Data Analysis Methods in Physical Oceanography

Data Analysis Methods in Physical Oceanography

3rd Edition - July 14, 2014

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  • Authors: Richard E. Thomson, William J Emery
  • Paperback ISBN: 9780123877826
  • eBook ISBN: 9780123877833

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Description

Data Analysis Methods in Physical Oceanography, Third Edition is a practical reference to established and modern data analysis techniques in earth and ocean sciences. Its five major sections address data acquisition and recording, data processing and presentation, statistical methods and error handling, analysis of spatial data fields, and time series analysis methods. The revised Third Edition updates the instrumentation used to collect and analyze physical oceanic data and adds new techniques including Kalman Filtering. Additionally, the sections covering spectral, wavelet, and harmonic analysis techniques are completely revised since these techniques have attracted significant attention over the past decade as more accurate and efficient data gathering and analysis methods.

Key Features

  • Completely updated and revised to reflect new filtering techniques and major updating of the instrumentation used to collect and analyze data
  • Co-authored by scientists from academe and industry, both of whom have more than 30 years of experience in oceanographic research and field work
  • Significant revision of sections covering spectral, wavelet, and harmonic analysis techniques
  • Examples address typical data analysis problems yet provide the reader with formulaic “recipes” for working with their own data
  • Significant expansion to 350 figures, illustrations, diagrams and photos

Readership

Oceanographers, atmospheric scientists, meteorologists, climatologists, and upper-undergraduate and graduate students studying statistical methods in oceanography, meteorology, and climatology

Table of Contents

    • Dedication
    • Preface
    • Acknowledgments
    • Chapter 1. Data Acquisition and Recording
      • 1.1. Introduction
      • 1.2. Basic Sampling Requirements
      • 1.3. Temperature
      • 1.4. Salinity
      • 1.5. Depth or Pressure
      • 1.6. Sea-Level Measurement
      • 1.7. Eulerian currents
      • 1.8. Lagrangian Current Measurements
      • 1.9. Wind
      • 1.10. Precipitation
      • 1.11. Chemical tracers
      • 1.12. Transient chemical tracers
    • Chapter 2. Data Processing and Presentation
      • 2.1. Introduction
      • 2.2. Calibration
      • 2.3. Interpolation
      • 2.4. Data Presentation
    • Chapter 3. Statistical Methods and Error Handling
      • 3.1. Introduction
      • 3.2. Sample Distributions
      • 3.3. Probability
      • 3.4. Moments and Expected Values
      • 3.5. Common PDFs
      • 3.6. Central Limit Theorem
      • 3.7. Estimation
      • 3.8. Confidence Intervals
      • 3.9. Selecting the Sample Size
      • 3.10. Confidence Intervals for Altimeter-Bias Estimates
      • 3.11. Estimation Methods
      • 3.12. Linear Estimation (Regression)
      • 3.13. Relationship between Regression and Correlation
      • 3.14. Hypothesis Testing
      • 3.15. Effective Degrees of Freedom
      • 3.16. Editing and Despiking Techniques: The Nature of Errors
      • 3.17. Interpolation: Filling the Data Gaps
      • 3.18. Covariance and the Covariance Matrix
      • 3.19. The Bootstrap and Jackknife Methods
    • Chapter 4. The Spatial Analyses of Data Fields
      • 4.1. Traditional Block and Bulk Averaging
      • 4.2. Objective Analysis
      • 4.3. Kriging
      • 4.4. Empirical Orthogonal Functions
      • 4.5. Extended Empirical Orthogonal Functions
      • 4.6. Cyclostationary EOFs
      • 4.7. Factor Analysis
      • 4.8. Normal Mode Analysis
      • 4.9. Self Organizing Maps
      • 4.10. Kalman Filters
      • 4.11. Mixed Layer Depth Estimation
      • 4.12. Inverse Methods
    • Chapter 5. Time Series Analysis Methods
      • 5.1. Basic Concepts
      • 5.2. Stochastic Processes and Stationarity
      • 5.3. Correlation Functions
      • 5.4. Spectral Analysis
      • 5.5. Spectral Analysis (Parametric Methods)
      • 5.6. Cross-Spectral Analysis
      • 5.7. Wavelet Analysis
      • 5.8. Fourier Analysis
      • 5.9. Harmonic Analysis
      • 5.10. Regime Shift Detection
      • 5.11. Vector Regression
      • 5.12. Fractals
    • Chapter 6. Digital Filters
      • 6.1. Introduction
      • 6.2. Basic Concepts
      • 6.3. Ideal Filters
      • 6.4. Design of Oceanographic Filters
      • 6.5. Running-Mean Filters
      • 6.6. Godin-Type Filters
      • 6.7. Lanczos-window cosine filters
      • 6.8. Butterworth Filters
      • 6.9. Kaiser–Bessel Filters
      • 6.10. Frequency-Domain (Transform) Filtering
    • References
    • Appendix A: Units in Physical Oceanography
    • Appendix B: Glossary of Statistical Terminology
    • Appendix C: Means, Variances and Moment-Generating Functions for Some Common Continuous Variables
    • Appendix D: Statistical Tables
    • Appendix E: Correlation Coefficients at the 5% and 1% Levels of Significance for Various Degrees of Freedom ν
    • Appendix F: Approximations and Nondimensional Numbers in Physical Oceanography
    • Appendix G: Convolution
    • Index

Product details

  • No. of pages: 728
  • Language: English
  • Copyright: © Elsevier Science 2014
  • Published: July 14, 2014
  • Imprint: Elsevier Science
  • Paperback ISBN: 9780123877826
  • eBook ISBN: 9780123877833

About the Authors

Richard E. Thomson

Richard E. Thomson

Affiliations and Expertise

Senior Research Scientist and Head of the Ocean Dynamics & Processes Section, Institute of Ocean Sciences, Sidney, British Columbia, Canada

William J Emery

Affiliations and Expertise

Professor, Aerospace Engineering Sciences, University of Colorado, Boulder, USA

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  • William S. Mon May 14 2018

    Great textbook.

    It is my go-to reference for statistical methods.