Computational Fluid Dynamics workshops

Small-scale ocean mixing must be understood and represented accurately in climate models. This workshop joins mathematicians, numerical modellers, laboratory researchers, observational oceanographers and machine-learning specialists to connect mixing mechanisms with predictive parameterizations. Participants will compare theory, experiments and increasingly detailed observations, assess computational and learning approaches, and identify ways to transfer advances between disciplines. Early-career researchers will gain a broad view of the methods and collaborations needed to link mathematical descriptions to ocean behaviour.

Marking a century of Richardson’s work on turbulent dispersion, this programme compares Lagrangian and Eulerian approaches, stochastic and deterministic models, particle dynamics and continuum descriptions. Topics include multiparticle dispersion, experimental particle tracking, geophysical transport, spontaneous stochasticity, mixing, and machine-learning methods for closure and inference. The programme connects theory, simulation and experiment with environmental and climate prediction. It targets doctoral students, postdocs and established researchers in turbulence and transport; exceptional master’s students may be considered. Accommodation is provided for outstation participants.