Computational Methods for Data Evaluation and Assimilation

Dan Gabriel Cacuci

ISBN 10: 0367379619 / ISBN 13: 9780367379612

Published by Chapman And Hall/CRC, 2019

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 # 9780367379612

Bibliographic Details

• Title: Computational Methods for Data Evaluation and Assimilation
• Publisher: Chapman And Hall/CRC
• Publication Date: 2019
• Language: English
• ISBN 10: 0367379619
• ISBN 13: 9780367379612
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 234W x 156H x 20D millimeters 234 millimeters width by 156 millimeters height by 20 millimeters depth
• Weight: 570 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