University of Cambridge > Talks.cam > Applied and Computational Analysis > New averaging results motivated by climate models: fat tails, oscillations, and tipping

New averaging results motivated by climate models: fat tails, oscillations, and tipping

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We review recent results where new averaging approaches are developed and applied in the context of systems with multiple time scales and fat tails and in non-autonomous multiple scale systems with oscillatory forcing. These types of systems appear in a variety of higher dimensional climate models, as well as in other areas of application. The results open new research directions, with potential to better address questions like: which mechanisms contribute to fat-tail statistical properties appearing in (climate) data? What are reasonable approximations for multiple scale systems with non-Gaussian behaviour? How can these approximations provide insight into the dynamics of larger models, such as parameter ranges with large variability, tipping, or reversibility? Some areas for further research are discussed.

This talk is part of the Applied and Computational Analysis series.

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