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.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
Rezensionen / Stimmen
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. 4P. 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
Auflage
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Gewicht
ISBN-13
978-0-444-50756-3 (9780444507563)
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Schweitzer Klassifikation
Richard E. Thomson is a researcher in coastal and deep-sea physical oceanography within the Ocean Sciences Division. Coastal oceanographic processes on the continental shelf and slope including coastally trapped waves, upwelling and baroclinic instability; hydrothermal venting and the physics of buoyant plumes; linkage between circulation and zooplankton biomass aggregations at hydrothermal venting sites; analysis and modelling of landslide generated tsunamis; paleoclimate using tree ring records and sediment cores from coastal inlets and basins. William (Bill) Emery worked as a professor in Aerospace Engineering Sciences at the University of Colorado from 1987, prior to which he worked in the University of British Columbia where he created a Satellite Oceanography education/research program. He has authored over 220-refereed publications and 4 textbooks in addition to having given 200 conference papers. He is a fellow of: the IEEE (2002), the American Meteorological Society (2010), the American Astronautical Society (2011) and the American Geophysical Union (2012). He was recently elected to the IEEE TAB Hall of Honor (2020). In 2022 he received the GRSS Fawaz Ulaby Distinguised Achievement Award.
Autor*in
Senior Research Scientist and Head of the Ocean Dynamics and Processes Section, Institute of Ocean Sciences, Sidney, British Columbia, Canada
Professor, Aerospace Engineering Sciences, University of Colorado, Boulder, USA
Herausgeber*in
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
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.
