Data Analysis Methods In Physical Oceanography: Second And Revised Edition

Other | April 1, 2001

byThomson, Richard E., Richard E. Thomson

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Data Analysis Methods in Physical Oceanography is a practical reference
guide to established and modern data analysis techniques in earth and ocean
sciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'.

Intended for both students and established scientists, the five
major chapters of the book cover data acquisition and recording, data
processing and presentation, statistical methods and error handling,
analysis of spatial data fields, and time series analysis methods. Chapter 5
on time series analysis is a book in itself, spanning a wide diversity of
topics from stochastic processes and stationarity, coherence functions,
Fourier analysis, tidal harmonic analysis, spectral and cross-spectral
analysis, wavelet and other related methods for processing nonstationary
data series, digital filters, and fractals. The seven appendices include
unit conversions, approximation methods and nondimensional numbers used in
geophysical fluid dynamics, presentations on convolution, statistical
terminology, and distribution functions, and a number of important
statistical tables. Twenty pages are devoted to references.



Featuring:
• An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.
• A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.
• 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters.




In praise of the first edition:

"(...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)
The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers."
Aslib Book Guide Vol 63, No. 9, 1998



"(...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching."EOS Transactions, D.A. Jay, 1999



"(...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations."Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999



"(...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries."E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999

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From the Publisher

Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'.Intended for both students and e...

Format:OtherDimensions:654 pages, 1 × 1 × 1 inPublished:April 1, 2001Publisher:Elsevier Science & TechLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0080477003

ISBN - 13:9780080477008

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Table of Contents

Chapter and section headings:Preface. Acknowledgments.Data Acquisition and Recording.Introduction. Basic sampling requirements. Temperature. Salinity. Depth or pressure. Sea-level measurement. Eulerian currents. Lagrangian current measurements. Wind. Precipitation. Chemical tracers. Transient chemical tracers.Data Processing and Presentation.Introduction. Calibration. Interpolation. Data presentation.Statistical Methods and Error Handling.Introduction. Sample distributions. Probability. Moments and expected values. Common probability density functions. Central limit theorem. Estimation. Confidence intervals. Selecting the sample size. Confidence intervals for altimeter bias estimators. Estimation methods. Linear estimation (regression). Relationship between regression and correlation. Hypothesis testing. Effective degrees of freedom. Editing and despiking techniques: the nature of errors. Interpolation: filling the data gaps. Covariance and the covariance matrix. Bootstrap and jackknife methods.The Spatial Analyses of Data Fields.Traditional block and bulk averaging. Objective analysis. Empirical orthogonal functions. Normal mode analysis. Inverse methods.Time-series Analysis Methods.Basic concepts. Stochastic processes and stationarity. Correlation functions. Fourier analysis. Harmonic analysis. Spectral analysis. Spectral analysis (parametric methods). Cross-spectral analysis. Wavelet analysis. Digital filters. Fractals.Appendices.
References. Index.
8 illus., 135 line drawings.