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

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

Author: Seon Ki Park

Publisher: Springer

Published: 2016-12-26

Total Pages: 553

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 Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)

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

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.

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

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

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.

Principles of Data Assimilation

Principles of Data Assimilation PDF

Author: Seon Ki Park

Publisher: Cambridge University Press

Published: 2022-09-29

Total Pages: 413

ISBN-13: 1108831761

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A unique combination of both theoretical and practical aspects of data assimilation with examples and exercises for students.

Principles of Data Assimilation

Principles of Data Assimilation PDF

Author: Seon Ki Park

Publisher: Cambridge University Press

Published: 2022-09-29

Total Pages: 413

ISBN-13: 1108923895

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Data assimilation is theoretically founded on probability, statistics, control theory, information theory, linear algebra, and functional analysis. At the same time, data assimilation is a very practical subject, given its goal of estimating the posterior probability density function in realistic high-dimensional applications. This puts data assimilation at the intersection between the contrasting requirements of theory and practice. Based on over twenty years of teaching courses in data assimilation, Principles of Data Assimilation introduces a unique perspective that is firmly based on mathematical theories, but also acknowledges practical limitations of the theory. With the inclusion of numerous examples and practical case studies throughout, this new perspective will help students and researchers to competently interpret data assimilation results and to identify critical challenges of developing data assimilation algorithms. The benefit of information theory also introduces new pathways for further development, understanding, and improvement of data assimilation methods.

Forecast Error Correction using Dynamic Data Assimilation

Forecast Error Correction using Dynamic Data Assimilation PDF

Author: Sivaramakrishnan Lakshmivarahan

Publisher: Springer

Published: 2016-10-21

Total Pages: 270

ISBN-13: 3319399977

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This book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)—an optimal assimilation strategy called Forecast Sensitivity Method (FSM), as an alternative to the well-known four-dimensional variational (4D-Var) data assimilation method. 4D-Var works with a forward in time prediction model and a backward in time tangent linear model (TLM). The equivalence of data assimilation via 4D-Var and FSM is proven and problems using low-order dynamics clarify the process of data assimilation by the two methods. The problem of return flow over the Gulf of Mexico that includes upper-air observations and realistic dynamical constraints gives the reader a good idea of how the FSM can be implemented in a real-world situation.

Data Assimilation and Control: Theory and Applications in Life Sciences

Data Assimilation and Control: Theory and Applications in Life Sciences PDF

Author: Axel Hutt

Publisher: Frontiers Media SA

Published: 2019-08-16

Total Pages: 116

ISBN-13: 2889459853

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The understanding of complex systems is a key element to predict and control the system’s dynamics. To gain deeper insights into the underlying actions of complex systems today, more and more data of diverse types are analyzed that mirror the systems dynamics, whereas system models are still hard to derive. Data assimilation merges both data and model to an optimal description of complex systems’ dynamics. The present eBook brings together both recent theoretical work in data assimilation and control and demonstrates applications in diverse research fields.

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