Data Assimilation for the Geosciences. From Theory to Application

✍ Scribed by Steven J. Fletcher (Auth.)

Publisher: Elsevier
Year: 2017
Tongue: English
Leaves: 949
Edition: 1st Edition
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Content:
Front Matter,CopyrightEntitled to full textChapter 1 - Introduction, Pages 1-4
Chapter 2 - Overview of Linear Algebra, Pages 5-27
Chapter 3 - Univariate Distribution Theory, Pages 29-124
Chapter 4 - Multivariate Distribution Theory, Pages 125-161
Chapter 5 - Introduction to Calculus of Variation, Pages 163-196
Chapter 6 - Introduction to Control Theory, Pages 197-234
Chapter 7 - Optimal Control Theory, Pages 235-272
Chapter 8 - Numerical Solutions to Initial Value Problems, Pages 273-315
Chapter 9 - Numerical Solutions to Boundary Value Problems, Pages 317-360
Chapter 10 - Introduction to Semi-Lagrangian Advection Methods, Pages 361-441
Chapter 11 - Introduction to Finite Element Modeling, Pages 443-482
Chapter 12 - Numerical Modeling on the Sphere, Pages 483-554
Chapter 13 - Tangent Linear Modeling and Adjoints, Pages 555-598
Chapter 14 - Observations, Pages 599-626
Chapter 15 - Non-variational Sequential Data Assimilation Methods, Pages 627-671
Chapter 16 - Variational Data Assimilation, Pages 673-703
Chapter 17 - Subcomponents of Variational Data Assimilation, Pages 705-751
Chapter 18 - Observation Space Variational Data Assimilation Methods, Pages 753-763
Chapter 19 - Kalman Filter and Smoother, Pages 765-782
Chapter 20 - Ensemble-Based Data Assimilation, Pages 783-821
Chapter 21 - Non-Gaussian Variational Data Assimilation, Pages 823-868
Chapter 22 - Markov Chain Monte Carlo and Particle Filter Methods, Pages 869-885
Chapter 23 - Applications of Data Assimilation in the Geosciences, Pages 887-916
Chapter 24 - Solutions to Select Exercise, Pages 917-922
Bibliography, Pages 923-939
Index, Pages 941-957

✦ Subjects

Home;Books & Journals;Earth and Planetary Sciences;Geophysics;Data Assimilation for the Geosciences

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