North Atlantic observations sharpen meridional overturning projections.

Olson, R., S.-I. An, Y. Fan, J.P. Evans and L. Caesar
Climate Dynamics, doi: 10.1007/s00382-017-3867-7, 2017.


Atlantic Meridional Overturning Circulation (AMOC) projections are uncertain due to both model errors, as well as internal climate variability. An AMOC slowdown projected by many climate models is likely to have considerable effects on many aspects of global and North Atlantic climate. Previous studies to make probabilistic AMOC projections have broken new ground. However, they do not drift-correct or cross-validate the projections, and do not fully account for internal variability. Furthermore, they consider a limited subset of models, and ignore the skill of models at representing the temporal North Atlantic dynamics. We improve on previous work by applying Bayesian Model Averaging to weight 13 Coupled Model Intercomparison Project phase 5 models by their skill at modeling the AMOC strength, and its temporal dynamics, as approximated by the northern North-Atlantic temperature-based AMOC Index. We make drift-corrected projections accounting for structural model errors, and for the internal variability. Cross- validation experiments give approximately correct empirical coverage probabilities, which validates our method. Our results present more evidence that AMOC likely already started slowing down. While weighting considerably moderates and sharpens our projections, our results are at low end of previously published estimates. We project mean AMOC changes between periods 1960–1999 and 2060–2099 of −4.0 Sv and −6.8 Sv for RCP4.5 and RCP8.5 emissions scenarios respectively. The corresponding average 90% credible intervals for our weighted experiments are [−7.2, −1.2] and [−10.5, −3.7] Sv respectively for the two scenarios.

Key Figure

Fig. 11 Probabilistic AMOC change projections 1960–1999 to 2060–2099 [Sv] under RCP8.5 and RCP4.5 emissions scenarios for the weighted and un-weighted experiments. Red circles changes from individual models

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