Data Assimilation for the Geosciences

Data Assimilation for the Geosciences: From Theory to Application, Second Edition brings together all of the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place. It includes practical exercises enabling readers to apply theory in both a theoretical formulation as well as teach them how to code the theory with toy problems to verify their understanding. It also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to land surface, the atmosphere, ocean and other geophysical situations. The second edition of Data Assimilation for the Geosciences has been revised with up to date research that is going on in data assimilation, as well as how to apply the techniques. The new edition features an introduction of how machine learning and artificial intelligence are interfacing and aiding data assimilation. In addition to appealing to students and researchers across the geosciences, this now also appeals to new students and scientists in the field of data assimilation as it will now have even more information on the techniques, research, and applications, consolidated into one source.

Autorentext
Steven J. Fletcher is a Research Scientist III at the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University, where he is the lead scientist on the development of non-Gaussian based data assimilation theory for variational, PSAS, and hybrid systems. He has worked extensively with the Naval Research Laboratory in Monterey in development of their data assimilation system, as well as working with the National Atmospheric and Oceanic Administration (NOAA)'s Environmental Prediction Centers (EMC) data assimilation system. Dr. Fletcher is extensively involved with the American Geophysical Union (AGU)'s Fall meeting planning committee, having served on the committee since 2013 as the representative of the Nonlinear Geophysics section. He has also been the lead organizer and science program committee member for the Joint Center for Satellite Data Assimilation Summer Colloquium on Satellite Data Assimilation since 2016. Dr. Fletcher is the author of Data Assimilation for the Geosciences: From Theory to Application (Elsevier, 2017). In 2017 Dr. Fletcher became a fellow of the Royal Meteorological Society.

Inhalt

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