Discerning connectivity from dynamics in climate networks

Abstract

The bias due to dynamical memory (serial correlations) in an association/dependence measure (absolute crosscorrelation) is demonstrated in model data and identified in time series of meteorological variables used for construction of climate networks. Accounting for such bias in inferring links of the climate network markedly changes the network topology and allows to observe previously hidden phenomena in climate network evolution. © 2011 Author(s).