An article in Nature Geoscience argues that current climate models are incapable of modeling the rapid changes in climate that Earth has seen in the past. This deficiency casts doubt on whether they can accurately model future tipping points.
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Critical thresholds may be inherent to the climate system. If so, they could lead to abrupt, and perhaps irreversible, changes to the Earth system. This possibility has caught the imagination of the public — often under the emotive term 'tipping points' — and has led to a huge growth in media and scientific publications on the topic in the past few years. If we are about to cross such a critical threshold, the implications for climate adaptation strategies could be significant. Likewise, knowledge of thresholds would have a strong influence on mitigation policy, not least by helping to define the meaning of the term 'dangerous climate change'.
Yet it is less clear exactly how such critical thresholds should be defined, whether they even exist and, if so, whether we are close to one. Expert elicitation is subjective. And attempts to identify early signals of catastrophic change with a variety of nonlinear system techniques are, in practice, unlikely to provide warning with sufficient lead times. Climate model simulations are the only other means for gaining advance knowledge of sudden climate change. It is therefore crucial to assess whether the available models are capable of investigating these phenomena.
I argue that climate models of the current generation, as used in the latest assessment of the Intergovernmental Panel on Climate Change (IPCC), have not proved their ability to simulate abrupt change when a critical threshold is crossed. I discuss four well-documented examples of past rapid climate change (Box 1). In two cases, the models did not adequately capture the basic climate configuration before abrupt change ensued, and in the remaining two examples, to initiate abrupt change the models needed external nudging that is up to ten times stronger than reconstructed. The models seem to be too stable.
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http://www.nature.com/ngeo/journal/v4/n7/pdf/ngeo1200.pdf