Computational Methods for Data Evaluation and Assimilation

Dan Gabriel Cacuci

ISBN 10: 1584887354 / ISBN 13: 9781584887355

Published by Chapman And Hall/CRC, 2013

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - This self-contained book presents interdisciplinary methods for integrating experimental and computational information in many scientific and engineering areas. It 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. 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.

Seller Inventory # 9781584887355

Bibliographic Details

• Title: Computational Methods for Data Evaluation and Assimilation
• Publisher: Chapman And Hall/CRC
• Publication Date: 2013
• Language: English
• ISBN 10: 1584887354
• ISBN 13: 9781584887355
• Binding: Buch
• Condition: Neu
• Dimensions: 240W x 161H x 25D millimeters 240 millimeters width by 161 millimeters height by 25 millimeters depth
• Weight: 728 grams

About this title

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 the Author

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