Provides a comprehensive and practical compilation of the essential information and analysis techniques required for the advanced processing and interpretation of digital spatio-temporal data in physical oceanography as well as in other branches of the geophysical sciences.
A. Plueddemann, Woods Hole Oceanographic Institution, Woods Hole, MA, USA ...this is an excellent, practical text on data analysis, with minor improvements over the first edition. Oceanography, Vol. 14, No. 4 P. Myers, University of Alberta, Canada ...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. 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.
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