On the robustness of Early Warning Indicators

Early warning indicators (EWIs) of tipping points are typically derived from insights gained from simple dynamical systems. Whether these indicators provide robust and reliable warnings when applied to the climate system remains an open question. In this study, we use climate models with known tipping points to investigate the behavior of classical EWIs associated with increasing memory and variance. In addition, we explore an alternative EWI based on changes in spatial correlations.

A key challenge in applying EWIs is determining when a change is significant enough to constitute a warning. How large must a deviation be relative to background variability? How should this background variability be defined—using an early segment of the simulation or an unforced control experiment? How much temporal smoothing should be applied to the indicators? And what is the associated risk of false positives?

We address these questions for several tipping elements, including the Atlantic Meridional Overturning Circulation (AMOC), the subpolar gyre region, and sea ice. Our analysis is based on simulations from both the CMIP6 ensemble and the OptimESM/TipESM ensembles.

Our results indicate that EWIs are generally sensitive to methodological choices and, in some cases, exhibit significant changes only after the tipping point has occurred.