Addressing the problems of making inferences from noisy observations and imperfect theories, this 2006 book introduces many inference tools and practical applications. Starting with fundamental algebraic and statistical ideas, it is ideal for graduate students and researchers in oceanography, climate science, and geophysical fluid dynamics.

Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography, atmospheric chemistry, and extensions to other geophysical sciences. The physical complexity and the high dimensionality of geophysical systems have led the community of geophysics to make significant contributions to the fundamental theory of data assimilation. This book gathers notes from lectures and seminars given by internationally recognized scientists during a three-week school held in the Les Houches School of physics in 2012, on theoretical and applied data assimilation. It is composed of (i) a series of main lectures, presenting the fundamentals of the most commonly used methods, and the information theory background required to understand and evaluate the role of observations; (ii) a series of specialized lectures, addressing various aspects of data assimilation in detail, from the most recent developments of the theory to the specificities of various thematic applications.

Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution. It provides a framework for, and insight into, the inverse problem nature of data assimilation, emphasizing why and not just how. Methods and diagnostics are emphasized, enabling readers to readily apply them to their own field of study. Readers will find a comprehensive guide that is accessible to nonexperts; numerous examples and diverse applications from a broad range of domains, including geophysics and geophysical flows, environmental acoustics, medical imaging, mechanical and biomedical engineering, economics and finance, and traffic control and urban planning; and the latest methods for advanced data assimilation, combining variational and statistical approaches.

The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.

The essential introduction to modern physical oceanography With the advent of computers, novel instruments, satellite technology, and increasingly powerful modeling tools, we know more about the ocean than ever before. Yet we also have a new generation of oceanographers who have become increasingly distanced from the object of their study. Ever fewer scientists collect the observational data on which they base their research. Instead, many download information without always fully understanding how far removed it is from the original data, with opportunity for great misinterpretation. This textbook introduces modern physical oceanography to beginning graduate students in marine sciences and experienced practitioners in allied fields. Real observations are strongly emphasized, as are their implications for understanding the behavior of the global ocean. Written by a leading physical oceanographer, Modern Observational Physical Oceanography explains what the observational revolution of the past twenty-five years has taught us about the real, changing fluid ocean. Unlike any other book, it provides a broad and accessible treatment of the subject, covering everything from modern methods of observation and data analysis to the fluid dynamics and modeling of ocean processes and variability. Fully illustrated in color throughout, the book describes the fundamental concepts that are needed before delving into more advanced topics, including internal-inertial waves, tides, balanced motions, and large-scale circulation physics. Provides an accessible introduction to modern physical oceanography Written by a leading physical oceanographer Emphasizes real observations of the fluid ocean Features hundreds of color illustrations An online illustration package is available to professors

The World Ocean Circulation Experiment drove the development of estimates of the decadal scale time evolving general circulation that are dynamically and kinematically consistent. A long timescale, and a goal of estimation rather than prediction, preclude the use of meteorological methods called “data assimilation (DA).” Instead, “state estimation” methods are reviewed here and distinguished from DA. Results from the dynamically consistent family of solutions from the project Estimating the Circulation and Climate of the Ocean based upon least-squares Lagrange multipliers (adjoints) are used to discuss the determination of the dominant elements of the circulation in the period since 1992—which marked the beginning of the satellite altimetric record. Significant changes documented in the Arctic in recent decades now mandate consideration of the coupled ocean-cryospheric state.

This volume presents a well balanced combination of state-of-the-art theoretical results in the field of nonlinear controller and observer design, combined with industrial applications stemming from mechatronics, electrical, (bio–) chemical engineering, and fluid dynamics. The unique combination of results of finite as well as infinite–dimensional systems makes this book a remarkable contribution addressing postgraduates, researchers, and engineers both at universities and in industry. The contributions to this book were presented at the Symposium on Nonlinear Control and Observer Design: From Theory to Applications (SYNCOD), held September 15–16, 2005, at the University of Stuttgart, Germany. The conference and this book are dedicated to the 65th birthday of Prof. Dr.–Ing. Dr.h.c. Michael Zeitz to honor his life – long research and contributions on the fields of nonlinear control and observer design.

An innovative survey of large-scale ocean circulation that links observations, conceptual models, numerical models, and theories.

This book examines how large-scale processes drive centimetre-scale mixing throughout the stratified ocean. It explores the primary factors affecting mixing and turbulence, and reviews insights from laboratory studies and numerical modelling. It is an excellent reference for researchers and graduate students in oceanography and related fields.