The Role of Internal Climate Variability in Noise-Shaped Hysteresis Cycles of the AMOC Under Rising CO2 Forcing

The Atlantic Meridional Overturning Circulation (AMOC), is a key tipping element of the climate system. A tipping point typically results from the interplay between external forcing (such as increased GHGs concentration or freshwater input) and the intrinsic internal variability of the system. While most studies mainly focus on identifying a critical forcing threshold (i.e. the minimal CO2 concentration or anomaly freshwater input needed for the collapse), the role of the internal climate variability remains less explored. Investigating the role of the internal variability requires performing large ensemble simulations which are  typically unfeasible with state-of-the-art models and traditional approaches. In our study, using an intermediate complexity model (PlaSIM-LSG, T21), once we assessed noise-induced collapse with a rare event algorithm, we investigated at which extent climate variability affects AMOC stability when CO2 forcing is applied. Traditionally, the AMOC stability landscape is investigated using single-realization hysteresis diagrams, driven by freshwater input in the North Atlantic. However, the effects of gradual CO2 forcing and, in particular, the impact of internal climate variability on the timing of AMOC tipping points have been less studied.  We conducted three independent hysteresis simulations, applying a slow CO2 ramp-up and ramp-down (0.2 ppm/year). Our findings reveal that internal variability strongly affects the timing of the AMOC tipping and the shape of the hysteresis cycle. In one simulation, we observed a reversed cycle, where the AMOC recovers at higher CO2 levels than at collapse. While statistical Early Warning Signals (EWS) provide some indication of approaching tipping points, the internal variability considerably reduces their predictability and introduces false positives. This suggests that AMOC behavior, when internal climate variability is considered, can differ significantly from characteristics of simpler models, and that caution is needed when interpreting results from a single-experiment realization. Moreover, the role of internal climate variability suggests that a probabilistic approach is necessary to define AMOC’s “safe operating space”, since it might not be possible to define a single critical CO2 threshold to prevent AMOC collapse.