Informing low-order models of climate tipping elements using outputs from higher-complexity Earth system models
Abstract. Crossing climate tipping points poses a rising risk under continued global warming. Yet quantitative tipping risk assessments often rely on idealised system dynamics and do not take into account Earth system model (ESM) processes. Here, we present a process-informed, updatable framework that links systematic stability assessments from comprehensive models to transparent low-order dynamical systems for three high-impact climate tipping elements (TEs): the Greenland Ice Sheet (GrIS), the West Antarctic Ice Sheet (WAIS) and the Atlantic Meridional Overturning Circulation (AMOC). We assemble TE experiments from Earth system and Earth system component models, fit element-specific dynamical systems with saddle-node bifurcations that map external forcing to state transitions, and run idealised instantaneous-forcing experiments to show the application of our framework. A simple, modular update protocol allows tipping thresholds and timescales to be revised as new simulations from ESMs become available without refitting the full framework. Applied to current ESM simulations, our emulators reproduce multistability of the GrIS and WAIS and a freshwater-forced weakening of the AMOC, yielding decision-relevant transient and equilibrium behaviour consistent with the underlying ESMs. Our approach provides a transparent bridge between comprehensive simulations and simple dynamical systems, and can be extended to additional climate tipping elements as suitable experiments become available.
The authors fit third order models, representing saddle-node bifurcations, to model data of three tipping elements; the Greenland Ice Sheet (GrIS), West Antarctic Ice Sheet (WAIS) and Atlantic Meridional Overturning Circulation (AMOC). The aim of this approach is to develop simple models representing tipping dynamics that allow for fast simulations, making them suitable for decision making.
The aim of the paper is worthwhile, however the current state does not go far beyond fitting a third order polynomial to model data. I have several suggestions/comments which I believe will strengthen this work and make it more valuable for the tipping community.
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