Modern Approaches to Data Assimilation in Ocean Modeling
Modern Approaches to Data Assimilation in Ocean Modeling

Author: P. Malanotte-Rizzoli

Publisher: Elsevier

Published: 1996-05-10

Total Pages: 469

ISBN-13: 0080536662

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The field of oceanographic data assimilation is now well established. The main area of concern of oceanographic data assimilation is the necessity for systematic model improvement and ocean state estimation. In this respect, the book presents the newest, innovative applications combining the most sophisticated assimilation methods with the most complex ocean circulation models.Ocean prediction has also now emerged as an important area in itself. The book contains reviews of scientific oceanographic issues covering different time and space scales. The application of data assimilation methods can provide significant advances in the understanding of this subject. Also included are the first, recent developments in the forecasting of oceanic flows.Only original articles that have undergone full peer review are presented, to ensure the highest scientific quality. This work provides an excellent coverage of state-of-the-art oceanographic data assimilation.

The Ocean Circulation Inverse Problem
The Ocean Circulation Inverse Problem

Author: Carl Wunsch

Publisher: Cambridge University Press

Published: 1996-06-13

Total Pages: 466

ISBN-13: 9780521480901

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This book addresses the problem of inferring the state of the ocean circulation, from a mathematical perspective.

Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)

Author: Seon Ki Park

Publisher: Springer Science & Business Media

Published: 2013-05-22

Total Pages: 736

ISBN-13: 3642350887

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This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.

Data Assimilation
Data Assimilation

Author: Geir Evensen

Publisher: Springer Science & Business Media

Published: 2006-12-22

Total Pages: 285

ISBN-13: 3540383018

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This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.

Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)

Author: Seon Ki Park

Publisher: Springer

Published: 2016-12-26

Total Pages: 576

ISBN-13: 3319434152

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This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.

Data Assimilation for the Geosciences
Data Assimilation for the Geosciences

Author: Steven J. Fletcher

Publisher: Elsevier

Published: 2022-11-16

Total Pages: 1130

ISBN-13: 0323972535

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Data Assimilation for the Geosciences: From Theory to Application, Second Edition brings together all of the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place. It includes practical exercises enabling readers to apply theory in both a theoretical formulation as well as teach them how to code the theory with toy problems to verify their understanding. It also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to land surface, the atmosphere, ocean and other geophysical situations. The second edition of Data Assimilation for the Geosciences has been revised with up to date research that is going on in data assimilation, as well as how to apply the techniques. The new edition features an introduction of how machine learning and artificial intelligence are interfacing and aiding data assimilation. In addition to appealing to students and researchers across the geosciences, this now also appeals to new students and scientists in the field of data assimilation as it will now have even more information on the techniques, research, and applications, consolidated into one source. - Includes practical exercises and solutions enabling readers to apply theory in both a theoretical formulation as well as enabling them to code theory - Provides the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place - New to this edition: covers new topics such as Observing System Experiments (OSE) and Observing System Simulation Experiments; and expanded approaches for machine learning and artificial intelligence

Nonlinear Data Assimilation
Nonlinear Data Assimilation

Author: Peter Jan Van Leeuwen

Publisher: Springer

Published: 2015-07-22

Total Pages: 130

ISBN-13: 3319183478

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This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters. The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.

Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)

Author: Seon Ki Park

Publisher: Springer Nature

Published: 2021-11-09

Total Pages: 707

ISBN-13: 3030777227

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This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including adaptive observations, sensitivity analysis, parameter estimation and AI applications. The book is useful to individual researchers as well as graduate students for a reference in the field of data assimilation.