GDMSeminar: Abstracts of the Talks (2020/5)

Abstract: The prediction of climate change and its impact on extreme weather events is one of the great societal and intellectual challenges of our time. The first part of the problem is to make the distinction between weather and climate. The second part is to understand the dynamics of the fluctuations of the physical variables. The third part is to predict how the variances of the fluctuations are affected by statistical correlations in their fluctuating dynamics. This GDM Seminar investigates a stochastic geometric mechanics framework called LA SALT which can at least formally meet all three parts of the challenge for the problem of climate change, given a deterministic fluid theory derived from the variational principles of geometric mechanics.
References:
[1] Lorenz, E.N., Climate is what you expect. (unpublished) (1995).    http://eaps4.mit.edu/research/Lorenz/Climate_expect.pdf
[2] Holm, D.D., Variational principles for stochastic fluid dynamics. Proc. R. Soc. A 471 (2176), 20140963 (2015)   http://dx.doi.org/10.1098/rspa.2014.0963
[3] Drivas, T.D., Holm, D.D., Leahy, J.-M., Lagrangian-averaged stochastic advection by Lie transport for fluids. J. Stat. Phys. (2020)
https://doi.org/10.1007/s10955-020-02493-4
[4] Alonso-Oran, D., Bethencourt de Leon, A., Holm, D.D., Takao, S., Modelling the climate and weather of a 2D Lagrangian-averaged Euler-Boussinesq equation with transport noise. J. Stat. Phys. (2020)   https://doi.org/10.1007/s10955-019-02443-9