Principles Of Data Assimilation
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Principles Of Data Assimilation
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Author : Seon Ki Park
language : en
Publisher: Cambridge University Press
Release Date : 2022-09-29
Principles Of Data Assimilation written by Seon Ki Park 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 2022-09-29 with Nature categories.
A unique combination of both theoretical and practical aspects of data assimilation with examples and exercises for students.
Principles Of Data Assimilation
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Author : Seon Ki Park
language : en
Publisher: Cambridge University Press
Release Date : 2022-09-29
Principles Of Data Assimilation written by Seon Ki Park 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 2022-09-29 with Science categories.
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.
Land Surface Observation Modeling And Data Assimilation
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Author : Shunlin Liang
language : en
Publisher: World Scientific
Release Date : 2013
Land Surface Observation Modeling And Data Assimilation written by Shunlin Liang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Science categories.
This book is unique in its ambitious and comprehensive coverage of earth system land surface characterization, from observation and modeling to data assimilation, including recent developments in theory and techniques, and novel application cases. The contributing authors are active research scientists, and many of them are internationally known leading experts in their areas, ensuring that the text is authoritative.This book comprises four parts that are logically connected from data, modeling, data assimilation integrating data and models to applications. Land data assimilation is the key focus of the book, which encompasses both theoretical and applied aspects with various novel methodologies and applications to the water cycle, carbon cycle, crop monitoring, and yield estimation.Readers can benefit from a state-of-the-art presentation of the latest tools and their usage for understanding earth system processes. Discussions in the book present and stimulate new challenges and questions facing today''s earth science and modeling communities.
The Statistical Physics Of Data Assimilation And Machine Learning
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Author : Henry D. I. Abarbanel
language : en
Publisher: Cambridge University Press
Release Date : 2022-02-17
The Statistical Physics Of Data Assimilation And Machine Learning written by Henry D. I. Abarbanel 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 2022-02-17 with Computers categories.
The theory of data assimilation and machine learning is introduced in an accessible manner for undergraduate and graduate students.
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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Data Assimilation For The Geosciences
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Author : Steven J. Fletcher
language : en
Publisher: Elsevier
Release Date : 2022-11-16
Data Assimilation For The Geosciences written by Steven J. Fletcher and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-16 with Science categories.
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
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.
Data Assimilation
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Author : William Lahoz
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-23
Data Assimilation written by William Lahoz 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 2010-07-23 with Science categories.
Data assimilation methods were largely developed for operational weather forecasting, but in recent years have been applied to an increasing range of earth science disciplines. This book will set out the theoretical basis of data assimilation with contributions by top international experts in the field. Various aspects of data assimilation are discussed including: theory; observations; models; numerical weather prediction; evaluation of observations and models; assessment of future satellite missions; application to components of the Earth System. References are made to recent developments in data assimilation theory (e.g. Ensemble Kalman filter), and to novel applications of the data assimilation method (e.g. ionosphere, Mars data assimilation).
Handbook Of Dynamic Data Driven Applications Systems
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Author : Frederica Darema
language : en
Publisher: Springer Nature
Release Date : 2023-09-14
Handbook Of Dynamic Data Driven Applications Systems written by Frederica Darema and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-14 with Computers categories.
This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Computational And Information Technologies In Science Engineering And Education
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Author : Yuri Shokin
language : en
Publisher: Springer
Release Date : 2019-02-20
Computational And Information Technologies In Science Engineering And Education written by Yuri Shokin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-20 with Computers categories.
This book constitutes the refereed proceedings of the 9th International Conference on Computational and Information Technologies in Science, Engineering and Education, CITech 2018, held in Ust-Kamenogorsk, Kazakhstan, in September 2018. The 25 revised full papers presented were carefully reviewed and selected from 64 submissions. The papers address issues such as mathematical and computer modeling, fundamental problems of mathematics, technological aspects of the applications of parallel computer systems, high level parallel programming languages and systems.