Early warning skill, extrapolation and tipping for accelerating cascades
Peter Ashwin, Robbin Bastiaansen, Anna S. von der Heydt, Paul Ritchie

TL;DR
This paper examines how nonlinear dynamics and system acceleration impact the reliability of early warning signals for tipping points in coupled systems, revealing limitations in extrapolation-based measures during cascades.
Contribution
It introduces a quantitative framework to assess early warning skill considering nonlinear effects and cascade acceleration in coupled systems.
Findings
Early warnings can be unreliable during accelerating cascades.
Extrapolation breakdown shortens warning timescales.
Downstream tipping often occurs with limited warning time.
Abstract
We investigate how nonlinear behaviour (both of forcing in time and of the system itself) can affect the skill of early warning signals to predict tipping in (directionally) coupled bistable systems when using measures based on critical slowing down due to the breakdown of extrapolation. We quantify the skill of early warnings with a time horizon using a receiver-operator methodology for ensembles where noise realisations and parameters are varied to explore the role of extrapolation and how it can break down. We highlight cases where this can occur in an accelerating cascade of tipping elements, where very slow forcing of a slowly evolving ``upstream'' system forces a more rapidly evolving ``downstream'' system. If the upstream system crosses a tipping point, this can shorten the timescale of valid extrapolation. In particular, ``downstream-within-upstream'' tipping will typically have…
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Taxonomy
TopicsCognitive Science and Education Research
