Anatomy and predictability of tipping points in the high-dimensional climate system

Tipping points (TPs) are usually understood as bifurcations due to a slow parameter shift in a bistable system, where the system's state is diffusing around a fixed point in an underlying climate potential. As the shape of the climate potential changes towards the bifurcation, universal early-warning signals (EWS) due to critical slowing down appear.

How reliable is it to transfer this conceptual view to high-level risk assessments of climate change? We set out to test the anatomy and predictability of TPs in the complex system of the global ocean circulation, where changes in ice melt is a control parameter. Several findings highlight the need for more realistic methods to address the risk of TP:

1. The critical threshold of the control parameter can be fuzzy due to sensitive dependence on initial conditions and rate of non-adiabatic forcing changes.

2. In this spatially extended system, there is a high degree of multistability. This leads to a multitude of critical thresholds and abrupt changes in deterministic variability, which can interfer with EWS stemming from noise-driven fluctuations.

3. The universality of EWS in the high-dimensional case is compromised in practise, which may be mitigated by deriving system-specific observables from the properties of an edge state related to the TP.