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 demand for oil and gas has brought exploration and production to unprecedented depths of the world’s oceans. Currently, over 50% of the oil from the Gulf of Mexico now comes from waters in excess of 1,500 meters (one mile) deep, where no oil was produced just 20 years ago. The Deepwater Horizon oil spill blowout did much to change the perception of oil spills as coming just from tanker accidents, train derailments, and pipeline ruptures. In fact, beginning with the Ixtoc 1 spill off Campeche, Mexico in 1979-1980, there have been a series of large spill events originating at the sea bottom and creating a myriad of new environmental and well control challenges. This volume explores the physics, chemistry, sub-surface oil deposition and environmental impacts of deep oil spills. Key lessons learned from the responses to previous deep spills, as well as unresolved scientific questions for additional research are highlighted, all of which are appropriate for governmental regulators, politicians, industry decision-makers, first responders, researchers and students wanting an incisive overview of issues surrounding deep-water oil and gas production.

The long-term goal is to understand the physical processes that critically regulate the coupling between the oceanic and atmospheric boundary layers and develop advanced parameterizations of this interaction for a new generation of coupled ocean-atmosphere models.

This volume covers a wide range of topics and summarizes our present knowledge in ocean modeling, ocean observing systems, and data assimilation. The Global Ocean Data Assimilation Experiment (GODAE) provides a framework for these efforts: a global system of observations, communications, modeling, and assimilation that will deliver regular, comprehensive information on the state of the oceans, engendering wide utility and availability for maximum benefit to the community.

This volume contains the ten most cited articles that have appeared in the journal Atmosphere-Ocean since 1995. These articles cover a wide range of topics in meteorology, climatology and oceanography. Modelling work is represented in five papers, covering global climate model development; a cumulus parameterization scheme for global climate models; development of a regional forecast modelling system and parameterization of peatland hydraulic processes for climate models. Data rehabilitation and compilation in order to support trend analysis work on comprehensive precipitation and temperature data sets is presented in four papers. Field studies are represented by a paper on the circumpolar lead system. While the modelling studies are global in their application and applicability, the data analysis and field study papers cover environments that are specifically, but not uniquely, Canadian. This book will be of interest to researchers, students and professionals in the various sub-fields of meteorology, oceanography and climate science.

In response to the Deepwater Horizon oil spill in the Gulf of Mexico (GoM), and given the increased activities of the offshore oil industry, an international multidisciplinary consortium - the CIGOM Consortium - was funded by Mexico's Energy Secretariat (SENER) and its National Council for Science and Technology (CONACyT). Spanning 2015-2022, CIGOM's goals were to establish an environmental baseline to characterize the southern GOM’s natural variability and contribute to the understanding of ecosystem function, use cutting-edge technologies to observe the ocean, couple physical circulation and biogeochemical models to gain understating of oceanographic processes, generate oil spill scenarios using model ensembles and statistical techniques and conducting vulnerability assessments. Over 300 researchers participated in the CIGOM consortium's efforts.

The mitigation of oil spills is an important facet of environmental protection. Understanding oil spills is a first step toward preventing and minimizing their damage to the environment. This compilation presents several of the current studies related to such an understanding of oil spills and the environment.This book is a compilation of 14 papers presenting new developments in the field of oil spills, giving insight into the rapidly changing world of oil spill studies and technology. The 14 papers included cover topics varying from risk analysis to oil spill remote sensing. Broadly categorized, included are six papers on modeling, four papers on remote sensing, three papers on risk assessment, and one paper on oil spill countermeasures. Each paper presents a unique insight into a facet of oil spill research and technology. The authors of these papers represent many different countries and affiliations around the world.

Mathematical modeling of atmospheric composition is a formidable scientific and computational challenge. This comprehensive presentation of the modeling methods used in atmospheric chemistry focuses on both theory and practice, from the fundamental principles behind models, through to their applications in interpreting observations. An encyclopaedic coverage of methods used in atmospheric modeling, including their advantages and disadvantages, makes this a one-stop resource with a large scope. Particular emphasis is given to the mathematical formulation of chemical, radiative, and aerosol processes; advection and turbulent transport; emission and deposition processes; as well as major chapters on model evaluation and inverse modeling. The modeling of atmospheric chemistry is an intrinsically interdisciplinary endeavour, bringing together meteorology, radiative transfer, physical chemistry and biogeochemistry, making the book of value to a broad readership. Introductory chapters and a review of the relevant mathematics make this book instantly accessible to graduate students and researchers in the atmospheric sciences.

Atmosphere-ocean interactions and feedbacks -- A classification of coupled atmosphere-ocean models -- Conceptual models of interannual variability -- Models of intermediate complexity and ENSO prediction -- AGCMs coupled to simpler ocean models -- OGCMs coupled to simpler atmospheric models -- Atmosphere-ocean coupled general circulation models -- Coupling software and technologies -- Coupling algorithms and specific coupling features in CGCMs.