Interactions, information transfer and complex structures on the dynamics of changing climate

Methods of complex networks and graph theory, tools from information theory and synchronization of nonlinear systems will be used in development of mathematical methods and computer algorithms for analysis of high-dimensional, nonlinear time series. Spectral and Monte-Carlo Markov-Chain approaches will be used for identification of hierarchical structures and clusters in climate networks constructed from spatio-temporal fields of meteorological variables. Information flows among important clusters will be quantified using information-theoretic functionals. Structures, clusters and information flows in network representation will be confronted with known modes of climate variability and with teleconnection patterns – global communication in the Earth atmosphere. Stability of the climate system and its sensitivity to external influences (greenhouse gases, solar and geomagnetic activity) will be evaluated within the complex network paradigm. New theoretical and computational approach will help to understand natural influences and anthropogenic forcing of global change.