Computational Methods for Data Evaluation and Assimilation

ISBN-13: 9781584887355 / Angielski / Twarda / 2013 / 374 str.

Dan G. Cacuci;Ionel Michael Navon;Mihaela Ionescu-Bujor

Opis

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.

Computing Methods for Data Analysis and Assimilation presents a comprehensive, up-to-date treatment of data analysis and assimilation. With practical applications from a wide range of fields, including climatology, this book introduces the optimal control mathematical framework for the data assimilation concepts of state vector, control space, observations, and departures. The authors discuss the methodologies of both time-independent three-dimensional and four-dimensional variational data assimilation. They also present the mathematical concepts and methods underlying data adjustment methodology for both static and time-dependent systems.

Spis treści

Experimental Data Evaluation: Basic Concepts. Computation of Means and Variances from Measurements. Optimization Methods for Large-Scale Data Assimilation. Basic Principles of 4D VAR. 4D VAR in Numerical Weather Prediction Models. Appendices. Bibliography. Index.

O autorze

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