A climate network‐based index to discriminate different types of El Niño and La Niña

El Ni\~no exhibits distinct Eastern Pacific (EP) and Central Pacific (CP) types which are commonly, but not always consistently, distinguished from each other by different signatures in equatorial climate variability. Here, we propose an index based on evolving climate networks to objectively discriminate between both flavors by utilizing a scalar-valued evolving climate network measure that quantifies spatial localization and dispersion in El Ni\~no's associated teleconnections. Our index displays a sharp peak (high localization) during EP events, whereas during CP events (larger dispersion) it remains close to the baseline observed during normal periods. In contrast to previous classification schemes, our approach specifically account for El Ni\~no's global impacts. We confirm recent El Ni\~no classifications for the years 1951 to 2014 and assign types to those cases were former works yielded ambiguous results. Ultimately, we study La Ni\~na episodes and demonstrate that our index provides a similar discrimination into two types.

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

[2]  A. Vespignani,et al.  The architecture of complex weighted networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[3]  D. Zanchettin,et al.  Central pacific El Niño, the "subtropical bridge," and Eurasian climate , 2012 .

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

[5]  Jürgen Kurths,et al.  Identifying causal gateways and mediators in complex spatio-temporal systems , 2015, Nature Communications.

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

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

[8]  Judith A. Curry,et al.  Impact of Shifting Patterns of Pacific Ocean Warming on North Atlantic Tropical Cyclones , 2009, Science.

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

[10]  Jürgen Kurths,et al.  Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System , 2013 .

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

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

[13]  S. Havlin,et al.  Emergence of El Niño as an autonomous component in the climate network. , 2010, Physical review letters.

[14]  A. Timmermann,et al.  Increased El Niño frequency in a climate model forced by future greenhouse warming , 1999, Nature.

[15]  S. Lyons,et al.  Transients and the Extratropical Response to El Niño , 1989 .

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

[17]  M. England,et al.  El Niño Modoki Impacts on Australian Rainfall , 2009 .

[18]  A. Timmermann,et al.  ENSO and greenhouse warming , 2015 .

[19]  J. Donges,et al.  Hierarchical structures in Northern Hemispheric extratropical winter ocean–atmosphere interactions , 2015, 1506.06634.

[20]  F. Jin,et al.  Two Types of El Nio Events: Cold Tongue El Nio and Warm Pool El Nio , 2009 .

[21]  Yang Wang,et al.  Oceanic El-Niño wave dynamics and climate networks , 2015, 1505.07220.

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

[23]  Norbert Marwan,et al.  Regional and inter-regional effects in evolving climate networks , 2014 .

[24]  Mikko Kivelä,et al.  Generalizations of the clustering coefficient to weighted complex networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[26]  D. E. Harrison,et al.  Global seasonal temperature and precipitation anomalies during El Niño autumn and winter , 2005 .

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

[28]  Yuan Yuan,et al.  Different types of La Niña events and different responses of the tropical atmosphere , 2013 .

[29]  B. Bollobás.  The evolution of random graphs , 1984 .

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

[31]  A. Grimm,et al.  Influences of two types of ENSO on South American precipitation , 2013 .

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

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

[34]  H. Kao.  Eastern Pacific and central Pacific types of ENSO , 2009 .

[35]  Jürgen Kurths,et al.  Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka , 2014 .

[36]  D. Hennig,et al.  Collective transport of coupled particles , 2012 .

[37]  Arun Kumar,et al.  An analysis of warm pool and cold tongue El Niños: air–sea coupling processes, global influences, and recent trends , 2012, Climate Dynamics.

[38]  Swadhin K. Behera,et al.  El Niño Modoki and its possible teleconnection , 2007 .

[39]  Y. Ham,et al.  Are there two types of La Nina? , 2011 .

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

[41]  Harry H. Hendon,et al.  Prospects for predicting two flavors of El Niño , 2009 .

[42]  T. McMahon,et al.  El Nino/Southern Oscillation and Australian rainfall, streamflow and drought : Links and potential for forecasting , 1998 .

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

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

[45]  Tong Lee,et al.  El Niño and its relationship to changing background conditions in the tropical Pacific Ocean , 2011 .

[46]  Nathaniel C. Johnson,et al.  How Many ENSO Flavors Can We Distinguish , 2013 .

[47]  B. Kirtman,et al.  El Niño in a changing climate , 2009, Nature.

[48]  Delphine Clara Zemp,et al.  Node-weighted measures for complex networks with directed and weighted edges for studying continental moisture recycling , 2014 .

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

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

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

[52]  P. Erdos,et al.  On the evolution of random graphs , 1984 .

[53]  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.

[54]  Joo‐Hong Kim,et al.  The unique 2009–2010 El Niño event: A fast phase transition of warm pool El Niño to La Niña , 2011 .

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

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