Advanced Data Assimilation For Geosciences

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Advanced Data Assimilation For Geosciences

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Author : Éric Blayo
language : en
Publisher: OUP Oxford
Release Date : 2014-10-30

Advanced Data Assimilation For Geosciences written by Éric Blayo and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-30 with Science categories.

Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography, atmospheric chemistry, and extensions to other geophysical sciences. The physical complexity and the high dimensionality of geophysical systems have led the community of geophysics to make significant contributions to the fundamental theory of data assimilation. This book gathers notes from lectures and seminars given by internationally recognized scientists during a three-week school held in the Les Houches School of physics in 2012, on theoretical and applied data assimilation. It is composed of (i) a series of main lectures, presenting the fundamentals of the most commonly used methods, and the information theory background required to understand and evaluate the role of observations; (ii) a series of specialized lectures, addressing various aspects of data assimilation in detail, from the most recent developments of the theory to the specificities of various thematic applications.

Advanced Data Assimilation For Geosciences

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Author : Marc Bocquet
language : en
Publisher: Lecture Notes of the Les Houch
Release Date : 2014

Advanced Data Assimilation For Geosciences written by Marc Bocquet and has been published by Lecture Notes of the Les Houch this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Science categories.

Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography, atmospheric chemistry, and extensions to other geophysical sciences. The physical complexity and the high dimensionality of geophysical systems have led the community of geophysics to make significant contributions to the fundamental theory of data assimilation. This book gathers notes from lectures and seminars given by internationally recognized scientists during a three-week school held in the Les Houches School of physics in 2012, on theoretical and applied data assimilation. It is composed of (i) a series of main lectures, presenting the fundamentals of the most commonly used methods, and the information theory background required to understand and evaluate the role of observations; (ii) a series of specialized lectures, addressing various aspects of data assimilation in detail, from the most recent developments of the theory to the specificities of various thematic applications.

Applications Of Data Assimilation And Inverse Problems In The Earth Sciences

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Author : Alik Ismail-Zadeh
language : en
Publisher: Cambridge University Press
Release Date : 2023-07-06

Applications Of Data Assimilation And Inverse Problems In The Earth Sciences written by Alik Ismail-Zadeh 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 2023-07-06 with Mathematics categories.

A comprehensive reference on data assimilation and inverse problems, and their applications across a broad range of geophysical disciplines, ideal for researchers and graduate students. It highlights the importance of data assimilation for understanding dynamical processes of the Earth and its space environment, and summarises recent advances.

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.

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.

Data Assimilation Fundamentals

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Author : Geir Evensen
language : en
Publisher: Springer Nature
Release Date : 2022-04-22

Data Assimilation Fundamentals written by Geir Evensen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-22 with Science categories.

This open-access textbook's significant contribution is the unified derivation of data-assimilation techniques from a common fundamental and optimal starting point, namely Bayes' theorem. Unique for this book is the "top-down" derivation of the assimilation methods. It starts from Bayes theorem and gradually introduces the assumptions and approximations needed to arrive at today's popular data-assimilation methods. This strategy is the opposite of most textbooks and reviews on data assimilation that typically take a bottom-up approach to derive a particular assimilation method. E.g., the derivation of the Kalman Filter from control theory and the derivation of the ensemble Kalman Filter as a low-rank approximation of the standard Kalman Filter. The bottom-up approach derives the assimilation methods from different mathematical principles, making it difficult to compare them. Thus, it is unclear which assumptions are made to derive an assimilation method and sometimes even which problem it aspires to solve. The book's top-down approach allows categorizing data-assimilation methods based on the approximations used. This approach enables the user to choose the most suitable method for a particular problem or application. Have you ever wondered about the difference between the ensemble 4DVar and the "ensemble randomized likelihood" (EnRML) methods? Do you know the differences between the ensemble smoother and the ensemble-Kalman smoother? Would you like to understand how a particle flow is related to a particle filter? In this book, we will provide clear answers to several such questions. The book provides the basis for an advanced course in data assimilation. It focuses on the unified derivation of the methods and illustrates their properties on multiple examples. It is suitable for graduate students, post-docs, scientists, and practitioners working in data assimilation.

Mesoscale Modelling For Meteorological And Air Pollution Applications

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Author : Ranjeet S. Sokhi
language : en
Publisher: Anthem Press
Release Date : 2018-11-15

Mesoscale Modelling For Meteorological And Air Pollution Applications written by Ranjeet S. Sokhi and has been published by Anthem Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-15 with Science categories.

‘Mesoscale Modelling for Meteorological and Air Pollution Applications’ combines the fundamental and practical aspects of mesoscale air pollution and meteorological modelling. Providing an overview of the fundamental concepts of air pollution and meteorological modelling, including parameterization of key atmospheric processes, the book also considers equally important aspects such as model integration, evaluation concepts, performance evaluation, policy relevance and user training.

Stochastic Methods For Modeling And Predicting Complex Dynamical Systems

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Author : Nan Chen
language : en
Publisher: Springer Nature
Release Date : 2023-03-13

Stochastic Methods For Modeling And Predicting Complex Dynamical Systems written by Nan Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-13 with Mathematics categories.

This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed.

Atmospheric Satellite Observations

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Author : Xiaolei Zou
language : en
Publisher: Academic Press
Release Date : 2020-03-05

Atmospheric Satellite Observations written by Xiaolei Zou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-05 with Science categories.

Atmospheric Satellite Observations: Variation Assimilation and Quality Assurance provides an invaluable reference for satellite data assimilation. Topics covered include linear algebra, frequently used statistical methods, the interpolation role of function fitting, filtering when dealing with real observations, minimization in data assimilation systems, 3D-Var and the inverse problem it solves, 4D-Var and adjoint techniques, and much more. The book concludes with satellite observation of hurricanes. - Contains mathematical concepts from several branches of study, including calculus, linear algebra, probability theory, functional analysis, and minimization - Illustrates quality assurance for satellite observations using real data examples - Includes a dedicated chapter on how different satellite instruments see hurricanes - Reviews theory, system development, and the numerical experiments of three- and four-dimensional variational data assimilation (3D-Var/4D-Var)

Mathematical Paradigms Of Climate Science

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Author : Fabio Ancona
language : en
Publisher: Springer
Release Date : 2016-11-07

Mathematical Paradigms Of Climate Science written by Fabio Ancona and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-07 with Mathematics categories.

This book, featuring a truly interdisciplinary approach, provides an overview of cutting-edge mathematical theories and techniques that promise to play a central role in climate science. It brings together some of the most interesting overview lectures given by the invited speakers at an important workshop held in Rome in 2013 as a part of MPE2013 (“Mathematics of Planet Earth 2013”). The aim of the workshop was to foster the interaction between climate scientists and mathematicians active in various fields linked to climate sciences, such as dynamical systems, partial differential equations, control theory, stochastic systems, and numerical analysis. Mathematics and statistics already play a central role in this area. Likewise, computer science must have a say in the efforts to simulate the Earth’s environment on the unprecedented scale of petabytes. In the context of such complexity, new mathematical tools are needed to organize and simplify the approach. The growing importance of data assimilation techniques for climate modeling is amply illustrated in this volume, which also identifies important future challenges.