This book addresses the problem of inferring the state of ocean circulation, understanding it dynamically, and forecasting it through a quantitative combination of theory and observation. It focuses on so-called inverse methods and related methods of statistical inference. The author considers both time-independent and time-dependent problems, including Gauss-Markov estimation, sequential estimators and adjoint/Pontryagin principle methods. This book is intended for use as a graduate level text for students of oceanography and related fields. It will also be of interest to working physical oceanographers.

The problems of making inferences about the natural world from noisy observations and imperfect theories occur in almost all scientific disciplines. This 2006 book addresses these problems using examples taken from geophysical fluid dynamics. It focuses on discrete formulations, both static and time-varying, known variously as inverse, state estimation or data assimilation problems. Starting with fundamental algebraic and statistical ideas, the book guides the reader through a range of inference tools including the singular value decomposition, Gauss-Markov and minimum variance estimates, Kalman filters and related smoothers, and adjoint (Lagrange multiplier) methods. The final chapters discuss a variety of practical applications to geophysical flow problems. Discrete Inverse and State Estimation Problems is an ideal introduction to the topic for graduate students and researchers in oceanography, meteorology, climate dynamics, and geophysical fluid dynamics. It is also accessible to a wider scientific audience; the only prerequisite is an understanding of linear algebra.

The problem of ocean acoustic tomography is to infer from precise measurements of travel time, or other properties of acoustic propagation, the state of the ocean traversed by a sound field. Tomography takes advantage of two facts: that travel time and other measurable acoustic parameters are functions of temperature, water velocity, and other parameters of oceanographic interest, and can be interpreted to provide information about the intervening ocean using inverse methods; and that the ocean is virtually transparent to low-frequency sound, so that signals can be transmitted over distances of many thousands of kilometres. It is therefore possible to prepare a practical system of transmitters and receivers to interpret the behaviour of the oceans. This book gives a comprehensive presentation of the underlying oceanography and mathematics necessary to understand and develop such a system. It covers the forward and inverse tomography problem, as well as numerous models for data interpretation. Also included is an epilogue outlining the history of tomographic techniques. It should prove a valuable resource to oceanographers and climatologists, as well as applied mathematicians and engineers interested in applications of fluid mechanics tools.