Climate Response Using a Three-Dimensional Operator Based on the Fluctuation–Dissipation Theorem

By A. Gritsun, Grant Branstator. 2007

164 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/fa47cb6cb8eb60fb736d38cb55c721bb22d9de98

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Citations in the corpus

Challenges in Climate Science and Contemporary Applied Mathematics (2012, methodology): “The explicit form of the PDF, p eq (x), allows one to calculate explicit forms of the ideal response operator to perturbations in forcing, F , or the dissipation parameter , a, as well as explicit analytic expressions for the FDT linear response operator and various approximations [102].”
Blended response algorithms for linear fluctuation-dissipation for complex nonlinear dynamical systems (2007, methodology): “Gritsoun and Branstator [9], and Gritsoun, Branstator and Majda [11] for computing the response of the mean state and variance, respectively, have applied the quasi-Gaussian approximation to a comprehensive general circulation model with interesting results.”
Normal forms for reduced stochastic climate models (2009, methodology): “Reduced models can also be used for climate sensitivity and climate change studies via the fluctuation dissipation theorem (FDT) (4, 9, 10).”
Intermodel variability of the poleward shift of the austral jet stream in the CMIP3 integrations linked to biases in 20th century climatology (2010, background): “modes sufficient to capture the dynamics [Gritsun and Branstator, 2007; Majda et al., 2009]. Such an analysis is beyond the scope of this study. As discussed by Leith [1975], the simple fluctuation‐dissipation relationship suggested in Figure 1c applies only if the annular mode is uncorrelated with ”
Mathematical and physical ideas for climate science (2013, background): “…mathematical difficulty, the application of FDT, even in extremely simplified, quasiGaussian, approximation, has enjoyed a good success in climate (Gritsun and Branstator , 2007; Langen and Alexeev , 2005) even if it is clear that the ability of FDT in predicting the response to perturbation…”
Stochastic climate dynamics: Random attractors and time-dependent invariant measures (2011, background): “Recent applications of ergodic theory to the problem of climate sensitivity, in the context of deterministic models of small and intermediate complexity, include [18–22].”
A simple framework to justify linear response theory (2009, background): “Leith’s suggestion has created a lot of recent activity in generating new theoretical formulations and approximate algorithms for FDT with applications to climate response ([GD99, GBD02, GB07 , GBM08, AM07, AM08, AM09, MW09]).”