ALBERT

Note: Contents: Preface. - Acknowledgments. - 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. - 2. Data Processing and Presentation. - 2.1 Introduction. - 2.2 Calibration. - 2.3 Interpolation. - 2.4 Data Presentation. - 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. - 4. The Spatial Analyses of Data Fields. - 4.1 Traditional Block and Bulk Averaging. - 4.2 Objective Analysis. - 4.3 Kriging. - 4.4 Empirical Orrhogonal Functions. - 4.5 Extended Empirical Orrhogonal 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. - 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. - 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 v. - Appendix F: Approximations and Nondimensional Numbers in Physical Oceanography. - Appendix G: Convolution. - Index.

Note: Contents: Preface. - Acknowledgments. - Chapter 1 Data Acquisition and Recording. - 1.1 Introduction. - 1.2 Basic sampling requirements. - 1.2.1 Sampling interval. - 1.2.2 Sampling duration. - 1.2.3 Sampling accuracy. - 1.2.4 Burst sampling versus continuous sampling. - 1.2.5 Regularly versus irregularly sampled data. - 1.2.6 Independent realizations. - 1.3 Temperature. - 1.3.1 Mercury thermometers. - 1.3.2 The mechanical bathythermograph (MBT). - 1.3.3 Resistance thermometers (expendable bathythermograph: XBT). - 1.3.4 Salinity/conductivity-temperature-depth profilers. - 1.3.5 Dynamic response of temperature sensors 19 1.3.6 Response times of CTD systems. - 1.3.7 Temperature calibration of STD/CTD profilers. - 1.3.8 Sea surface temperature. - 1.3.9 The modern digital thermometer. - 1.3.10 Potential temperature and density. - 1.4 Salinity. - 1.4.1 Salinity and electrical conductivity. - 1.4.2 The practical salinity scale. - 1.4.3 Nonconductive methods. - 1.5 Depth or pressure. - 1.5.1 Hydrostatic pressure. - 1.5.2 Free-fall velocity. - 1.5.3 Echo sounding. - 1.5.4 Other depth sounding methods. - 1.6 Sea-level measurement. - 1.6.1 Tide and pressure gauges. - 1.6.2 Satellite altimetry. - 1.6.3 Inverted echo sounder (IES). - 1.6.4 Wave height and direction. - 1.7 Eulerian currents. - 1.7.1 Early current meter technology. - 1.7.2 Rotor-type current meters. - 1.7.3 Nonmechanical current meters. - 1.7.4 Profiling acoustic Doppler current meters (ADCM). - 1.7.5 Comparisons of current meters. - 1.7.6 Electromagnetic methods. - 1.7.7 Other methods of current measurement. - 1.7.8 Mooring logistics. - 1.7.9 Acoustic releases. - 1.8 Lagrangian current measurements. - 1.8.1 Drift cards and bottles. - 1.8.2 Modern drifters. - 1.8.3 Processing satellite-tracked drifter data. - 1.8.4 Drifter response. - 1.8.5 Other types of surface drifters. - 1.8.6 Subsurface floats. - 1.8.7 Surface displacements in satellite imagery. - 1.9 Wind. - 1.10 Precipitation. - 1.11 Chemical tracers. - 1.11.1 Conventional tracers. - 1.11.2 Light attenuation and scattering. - 1.11.3 Oxygen isotope: δ18O. - 1.11.4 Helium-3; helium/heat ratio. - 1.12 Transient chemical tracers. - 1.12.1 Tritium. - 1.12.2 Radiocarbon. - 1.12.3 Chlorofluorocarbons. - 1.12.4 Radon-222. - 1.12.5 Sulfur hexachloride. - 1.12.6 Strontium-90. - Chapter 2 Data Processing and Presentation. - 2.1 Introduction. - 2.2 Calibration. - 2.3 Interpolation. - 2.4 Data presentation. - 2.4.1 Introduction. - 2.4.2 Vertical profiles. - 2.4.3 Vertical sections. - 2.4.4 Horizontal maps. - 2.4.5 Map projections. - 2.4.6 Characteristic or property versus property diagrams. - 2.4.7 Time-series presentation. - 2.4.8 Histograms. - 2.4.9 New directions in graphical presentation. - Chapter 3 Statistical Methods and Error Handling. - 3.1 Introduction. - 3.2 Sample distributions. - 3.3 Probability. - 3.3.1 Cumulative probability functions. - 3.4 Moments and expected values. - 3.4.1 Unbiased estimators and moments. - 3.4.2 Moment generating functions. - 3.5 Common probability density functions. - 3.6 Central limit theorem. - 3.7 Estimation. - 3.8 Confidence intervals. - 3.8.1 Confidence interval for μ (σ known) 3.8.2 Confidence interval for μ (σ unknown) 3.8.3 Confidence interval for σ^2. - 3.8.4 Goodness-of-fit test. - 3.9 Selecting the sample size. - 3.10 Confidence intervals for altimeter bias estimates. - 3.11 Estimation methods. - 3.11.1 Minimum variance unbiased estimation. - 3.11.2 Method of moments. - 3.11.3 Maximum likelihood. - 