Technical note: Characterising and comparing different palaeoclimates with dynamical systems theory

Numerical climate simulations produce vast amounts of high-resolution data. This poses new challenges to the palaeoclimate community - and indeed to the broader climate community - in how to efficiently process and interpret model output. The palaeoclimate community also faces the additional challenge of having to characterise and compare a much broader range of climates than encountered in other subfields of climate science. Here we propose an analysis framework, grounded in dynamical systems theory, which may contribute to overcoming these challenges. The framework enables the characterisation of the dynamics of a given climate through a small number of metrics. These may be applied to individual climate variables or to several variables at once, and they can diagnose properties such as persistence, active number of degrees of freedom and coupling. Crucially, the metrics provide information on instantaneous states of the chosen variable(s). To illustrate the framework's applicability, we analyse three numerical simulations of mid-Holocene climates over North Africa under different boundary conditions. We find that the three simulations produce climate systems with different dynamical properties, such as persistence of the spatial precipitation patterns and coupling between precipitation and large-scale sea level pressure patterns, which are reflected in the dynamical systems metrics. We conclude that the dynamical systems framework holds significant potential for analysing palaeoclimate simulations. At the same time, an appraisal of the framework's limitations suggests that it should be viewed as a complement to more conventional analyses, rather than as a wholesale substitute.

Automated summary

Numerical climate simulations produce vast amounts of data, posing challenges to efficiently process and interpret model output. The proposed analysis framework based on dynamical systems theory characterizes climate dynamics through a small number of metrics, providing information on properties such as persistence and coupling. Analyzing three mid-Holocene climate simulations, it was found that they exhibit different dynamical properties, highlighting the potential of the framework for analyzing paleoclimate simulations.