## Browse content

### Table of contents

#### Actions for selected chapters

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- Book chapterAbstract only
#### Chapter 1 - Introduction

Pages 1-4 - Book chapterAbstract only
#### Chapter 2 - Overview of Linear Algebra

Pages 5-27 - Book chapterAbstract only
#### Chapter 3 - Univariate Distribution Theory

Pages 29-124 - Book chapterAbstract only
#### Chapter 4 - Multivariate Distribution Theory

Pages 125-161 - Book chapterAbstract only
#### Chapter 5 - Introduction to Calculus of Variation

Pages 163-196 - Book chapterAbstract only
#### Chapter 6 - Introduction to Control Theory

Pages 197-234 - Book chapterAbstract only
#### Chapter 7 - Optimal Control Theory

Pages 235-272 - Book chapterAbstract only
#### Chapter 8 - Numerical Solutions to Initial Value Problems

Pages 273-315 - Book chapterAbstract only
#### Chapter 9 - Numerical Solutions to Boundary Value Problems

Pages 317-360 - Book chapterAbstract only
#### Chapter 10 - Introduction to Semi-Lagrangian Advection Methods

Pages 361-441 - Book chapterAbstract only
#### Chapter 11 - Introduction to Finite Element Modeling

Pages 443-482 - Book chapterAbstract only
#### Chapter 12 - Numerical Modeling on the Sphere

Pages 483-554 - Book chapterAbstract only
#### Chapter 13 - Tangent Linear Modeling and Adjoints

Pages 555-598 - Book chapterAbstract only
#### Chapter 14 - Observations

Pages 599-626 - Book chapterAbstract only
#### Chapter 15 - Non-variational Sequential Data Assimilation Methods

Pages 627-671 - Book chapterAbstract only
#### Chapter 16 - Variational Data Assimilation

Pages 673-703 - Book chapterAbstract only
#### Chapter 17 - Subcomponents of Variational Data Assimilation

Pages 705-751 - Book chapterAbstract only
#### Chapter 18 - Observation Space Variational Data Assimilation Methods

Pages 753-763 - Book chapterAbstract only
#### Chapter 19 - Kalman Filter and Smoother

Pages 765-782 - Book chapterAbstract only
#### Chapter 20 - Ensemble-Based Data Assimilation

Pages 783-821 - Book chapterAbstract only
#### Chapter 21 - Non-Gaussian Variational Data Assimilation

Pages 823-868 - Book chapterAbstract only
#### Chapter 22 - Markov Chain Monte Carlo and Particle Filter Methods

Pages 869-885 - Book chapterAbstract only
#### Chapter 23 - Applications of Data Assimilation in the Geosciences

Pages 887-916 - Book chapterNo access
#### Chapter 24 - Solutions to Select Exercise

Pages 917-922 - Book chapterNo access
#### Bibliography

Pages 923-939 - 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