1982 .