Buoyancy is one of the main forces driving flows on our planet, especially in the oceans and atmosphere. These flows range from buoyant coastal currents to dense overflows in the ocean, and from avalanches to volcanic pyroclastic flows on the Earth's surface. This book brings together contributions by leading world scientists to summarize our present theoretical, observational, experimental and modeling understanding of buoyancy-driven flows. Buoyancy-driven currents play a key role in the global ocean circulation and in climate variability through their impact on deep-water formation. Buoyancy-driven currents are also primarily responsible for the redistribution of fresh water throughout the world's oceans. This book is an invaluable resource for advanced students and researchers in oceanography, geophysical fluid dynamics, atmospheric science and the wider Earth sciences who need a state-of-the-art reference on buoyancy-driven flows.

Buoyancy is one of the main forces driving flows on our planet, especially in the oceans and atmosphere. These flows range from buoyant coastal currents to dense overflows in the ocean, and from avalanches to volcanic pyroclastic flows on the Earth's surface. This book brings together contributions by leading world scientists to summarize our present theoretical, observational, experimental and modeling understanding of buoyancy-driven flows. Buoyancy-driven currents play a key role in the global ocean circulation and in climate variability through their impact on deep-water formation. Buoyancy-driven currents are also primarily responsible for the redistribution of fresh water throughout the world's oceans. This book is an invaluable resource for advanced students and researchers in oceanography, geophysical fluid dynamics, atmospheric science and the wider Earth sciences who need a state-of-the-art reference on buoyancy-driven flows.

The field of physical oceanography has matured to a point where it is now conceivable to combine numerical models and observations via data assimilation in order to provide ocean prediction products on various spatial and time scales. As a result, many nations have begun large-scale efforts to provide routine products to the oceanographic community and started to develop operational oceanography systems. The Global Ocean Data Assimilation Experiment (GODAE) provides a framework for these efforts, i.e., a global system of observations, communications, modeling, and assimilation that will deliver regular, comprehensive information on the state of the oceans, in a way that will promote and engender wide utility and availability of this resource for maximum benefit to the community. The societal benefit of this experiment will be an increased knowledge of the marine environment and ocean climate, predictive skills for societal, industrial, and commercial benefit and tactical and strategic advantage, as well as the provision of a comprehensive and integrated approach to the oceans. We therefore considered it timely, given the international context, to bring together leading scientists, system developers, and application providers to present an integrated view of oceanography. The chapters collected in this volume cover a wide range of topics and summarize our present knowledge in ocean modeling, ocean observing systems, and data assimilation.

The realism of large scale numerical ocean models has improved dra matically in recent years, in part because modern computers permit a more faithful representation of the differential equations by their algebraic analogs. Equally significant, if not more so, has been the improved under standing of physical processes on space and time scales smaller than those that can be represented in such models. Today, some of the most challeng ing issues remaining in ocean modeling are associated with parameterizing the effects of these high-frequency, small-space scale processes. Accurate parameterizations are especially needed in long term integrations of coarse resolution ocean models that are designed to understand the ocean vari ability within the climate system on seasonal to decadal time scales. Traditionally, parameterizations of subgrid-scale, high-frequency mo tions in ocean modeling have been based on simple formulations, such as the Reynolds decomposition with constant diffusivity values. Until recently, modelers were concerned with first order issues such as a correct represen tation of the basic features of the ocean circulation. As the numerical simu lations become better and less dependent on the discretization choices, the focus is turning to the physics of the needed parameterizations and their numerical implementation. At the present time, the success of any large scale numerical simulation is directly dependent upon the choices that are made for the parameterization of various subgrid processes.

The realism of large scale numerical ocean models has improved dra matically in recent years, in part because modern computers permit a more faithful representation of the differential equations by their algebraic analogs. Equally significant, if not more so, has been the improved under standing of physical processes on space and time scales smaller than those that can be represented in such models. Today, some of the most challeng ing issues remaining in ocean modeling are associated with parameterizing the effects of these high-frequency, small-space scale processes. Accurate parameterizations are especially needed in long term integrations of coarse resolution ocean models that are designed to understand the ocean vari ability within the climate system on seasonal to decadal time scales. Traditionally, parameterizations of subgrid-scale, high-frequency mo tions in ocean modeling have been based on simple formulations, such as the Reynolds decomposition with constant diffusivity values. Until recently, modelers were concerned with first order issues such as a correct represen tation of the basic features of the ocean circulation. As the numerical simu lations become better and less dependent on the discretization choices, the focus is turning to the physics of the needed parameterizations and their numerical implementation. At the present time, the success of any large scale numerical simulation is directly dependent upon the choices that are made for the parameterization of various subgrid processes.