Climate tipping as a noisy bifurcation: a predictive technique

TL;DR

This paper introduces a novel stochastic analysis method to predict climate tipping points by fitting models to data, estimating tipping probabilities, and applying it to both simulation and real ice-core data.

Contribution

It presents a new technique for analyzing climate tipping points as noisy bifurcations, enabling probabilistic predictions from observational data.

Findings

Successfully applied to simulation data of past climate transition.

Provided probabilistic estimates for the end of recent glaciation.

Demonstrated the method's potential for real-world climate tipping point prediction.

Abstract

It is often known, from modelling studies, that a certain mode of climate tipping (of the oceanic thermohaline circulation, for example) is governed by an underlying fold bifurcation. For such a case we present a scheme of analysis that determines the best stochastic fit to the existing data. This provides the evolution rate of the effective control parameter, the variation of the stability coefficient, the path itself and its tipping point. By assessing the actual effective level of noise in the available time series, we are then able to make probability estimates of the time of tipping. This new technique is applied, first, to the output of a computer simulation for the end of greenhouse Earth about 34 million years ago when the climate tipped from a tropical state into an icehouse state with ice caps. Second, we use the algorithms to give probabilistic tipping estimates for the end of the most recent glaciation of the Earth using actual archaeological ice-core data.