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  • State-of-the-art climate models often fail to capture non-linear, abrupt shifts in the climate system, even though such changes are observed in paleoclimate records and could occur in the future. This is likely because traditional, process-based models are built for numerical stability, and thus are not suitable for capturing rapid climate events (large amplitude – short time scale). To have confidence in both paleoclimate reconstructions and future projections, modellers and paleoclimate scientists need new tools to identify and incorporate the potential for sudden transitions. Dynamical systems theory offers a complementary alternative approach to traditional models, dealing with perturbations through simplified numerical schemes which are better suited for non-linear processes and can robustly identify and characterise tipping points. Here we test the application of dynamical systems theory to identify early warning signals (EWS) of tipping points in paleoclimate datasets. Tipping points and non-linear state transitions are documented in many paleoclimate proxy records, including those derived from ice and marine sediment cores. We use the Atlantic Meridional Overturning Circulation (AMOC) as an example of a bi-modal system to illustrate one element or process that is capable of tipping which can have cascading consequences throughout the climate system. We first identify and characterise paleoclimate records that show signals of rapid change in the AMOC or other connected climate elements. We then test a simple 1D dynamical systems model on proxy records that exhibit critical transitions to evaluate the potential for using EWS to identify tipping points before they occur. We also explore how abrupt change in the earth system can be communicated more effectively to highlight the potential for rapid changes. This is critical in the current context of continued increase in greenhouse gases emissions and the need to act urgently to mitigate catastrophic consequences of climate change. DOI: 10.21420/4ST0-4G62 Cite video as: GNS Science. 2022. Video explaining abrupt climate change_CDF2022. Lower Hutt (NZ): GNS Science. https://doi.org/10.21420/4ST0-4G62