EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Early Warning Signals For Climate Tipping Points: Beyond White Noise

Joseph Clarke1, Chris Huntingford2, Paul Ritchie1, and Peter Cox1
Joseph Clarke et al.
  • 1Department of Mathematics,University of Exeter,Exeter,UK
  • 2UK Centre for Ecology and Hydrology, Wallingford,UK

Tipping points in the Earth System could present challenges for society and ecosystems. The existence of tipping points also provides a major challenge for science, as the global warming thresholds at which they are triggered is highly uncertain. A theory of `Early Warning Signals' has been developed to 
warn of approaching tipping points. Although this theory uses generic features of a system approaching a Tipping Point, the conventional application of it relies on an implicit assumption that the system experiences white noise forcing. In the Earth system, this assumption is frequently invalid.
Here, we extend the theory of early warning signals to a system additively forced by an autocorrelated process. We do this by considering the spectral properties of both the system and also of the forcing.  We test our method on a simple dynamical system, before applying our method to a particular example from the Earth System: Amazon rainforest dieback. Using our new approach, we successfully forewarn of modelled rainforest collapse in a state-of-the-art CMIP6 Earth System Model.

How to cite: Clarke, J., Huntingford, C., Ritchie, P., and Cox, P.: Early Warning Signals For Climate Tipping Points: Beyond White Noise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10031,, 2022.