Dynamic Data Assimilation

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Dynamic Data Assimilation

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Author : John M. Lewis
language : en
Publisher: Cambridge University Press
Release Date : 2009-12-18

Dynamic Data Assimilation written by John M. Lewis and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-18 with Mathematics categories.

Dynamic data assimilation is the assessment, combination and synthesis of observational data, scientific laws and mathematical models to determine the state of a complex physical system, for instance as a preliminary step in making predictions about the system's behaviour. The topic has assumed increasing importance in fields such as numerical weather prediction where conscientious efforts are being made to extend the term of reliable weather forecasts beyond the few days that are presently feasible. This book is designed to be a basic one-stop reference for graduate students and researchers. It is based on graduate courses taught over a decade to mathematicians, scientists, and engineers, and its modular structure accommodates the various audience requirements. Thus Part I is a broad introduction to the history, development and philosophy of data assimilation, illustrated by examples; Part II considers the classical, static approaches, both linear and nonlinear; and Part III describes computational techniques. Parts IV to VII are concerned with how statistical and dynamic ideas can be incorporated into the classical framework. Key themes covered here include estimation theory, stochastic and dynamic models, and sequential filtering. The final part addresses the predictability of dynamical systems. Chapters end with a section that provides pointers to the literature, and a set of exercises with instructive hints.

Dynamic Data Assimilation

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Author : John M. Lewis
language : en
Publisher: Cambridge University Press
Release Date : 2006-08-03

Dynamic Data Assimilation written by John M. Lewis and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-03 with Mathematics categories.

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Dynamic Data Assimilation

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Author :
language : en
Publisher:
Release Date : 2006

Dynamic Data Assimilation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with MATHEMATICS categories.

A basic one-stop reference for graduate students and researchers.

Dynamic Data Assimilation

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Author : Dinesh G. Harkut
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-10-28

Dynamic Data Assimilation written by Dinesh G. Harkut and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-28 with Computers categories.

Data assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.

Forecast Error Correction Using Dynamic Data Assimilation

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Author : Sivaramakrishnan Lakshmivarahan
language : en
Publisher: Springer
Release Date : 2016-11-02

Forecast Error Correction Using Dynamic Data Assimilation written by Sivaramakrishnan Lakshmivarahan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-02 with Computers categories.

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.

Forecast Error Correction Using Dynamic Data Assimilation

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Author : Sivaramakrishnan Lakshmivarahan
language : en
Publisher: Springer
Release Date : 2016-10-21

Forecast Error Correction Using Dynamic Data Assimilation written by Sivaramakrishnan Lakshmivarahan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-21 with Computers categories.

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 Methods Algorithms And Applications

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Author : Mark Asch
language : en
Publisher: SIAM
Release Date : 2016-12-29

Data Assimilation Methods Algorithms And Applications written by Mark Asch and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-29 with Mathematics categories.

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.

Dynamic Data Assimilation

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Author : John M Lewis
language : en
Publisher:
Release Date : 2014-05-14

Dynamic Data Assimilation written by John M Lewis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-14 with categories.

A basic one-stop reference for graduate students and researchers.

Data Assimilation For Atmospheric Oceanic And Hydrologic Applications Vol Ii

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Author : Seon Ki Park
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-05-22

Data Assimilation For Atmospheric Oceanic And Hydrologic Applications Vol Ii written by Seon Ki Park and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-22 with Science categories.

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.

Dynamic Data Driven Simulation Real Time Data For Dynamic System Analysis And Prediction

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Author : Xiaolin Hu
language : en
Publisher: World Scientific
Release Date : 2023-03-21

Dynamic Data Driven Simulation Real Time Data For Dynamic System Analysis And Prediction written by Xiaolin Hu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.

This comprehensive book systematically introduces Dynamic Data Driven Simulation (DDDS) as a new simulation paradigm that makes real-time data and simulation model work together to enable simulation-based prediction/analysis.The text is significantly dedicated to introducing data assimilation as an enabling technique for DDDS. While data assimilation has been studied in other science fields (e.g., meteorology, oceanography), it is a new topic for the modeling and simulation community.This unique reference text bridges the two study areas of data assimilation and modelling and simulation, which have been developed largely independently from each other.