Coastal Acoustic Tomography

Coastal Acoustic Tomography
Author: Arata Kaneko
Publisher: Elsevier
Total Pages: 363
Release: 2020-02-05
Genre: Science
ISBN: 0128189428

Coastal Acoustic Tomography begins with the specifics required for designing a Coastal Acoustic Tomography (CAT) experiment and operating the CAT system in coastal seas. Following sections discuss the procedure for data analyses and various application examples of CAT to coastal/shallow seas (obtained in various locations). These sections are broken down into four kinds of methods: horizontal-slice inversion, vertical-slice inversion, modal expansion method and data assimilation. This book emphasizes how dynamic phenomena occurring in coastal/shallow seas can be analyzed using the standard method of inversion and data assimilation. The book is relevant for physical oceanographers, ocean environmentalists and ocean dynamists, focusing on the event being observed rather than the intrinsic details of observational processes. Application examples of successful dynamic phenomena measured by coastal acoustic tomography are also included. - Provides the information needed for researchers and graduate students in physical oceanography, ocean-fluid dynamics and ocean environments to apply Ocean Acoustic Tomography (OAT) to their own fields - Presents the benefits of using acoustic tomography, including less disturbance to aquatic environments vs. other monitoring methods - Includes the assimilation of CAT data into a coastal sea circulation model, a powerful tool to predict coastal-sea environmental changes

Data Assimilation: Methods, Algorithms, and Applications

Data Assimilation: Methods, Algorithms, and Applications
Author: Mark Asch
Publisher: SIAM
Total Pages: 310
Release: 2016-12-29
Genre: Mathematics
ISBN: 1611974542

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.

Data Assimilation for the Geosciences

Data Assimilation for the Geosciences
Author: Steven J. Fletcher
Publisher: Elsevier
Total Pages: 978
Release: 2017-03-10
Genre: Science
ISBN: 0128044845

Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical,statistical, and probability background knowledge needed to formulate data assimilation systems in one place. It includes practical exercises for understanding theoretical formulation and presents some aspects of coding the theory with a toy problem. The book also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to the atmosphere, oceans, as well as the land surface and other geophysical situations. It offers a comprehensive presentation of the subject, from basic principles to advanced methods, such as Particle Filters and Markov-Chain Monte-Carlo methods. Additionally, Data Assimilation for the Geosciences: From Theory to Application covers the applications of data assimilation techniques in various disciplines of the geosciences, making the book useful to students, teachers, and research scientists. Includes practical exercises, enabling readers to apply concepts in a theoretical formulation Offers explanations for how to code certain parts of the theory Presents a step-by-step guide on how, and why, data assimilation works and can be used