Summary: Earth's climate is a highly complex, non-equilibrium and chaotic stochastic system. In this project, we attempt to classify its chaotic attractors with methods from non-equilibrium statistical mechanics, large deviation theory and manifold learning. For example, due to the ice albedo feedback, the climate is known to exist in two locally stable states, the current (warm) climate, and a "snowball" state, where the globe is covered in ice. Some models even suggest additional metastable climate states, such as the slushball Earth. Similarly, the currently active Atlantic Meridional Overturning Circulation (AMOC, colloquially known as Gulf Steram), transports hot water to northern Europe, but is suspected to be only metastable: If perturbed the right way, the climate would persist with the AMOC non-existent. Transitions between these climate states, and their local stability, can in principle be analyzed in light of the non-equilibrium quasipotential, characterizing the expected transition times and most likely escape paths out of the current climate state.
Relevant publications
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G. Margazoglou, T. Grafke, A. Laio, and V. Lucarini, "Dynamical Landscape and Multistability of a Climate Model", Proc. R. Soc. A 447 (2021), 2250 (link)
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Jelle Soons, Tobias Grafke, Henk A. Dijkstra, "Optimal Transition Paths for AMOC Collapse and Recovery in a Stochastic Box Model", J Physical Oceanography 54 (2024), 2537 (link)
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Jelle Soons, Tobias Grafke, Henk A. Dijkstra, "Most Likely Noise-Induced Overturning Circulation Collapse in a 2D Boussinesq Fluid Model", ArXiv (2024) (link)