Computation of the AMOC collapse probability using a rare-event algorithm

The Atlantic Meridional Overturning Circulation (AMOC) transports warm, saline water towards the northern North Atlantic, contributing substantially to the meridional heat transport in the climate system. Measurements of the Atlantic freshwater divergence show that the AMOC may be in a bistable state and hence subject to collapsing under anthropogenic greenhouse gas forcing. We aim at computing the probability of such a transition, focusing on time scales up to the end of this century.  

Simulating trajectories in a climate model is very expensive. To minimize the amount of data required to compute the probability of such rare AMOC transitions, we use a rare-events algorithm called TAMS (Trajectory-Adaptive Multilevel Sampling), that encourages the transition without changing the statistics. In TAMS, N trajectories are simulated and evaluated with a score function; the poorest-performing trajectories are discarded, and the best ones are re-simulated.

The optimal score function is the committor function, defined as the probability that a trajectory reaches a zone A of the phase space before another zone B. To avoid the difficulties raised by its exact computation, we estimate it using a feedforward neural network. Because of the expense of simulating data in a climate model, we also minimize the amount of data needed to train the neural network by reusing data processed through TAMS.

As a first step, using simulated data from an idealized stochastic AMOC model, where forcing and white noise are applied via a surface freshwater flux, we compute the transition probabilities versus noise and forcing amplitudes. Then, we apply the same protocol to compute these transition probabilities in the much more sophisticated climate model FAMOUS. This model is a coarse resolution Atmosphere-Ocean General Circulation Model that has been shown to exhibit a collapse of the AMOC via hosing experiments. In this new setup, we compute once again the transition probabilities of the AMOC versus noise and forcing, where the forcing amplitude is a hosing flux, and the atmosphere dynamics plays the role of the noise.