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

By Rachel Kuske

University of British Columbia, Mathematics

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Abstract

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.

Joint work with: Thomas Erneux, Adam Monahan, Will Thompson, and Jielin Zhu 

This was the 4th MCRN Colloquium Webinar, on Thursday, December 3rd, 2015, 7:00pm EST.

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MCRN

Submitter

Monica Romeo

RENCI, UNC Chapel Hill

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