The mathematical theory of nonautonomous and random dynamical systems (NDSs and RDSs) is the proper framework to study the effects of time-dependent forcing, both anthropogenic and natural, on the intrinsic variability of the climate system. We will examine the ways in which such forcing changes not just the means (i.e., the warming) but also the higher moments of climatic fields (i.e., the weirding). Examples from atmospheric, oceanic and coupled models will be given. The role of AI emulators in the numerical study of these phenomena will be discussed. Ghil, M., 2019: A century of nonlinearity in the geosciences, Earth & Space Science, 6, 1007–1042, doi: 10.1029/2019EA000599. Ghil, M., and V. Lucarini, 2020: The physics of climate variability and climate change, Rev. Mod. Phys., 92(3), 035002, doi: 10.1103/RevModPhys.92.035002.
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