Computational Methods for Data Evaluation and Assimilation - Softcover

Cacuci, Dan Gabriel

Softcover

ISBN 10: 0367379619 ISBN 13: 9780367379612

Publisher: Routledge, 2019

Synopsis

Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdisciplinary methods for integrating experimental and computational information. This self-contained book shows how the methods can be applied in many scientific and engineering areas.

After presenting the fundamentals underlying the evaluation of experimental data, the book explains how to estimate covariances and confidence intervals from experimental data. It then describes algorithms for both unconstrained and constrained minimization of large-scale systems, such as time-dependent variational data assimilation in weather prediction and similar applications in the geophysical sciences. The book also discusses several basic principles of four-dimensional variational assimilation (4D VAR) and highlights specific difficulties in applying 4D VAR to large-scale operational numerical weather prediction models.

About this title

About the Author:

Cacuci, Dan Gabriel; Navon, Ionel Michael; Ionescu-Bujor, Mihaela

Review:

"This book, addressed to graduate students, post-graduate students, and inter-disciplinary scientist, focuses on computational techniques used to experimental data evaluation and assimilation. The theory is illustrated with examples belonging to many scientific and engineering domains."
--Florin Gorunescu, in Zentralblatt MATH 1283

About this edition

• Publisher: Routledge
• Publication date: 2019
• ISBN 10: 0367379619
• ISBN 13: 9780367379612
• Binding: Paperback
• Edition number: 1
• Number of pages: 376