Data Analysis Methods in Physical Oceanography

About this book

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.

Contents

- 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

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