Data Assimilation for the Geosciences
eBook - ePub

Data Assimilation for the Geosciences

From Theory to Application

  1. 976 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Data Assimilation for the Geosciences

From Theory to Application

About this book

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. - 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

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Yes, you can access Data Assimilation for the Geosciences by Steven J. Fletcher in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Geophysics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Elsevier
Year
2017
Print ISBN
9780128044445

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Chapter 1: Introduction
  6. Chapter 2: Overview of Linear Algebra
  7. Chapter 3: Univariate Distribution Theory
  8. Chapter 4: Multivariate Distribution Theory
  9. Chapter 5: Introduction to Calculus of Variation
  10. Chapter 6: Introduction to Control Theory
  11. Chapter 7: Optimal Control Theory
  12. Chapter 8: Numerical Solutions to Initial Value Problems
  13. Chapter 9: Numerical Solutions to Boundary Value Problems
  14. Chapter 10: Introduction to Semi-Lagrangian Advection Methods
  15. Chapter 11: Introduction to Finite Element Modeling
  16. Chapter 12: Numerical Modeling on the Sphere
  17. Chapter 13: Tangent Linear Modeling and Adjoints
  18. Chapter 14: Observations
  19. Chapter 15: Non-variational Sequential Data Assimilation Methods
  20. Chapter 16: Variational Data Assimilation
  21. Chapter 17: Subcomponents of Variational Data Assimilation
  22. Chapter 18: Observation Space Variational Data Assimilation Methods
  23. Chapter 19: Kalman Filter and Smoother
  24. Chapter 20: Ensemble-Based Data Assimilation
  25. Chapter 21: Non-Gaussian Variational Data Assimilation
  26. Chapter 22: Markov Chain Monte Carlo and Particle Filter Methods
  27. Chapter 23: Applications of Data Assimilation in the Geosciences
  28. Chapter 24: Solutions to Select Exercise
  29. Bibliography
  30. Index