Geir Evensen

Data Assimilation

The Ensemble Kalman Filter

• Gebundenes Buch

Produktbeschreibung

This volume covers various popular data assimilation methods. It demonstrates how the different methods can be derived from a common theoretical basis as well as how they differ and/or are related to each other, and which properties characterize them.

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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.

Produktdetails

• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 12741908, 978-3-642-03710-8
• 2nd ed.
• Seitenzahl: 332
• Erscheinungstermin: 27. August 2009
• Englisch
• Abmessung: 241mm x 160mm x 23mm
• Gewicht: 738g
• ISBN-13: 9783642037108
• ISBN-10: 3642037100
• Artikelnr.: 26817662

Autorenporträt

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.

Inhaltsangabe

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.

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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.

Rezensionen

From the reviews of the second edition:

"This is a well-written and interesting book addressed to students taking an introductory course in data assimilation and inverse methods ... . The material is presented with detail, and calculations are easy to follow. Many figures help the reader to assess the results. Several discussions and comments are provided in each chapter. In this sense, it is written in a pedagogical way. ... a reference book for researchers interested in the interpretation and implementation of advanced ensemble methods." (Jesús Marín-Solano, Mathematical Reviews, Issue 2011 c)

"Data assimilation, as defined by Geir Evensen, refers to the computation of the conditional probability distribution function of the output of a numerical model describing a dynamical process, conditioned by observations. ... the book is subdivided into seventeen chapters, which progressively introduce different aspects of data assimilation with Kalman filters. ... The book primarily addresses researchers in the field of data assimilation, for whom it represents a basic reference text. The text is very carefully written and is intended to be self-contained." (Hans Wackernagel, Mathematical Geosciences, Vol. 42, 2010)