Using natural archives to detect climate and environmental tipping points in the Earth System

'Tipping points' in the Earth system are characterised by a nonlinear response to gradual forcing, and may have severe and wide-ranging impacts. Many abrupt events result from simple underlying system dynamics termed 'critical transitions' or 'bifurcations'. One of the best ways to identify and potentially predict threshold behaviour in the climate system is through analysis of natural ('palaeo') archives. Specifically, on the approach to a tipping point, early warning signals can be detected as characteristic fluctuations in a time series as a system loses stability. Testing whether these early warning signals can be detected in highly complex real systems is a key challenge, since much work is either theoretical or only tested with simple models. This is particularly problematic in palaeoclimate and palaeoenvironmental records with low resolution, non-equidistant data, which can limit accurate analysis. Here, a range of different datasets are examined to explore generic rules that can be used to detect such dramatic events. A number of key criteria are identified to be necessary for the reliable identification of early warning signals in natural archives, most crucially, the need for a low-noise record of sufficient data length, resolution and accuracy. A deeper understanding of the underlying system dynamics is required to inform the development of more robust system-specific indicators, or to indicate the temporal resolution required, given a known forcing. This review demonstrates that time series precursors from natural archives provide a powerful means of forewarning tipping points within the Earth System. (C) 2016 Elsevier Ltd. All rights reserved.