  We use the extension of the method of recurrence plots to cross recurrence
plots (CRP) which enables a nonlinear analysis of bivariate data. To quantify
CRPs, we develop further three measures of complexity mainly basing on diagonal
structures in CRPs. The CRP analysis of prototypical model systems with
nonlinear interactions demonstrates that this technique enables to find these
nonlinear interrelations from bivariate time series, whereas linear correlation
tests do not. Applying the CRP analysis to climatological data, we find a
complex relationship between rainfall and El Nino data.
