caa a22 4500 605472882 CHVBK 20210128100340.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00382-015-2479-3 doi (NATIONALLICENCE)springer-10.1007/s00382-015-2479-3 How complex climate networks complement eigen techniques for the statistical analysis of climatological data [Elektronische Daten] [Jonathan Donges, Irina Petrova, Alexander Loew, Norbert Marwan, Jürgen Kurths] Eigen techniques such as empirical orthogonal function (EOF) or coupled pattern (CP)/maximum covariance analysis have been frequently used for detecting patterns in multivariate climatological data sets. Recently, statistical methods originating from the theory of complex networks have been employed for the very same purpose of spatio-temporal analysis. This climate network (CN) analysis is usually based on the same set of similarity matrices as is used in classical EOF or CP analysis, e.g., the correlation matrix of a single climatological field or the cross-correlation matrix between two distinct climatological fields. In this study, formal relationships as well as conceptual differences between both eigen and network approaches are derived and illustrated using global precipitation, evaporation and surface air temperature data sets. These results allow us to pinpoint that CN analysis can complement classical eigen techniques and provides additional information on the higher-order structure of statistical interrelationships in climatological data. Hence, CNs are a valuable supplement to the statistical toolbox of the climatologist, particularly for making sense out of very large data sets such as those generated by satellite observations and climate model intercomparison exercises. Springer-Verlag Berlin Heidelberg, 2015 Climate networks nationallicence Empirical orthogonal functions nationallicence Coupled patterns nationallicence Maximum covariance analysis nationallicence Climate data analysis nationallicence Donges Jonathan Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412, Potsdam, Germany aut Petrova Irina Max-Planck-Institute for Meteorology, 20146, KlimaCampus, Hamburg, Germany aut Loew Alexander Department of Geography, University of Munich (LMU), Luisenstr. 37, 80333, Munich, Germany aut Marwan Norbert Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412, Potsdam, Germany aut Kurths Jürgen Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412, Potsdam, Germany aut Climate Dynamics Springer Berlin Heidelberg 45/9-10(2015-11-01), 2407-2424 0930-7575 45:9-10<2407 2015 45 382 https://doi.org/10.1007/s00382-015-2479-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00382-015-2479-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Donges Jonathan Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412, Potsdam, Germany aut NATIONALLICENCE 700 1- Petrova Irina Max-Planck-Institute for Meteorology, 20146, KlimaCampus, Hamburg, Germany aut NATIONALLICENCE 700 1- Loew Alexander Department of Geography, University of Munich (LMU), Luisenstr. 37, 80333, Munich, Germany aut NATIONALLICENCE 700 1- Marwan Norbert Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412, Potsdam, Germany aut NATIONALLICENCE 700 1- Kurths Jürgen Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412, Potsdam, Germany aut NATIONALLICENCE 773 0- Climate Dynamics Springer Berlin Heidelberg 45/9-10(2015-11-01), 2407-2424 0930-7575 45:9-10<2407 2015 45 382