Climate Sensitivity via a Nonparametric Fluctuation–Dissipation Theorem

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Mathematical and physical ideas for climate science (2013, background): “…response to perturbation depends critically on the choice of the observable of interest, on the length of the integrations needed for constructing the approximation of the invariant measure, and, of course, on the validity of the linear approximation (Cooper and Haynes, 2011; Cooper et al., 2013).”
Gradients are Not All You Need (2021, methodology): “Other methods make use of the Fluctuation-Dissipation Theorem with various diferent assumptions [Abramov and Majda, 2007, Cooper and Haynes, 2011].”
Toward a stochastic parameterization of ocean mesoscale eddies (2014, background): “However, the use of Gaussian distributions as forcing of non-Gaussian systems has been shown to lead to quantitative discrepancies in the system’s response (Franzke et al., 2007; Ring and Plumb, 2008; Cooper and Haynes, 2011).”