Modified bifurcation diagrams to analyse the intermittency observed in local climate dynamics

Climate models excuse the grate variety of uncertainties in the observable dynamics by the complex nonlinear chaotic nature of climate, where the normal distribution remains the basis to estimate the chaotic uncertainty, and the trend estimations remains the basis to estimate regularities in climate dynamics. But, for example, the local dynamics of annual warming-cooling cycles seems to be one of the obscure points to comprehend why the annual behavior abruptly changes from year to year? The experimental bifurcation analysis to study the qualitative evolution of local climate dynamics is developed in the paper. We found on the conceptual model with a variable structure (HDS-model), where the dynamics is determined and restricted by the competition between the amplitude quantization and the time quantization. Then it becomes possible to show the different kinds of the interplay between several periodical processes in the local climate dynamics instead of chaos. Taking into account the abilities of both the fractal approach and SUC-logic to experimental bifurcation analysis, we realize the software to intelligent data processing instead of expert estimations. Then 2D parametrical diagram, 2D spacial diagram and the modified bifurcation diagrams with the revealed O-structures are built to research separately and comparatively the local climate dynamics. We introduce the notion of “likely periodicity” to describe the revealed synchronization of the bifurcation events with the sunspot cycles that seems to be the valid argument to verify the used HDS-model. So, the research concerns the computer intelligent tool to study the latent effects in local climate dynamics over centenary timescale.