3.12 Linear estimation (regression). - 3.12.1 Method of least squares. - 3.12.2 Standard error of the estimate. - 3.12.3 Multivariate regression. - 3.12.4 A computational example of matrix regression. - 3.12.5 Polynomial curve fitting with least squares. - 3.12.6 Relationship between least-squares and maximum likelihood. - 3.13 Relationship between regression and correlation. - 3.13.1 The effects of random errors on correlation. - 3.13.2 The maximum likelihood correlation estimator. - 3.13.3 Correlation and regression: cause and effect. - 3.14 Hypothesis testing. - 3.14.1 Significance levels and confidence intervals for correlation. - 3.14.2 Analysis of variance and the F-distribution. - 3.15 Effective degrees of freedom. - 3.1 5.1 Trend estimates and the integral time scale. - 3.16 Editing and despiking techniques: the nature of errors. - 3.16.1 Identifying and removing errors. - 3.16.2 Propagation of error. - 3.16.3 Dealing with numbers: the statistics of roundoff. - 3.16.4 Gauss-Markov theorem. - 3.17 Interpolation: filling the data gaps. - 3.17.1 Equally and unequally spaced data. - 3.17.2 Interpolation methods. - 3.17.3 Interpolating gappy records: practical examples. - 3.18 Covariance and the covariance matrix. - 3.18.1 Covariance and structure functions. - 3.18.2 A computational example. - 3.18.3 Multivariate distributions. - 3.19 Bootstrap and jackknife methods. - 3.19.1 Bootstrap method. - 3.19.2 Jackknife method. - Chapter 4 The Spatial Analyses of Data Fields. - 4.1 Traditional block and bulk averaging. - 4.2 Objective analysis. - 4.2.1 Objective mapping: examples. - 4.3 Empirical orthogonal functions. - 4.3.1 Principal axes of a single vector time series (scatter plot). - 4.3.2 EOF computation using the scatter matrix method. - 4.3.3 EOF computation using singular value decomposition. - 4.3.4 An example: deep currents near a mid-ocean ridge. - 4.3.S Interpretation of EOFs. - 4.3.6 Variations on conventional EOF analysis. - 4.4 Normal mode analysis. - 4.4.1 Vertical normal modes. - 4.4.2 An example: normal modes of semidiurnal frequency. - 4.4.3 Coastal-trapped waves (CTWs). - 4.5 Inverse methods. - 4.5.1 General inverse theory. - 4.5.2 Inverse theory and absolute currents. - 4.5.3 The IWEX internal wave problem. - 4.5.4 Summary of inverse methods. - Chapter 5 Time-series Analysis Methods. - 5.1 Basic concepts. - 5.2 Stochastic processes and stationarity. - 5.3 Correlation functions. - 5.4 Fourier analysis. - 5.4.1 Mathematical formulation. - 5.4.2 Discrete time series. - 5.4.3 A computational example. - 5.4.4 Fourier analysis for specified frequencies. - 5.4.5 The fast Fourier transform. - 5.5 Harmonic analysis. - 5.5.1 A least-squares method. - 5.5.2 A computational example. - 5.5.3 Harmonic analysis of tides. - 5.5.4 Choice of constituents. - 5.5.5 A computational example for tides. - 5.5.6 Complex demodulation. - 5.6 Spectral analysis. - 5.6.1 Spectra of deterministic and stochastic processes. - 5.6.2 Spectra of discrete series. - 5.6.3 Conventional spectral methods. - 5.6.4 Spectra of vector series. - 5.6.5 Effect of sampling on spectral estimates. - 5.6.6 Smoothing spectral estimates (windowing). - 5.6.7 Smoothing spectra in the frequency domain. - 5.6.8 Confidence intervals on spectra. - 5.6.9 Zero-padding and prewhitening. - 5.6.10 Spectral analysis of unevenly spaced time series. - 5.6.11 General spectral bandwidth and Q of the system. - 5.6.12 Summary of the standard spectral analysis approach. - 5.7 Spectral analysis (parametric methods). - 5.7.1 Some basic concepts. - 5.7.2 Autoregressive power spectral estimation. - 5.7.3 Maximum likelihood spectral estimation. - 5.8 Cross-spectral analysis. - 5.8.1 Cross-correlation functions. - 5.8.2 Cross-covariance method. - 5.8.3 Fourier transform method. - 5.8.4 Phase and cross-amplitude functions. - 5.8.S Coincident and quadrature spectra. - 5.8.6 Coherence spectrum (coherency). - 5.8.7 Frequency response of a linear system. - 5.8.8 Rotary cross-spectral analysis. - 5.9 Wavelet analysis. - 5.9.1 The wavelet transform. - 5.9.2 Wavelet algorithms. - 5.9.3 Oceanographic examples. - 5.9.4 The S-transformation. - 5.9.5 The multiple filter technique. - 5.10 Digital filters. - 5.10.1 Introduction. - 5.10.2 Basic concepts. - 5.10.3 Ideal filters. -