Teaching

Covers the equations used in atmosphere and climate modelling and their scale analysis; numerical discretization (horizontal, vertical, and time) of governing equations for mass, momentum, and energy conservation; finite difference and finite volume schemes; semi-Lagrangian techniques; spectral methods and Galerkin projection; modelling of sub-grid scale processes such as cumulus parameterization; and special topics including emerging computational architectures and data-driven/hybrid approaches.

An introduction to nonlinear dynamics — linearization, bifurcation, and chaos — including model reduction and Galerkin projection. Develops and analyzes low-order models drawn from across the climate system, such as Rayleigh–Bénard convection, atmospheric general circulation, ocean thermohaline circulation, planetary dynamos, energy balance and global warming, ice sheets, ENSO, the carbon cycle, and examples from paleoclimate. Special topics include data-driven methods and dynamics on networks.