Stochastic data adapted AMOC box models

The Atlantic Meridional overturning Circulation is responsible for the comparatively temperate climate found in Western Europe, and its previous collapse thought to have triggered glacial periods seen in the paleo data. This is a system that has multiple stable states- referred to as ‘on’ when the circulation is strong as in the current climate, and ‘off’ when it is much weaker. The AMOC has tipping points between these states. Tipping points occur when a rapid shift in dynamics happens in response to a relatively small change in a parameter. Making future projections of AMOC response to the climate is essential for avoiding any anthropogenic caused tipping, but it is computationally expensive to calculate the full hysteresis for different scenarios. This work looks at a conceptual five box model of the AMOC [1] which is easy to understand and cheap to implement. Previous work has considered bifurcation and rate-dependent tipping [2] of this model. This current work looks to estimate a realistic amount of noise from various GCM data sets and apply this to the model. We compare the covariance of the salinity data for a variety of CMIP6 models, and we compare the amount of noise covariance found in each data set, and how this can be input back into the box model. We perform some analysis to suggest where in the model the largest noise sources should be found.

[1] Wood, R. et.al. (2019), Climate Dynamics, 53(11), 6815-6834

[2] Alkhayuon, H. et.al. (2019), Proc. R. Soc. A, 475(2225)