Data Analysis Methods in Physical Oceanography, 3EBy
- W. J. Emery, Aerospace Engineering Science Department, University of Colorado, USA
- W.J. Emery, CCAR Box 431, Aerospace Engineering Sciences Department, Engineering Center, University of Colorado, Boulder, CO 80309, USA
- R.E. Thomson, Institute of Ocean Sciences, 9860 West Saanich Road, Sidney, British Colombia V8L 4B2 Canada
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 established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references.
• 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
"(...)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
Hardbound, 654 pages
Published: April 2001
...this is an excellent, practical text on data analysis, with minor improvements over the first edition.
A. Plueddemann, Woods Hole Oceanographic Institution, Woods Hole, MA, USA, Oceanography, Vol. 14, No. 4
...The book is well laid out, with the content easy to find and access. The statistical presentation, while mathematical, is clear and straightforward, without unnecessary complexity. ...I think this is an excellent book on the topic and it would be an ideal textbook for a graduate level course on geophysical data analysis. I could also see the book becoming a well referred to reference for researchers working with oceanographic data, whether from actual observations or from the output of numerical models.
P. Myers, University of Alberta, Canada, CMOS Bulletin SCMO
- 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.