Stochastic Bifurcation of the North Atlantic Circulation under a Midrange Future Climate Scenario with the NASA-GISS ModelE

Abstract A 10-member ensemble simulation with the NASA GISS-E2-1-G climate model shows a clear bifurcation in the Atlantic meridional overturning circulation (AMOC) strength under the SSP2–4.5 extended scenario. At 26°N, the bifurcation leads to 8 strong AMOC and 2 much weaker AMOC states, while at 48°N, it leads to 8 stable AMOC-on and 2 nearly AMOC-off states, the latter lasting approximately 800 years. A variety of fully coupled models have demonstrated tipping points in AMOC through hosing experiments, i.e., prescribing sufficient freshwater inputs in the subpolar North Atlantic. In the GISS simulations, there are no external freshwater perturbations. The bifurcation arises freely in the coupled system and is the result of stochastic variability (noise-induced bifurcation) associated with sea ice transport and melting in the Irminger Sea after a slowing of the greenhouse gas forcing. While the AMOC strength follows the near shutdown of the Labrador Sea deep convection initially, the Irminger Sea salinity and deep mixing determine the timing of the AMOC recovery or near collapse at 48°N, which varies widely across the ensemble members. Other feedbacks such as ice-albedo, ice-evaporation, E − P , and the overturning salt-advection feedback play a secondary role that may enhance or reduce the primary mechanism which is ice melt. We believe this is the first time that a coupled climate model has shown such a bifurcation across an initial condition ensemble and might imply that there is a chance for significant and prolonged AMOC slow down due to internal variability of the system. Significance Statement We believe this is the first time that divergent AMOC behavior has been reported for an ensemble of Earth system model simulations using identical climate forcing and no prescribed freshwater perturbations. This response is a manifestation of noise-induced bifurcation, enhanced by feedbacks, revealing the role stochastic (or intrinsic) variability may play in AMOC stability.