Large-Scale Atmosphere-Ocean Dynamics [Hardcover]

The lectures in this volume, first published in 2002, cover numerical weather prediction, chaotic atmospheric dynamics, atmospheric modelling.This book and its companion describe, in a language accessible to both mathematicians and meteorologists, the mathematics underpinning our understanding of large-scale atmosphere and ocean dynamics. Meteorologists understand 'weather' by identifying the dominant controlling mechanisms, and so mathematicians are deducing how such features can be described mathematically. They are discovering that geometry plays a key role in this process. These developments promise an important spin-off - improving numerical models by incorporating, using a geometric language, constraints that govern the optimal use of observationa data and the development of typical weather systems.This book and its companion describe, in a language accessible to both mathematicians and meteorologists, the mathematics underpinning our understanding of large-scale atmosphere and ocean dynamics. Meteorologists understand 'weather' by identifying the dominant controlling mechanisms, and so mathematicians are deducing how such features can be described mathematically. They are discovering that geometry plays a key role in this process. These developments promise an important spin-off - improving numerical models by incorporating, using a geometric language, constraints that govern the optimal use of observationa data and the development of typical weather systems.The complex flows in the atmosphere and oceans are believed to be accurately modeled by the Navier-Stokes equations of fluid mechanics together with classical thermodynamics. However, due to the enormous complexity of these equations, meteorologists and oceanographers have constructed approximate models of the dominant, large-scale flows that control the evolution of weather systems and that describe, for example, the dynamics of cyclones and ocean eddies. The simplifications often result in models that al$