Data Assimilation

The Ensemble Kalman Filter
2. Auflage 2009
ISBN: 978-3-642-42476-2
Verlag: Springer

Buch, Englisch, 307 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 505 g

This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.

Zielgruppe

Research

Autoren/Hrsg.

Evensen, Geir

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Bayesianische Inferenz
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

Statistical definitions.- Analysis scheme.- Sequential data assimilation.- Variational inverse problems.- Nonlinear variational inverse problems.- Probabilistic formulation.- Generalized Inverse.- Ensemble methods.- Statistical optimization.- Sampling strategies for the EnKF.- Model errors.- Square Root Analysis schemes.- Rank issues.- Spurious correlations, localization, and inflation.- An ocean prediction system.- Estimation in an oil reservoir simulator.

Über Autor(innen)

Geir Evensen obtained his Ph.D. in applied mathematics at the University in Bergen in 1992. Thereafter he has worked as a Research Director at the Nansen Environmental and Remote Sensing Center/Mohn-Sverdrup Center, as Prof. II at the Department of Mathematics at the University in Bergen, and as a Principal Engineer at the Hydro Research Center in Bergen. He is author or coauthor of more that 40 refereed publications related to modelling and data assimilation, and he has been the coordinator of international research projects on the development of data assimilation methodologies and systems.