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.
• 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.
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.
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- © Elsevier Science 2001
- 3rd April 2001
- Elsevier Science
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CCAR Box 431, Aerospace Engineering Sciences Department, Engineering Center, University of Colorado, Boulder, CO 80309, USA
Institute of Ocean Sciences, 9860 West Saanich Road, Sidney, British Colombia V8L 4B2 Canada
Senior Research Scientist and Head of the Ocean Dynamics & Processes Section, Institute of Ocean Sciences, Sidney, British Columbia, Canada
Professor, Aerospace Engineering Sciences, University of Colorado, Boulder, USA
@from:A. Plueddemann, Woods Hole Oceanographic Institution, Woods Hole, MA, USA @qu:...this is an excellent, practical text on data analysis, with minor improvements over the first edition. @source:Oceanography, Vol. 14, No. 4 @from:P. Myers, University of Alberta, Canada @qu:...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. @source:CMOS Bulletin SCMO