Cover for Data Assimilation for the Geosciences

Data Assimilation for the Geosciences

From Theory to Application

Book2017

Author:

Steven J. Fletcher

Data Assimilation for the Geosciences

From Theory to Application

Book2017

 

Cover for Data Assimilation for the Geosciences

Author:

Steven J. Fletcher

About the book

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Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical,statistical, and probability background knowledge needed to formulate data ... read full description

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  2. Book chapterAbstract only

    Chapter 1 - Introduction

    Pages 1-4

  3. Book chapterAbstract only

    Chapter 2 - Overview of Linear Algebra

    Pages 5-27

  4. Book chapterAbstract only

    Chapter 3 - Univariate Distribution Theory

    Pages 29-124

  5. Book chapterAbstract only

    Chapter 4 - Multivariate Distribution Theory

    Pages 125-161

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    Chapter 5 - Introduction to Calculus of Variation

    Pages 163-196

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    Chapter 6 - Introduction to Control Theory

    Pages 197-234

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    Chapter 7 - Optimal Control Theory

    Pages 235-272

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    Chapter 8 - Numerical Solutions to Initial Value Problems

    Pages 273-315

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    Chapter 9 - Numerical Solutions to Boundary Value Problems

    Pages 317-360

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    Chapter 10 - Introduction to Semi-Lagrangian Advection Methods

    Pages 361-441

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    Chapter 11 - Introduction to Finite Element Modeling

    Pages 443-482

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    Chapter 12 - Numerical Modeling on the Sphere

    Pages 483-554

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    Chapter 13 - Tangent Linear Modeling and Adjoints

    Pages 555-598

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    Chapter 14 - Observations

    Pages 599-626

  16. Book chapterAbstract only

    Chapter 15 - Non-variational Sequential Data Assimilation Methods

    Pages 627-671

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    Chapter 16 - Variational Data Assimilation

    Pages 673-703

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    Chapter 17 - Subcomponents of Variational Data Assimilation

    Pages 705-751

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    Chapter 18 - Observation Space Variational Data Assimilation Methods

    Pages 753-763

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    Chapter 19 - Kalman Filter and Smoother

    Pages 765-782

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    Chapter 20 - Ensemble-Based Data Assimilation

    Pages 783-821

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    Chapter 21 - Non-Gaussian Variational Data Assimilation

    Pages 823-868

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    Chapter 22 - Markov Chain Monte Carlo and Particle Filter Methods

    Pages 869-885

  24. Book chapterAbstract only

    Chapter 23 - Applications of Data Assimilation in the Geosciences

    Pages 887-916

  25. Book chapterNo access

    Chapter 24 - Solutions to Select Exercise

    Pages 917-922

  26. Book chapterNo access

    Bibliography

    Pages 923-939

  27. Book chapterNo access

    Index

    Pages 941-957

About the book

Description

Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical,statistical, and probability background knowledge needed to formulate data assimilation systems in one place. It includes practical exercises for understanding theoretical formulation and presents some aspects of coding the theory with a toy problem.

The book also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to the atmosphere, oceans, as well as the land surface and other geophysical situations. It offers a comprehensive presentation of the subject, from basic principles to advanced methods, such as Particle Filters and Markov-Chain Monte-Carlo methods. Additionally, Data Assimilation for the Geosciences: From Theory to Application covers the applications of data assimilation techniques in various disciplines of the geosciences, making the book useful to students, teachers, and research scientists.

Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical,statistical, and probability background knowledge needed to formulate data assimilation systems in one place. It includes practical exercises for understanding theoretical formulation and presents some aspects of coding the theory with a toy problem.

The book also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to the atmosphere, oceans, as well as the land surface and other geophysical situations. It offers a comprehensive presentation of the subject, from basic principles to advanced methods, such as Particle Filters and Markov-Chain Monte-Carlo methods. Additionally, Data Assimilation for the Geosciences: From Theory to Application covers the applications of data assimilation techniques in various disciplines of the geosciences, making the book useful to students, teachers, and research scientists.

Key Features

  • Includes practical exercises, enabling readers to apply concepts in a theoretical formulation
  • Offers explanations for how to code certain parts of the theory
  • Presents a step-by-step guide on how, and why, data assimilation works and can be used
  • Includes practical exercises, enabling readers to apply concepts in a theoretical formulation
  • Offers explanations for how to code certain parts of the theory
  • Presents a step-by-step guide on how, and why, data assimilation works and can be used

Details

ISBN

978-0-12-804444-5

Language

English

Published

2017

Copyright

Copyright © 2017 Elsevier Inc. All rights reserved.

Imprint

Elsevier

Authors

Steven J. Fletcher

Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA