Data Assimilation For The Geosciences: From Theory To Application

Paperback | March 1, 2017

bySteven James Fletcher

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Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place. It includes practical exercises that enable readers to apply theory in a theoretical formulation and teaches how to code the theory with sample problems that verify understanding. The book also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to land surface, the atmosphere, oceans, and other geophysical situations. Users will find a comprehensive presentation of the subject, beginning with basic principles and then advanced methods, like Particle Filters and Monte-Carlo-Markov-Chain methods. In addition, the book covers the applications of data assimilation techniques in various disciplines of geosciences, making the book useful to students, teachers, and research scientists. Includes practical exercises, enabling readers to apply theory in a theoretical formulation Teaches users how to code theory Presents a step-by-step guide on how, and why, data assimilation works and can be used Provides all of the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place

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From the Publisher

Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place. It includes practical exercises that enable readers to apply theory in a theoretical formulation and teaches how to code the theory ...

Steven Fletcher has years of experience in Data Assimilation and has taught and researched in this area. He has published numerous journal articles and book chapters in the area. His research crosses over the disciplines of mathematics and geosciences. His research projects include Improvements to background error covariances and moist...
Format:PaperbackDimensions:600 pages, 8.75 × 6.35 × 0.68 inPublished:March 1, 2017Publisher:Elsevier Science & TechLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0128044446

ISBN - 13:9780128044445

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Table of Contents

1. Introduction to Data Assimilation 2. Statistics Overview 3. Mathematics Overview 4. Numerical Modelling 5. Tangent Linear and Adjoint Modelling 6. Observations 7. Non-Variational Based Sequential Data Assimilation Methods 8. Variational Data Assimilation (VAR DA) 9. Incremental Variational Data Assimilation 10. Variational Data Assimilation Sub-components 11. Ensemble Kalman Filters 12. Physical-space Statistical Analysis Systems (PSAS) 13. Non-Gaussian Variational Data Assimilation 14. Particle Filters and Monte-Carlo-Markov-Chain Methods 15. Summary of Applications of Data Assimilation Systems in the Geosciences