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Computational Methods for Data Evaluation and Assimilation

Computational Methods for Data Evaluation and Assimilation

Computational Methods for Data Evaluation and Assimilation Hardback - 2013

by Dan Gabriel Cacuci

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Hardcover. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; 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 exper
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Details

  • Title Computational Methods for Data Evaluation and Assimilation
  • Author Dan Gabriel Cacuci
  • Binding Hardback
  • Edition INDIAN EDITIONS
  • Condition New
  • Pages 374
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2013-08-15
  • Features Bibliography, Index
  • Bookseller's Inventory # ria9781584887355_inp
  • ISBN 9781584887355 / 1584887354
  • Weight 1.45 lbs (0.66 kg)
  • Dimensions 9.3 x 6.2 x 1 in (23.62 x 15.75 x 2.54 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Category Mathematics
  • Library of Congress subjects Multivariate analysis, Analysis of covariance
  • Library of Congress Catalogue Number 2013026450
  • Dewey Decimal Code 518
  • Quantity available 407

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Reader reviews for Computational Methods for Data Evaluation and Assimilation

From the publisher

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
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