Scheme: Wolfson Research Merit Awards
Organisation: University of Exeter
Dates: May 2013-Apr 2018
Summary: My research is focused on identifying potential ‘tipping points’ leading to abrupt climate change, developing early warning methods for them, and exploring how this knowledge should affect policy.
It is often assumed that climate tipping points are unpredictable, but my research has shown that they do carry some useful predictability. The computer models used to project future climate change generally do a poor job of capturing climate tipping points. They are unable to simulate known, past abrupt climate changes, and they failed to forecast the recent acceleration of climate change in the Arctic. These weaknesses of current models led me to take a different approach to prediction, based on the theory that for a range of complex systems - including the Earth’s climate - there are quite general early warning signals before a tipping point is reached. In particular, systems become more sluggish in responding to perturbations and often exhibit greater internal variability as they approach a tipping point. This behaviour is detectable using statistical methods. Applying these methods to cases of abrupt change in Earth’s past and in climate models, has revealed that they do sometimes carry early warning signals. My aim is to use this knowledge to develop an ‘early warning system’ that helps societies pre-emptively adapt to approaching climate tipping points.
At the same time I am collaborating with economists to capture the somewhat unpredictable, ‘stochastic’ nature of tipping points in the models used to guide climate policymaking. When the likelihood and impacts of multiple, interacting climate tipping points are included in such a model, it profoundly affects the results. The optimal policy response becomes an immediate high price on CO2 emissions (>$100/tCO2) and a decarbonisation of the global economy by 2050, restricting global warming to 1.5C in an effort to avoid irreversible, damaging tipping points.