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Oceanography 569A Oceanographic Data Analysis Laboratory

Organization. 1 lecture, 1 lab period (2 hrs) per weekExercise assigned on Monday, finish in Friday lab (open lab hours during week)Presentation of solution in Monday classWorking groups for exercises - everyone is to write Matlab codeOne class project: working group discussion andmethodology,

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Oceanography 569A Oceanographic Data Analysis Laboratory

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    1. Oceanography 569A Oceanographic Data Analysis Laboratory Kathie Kelly Applied Physics Laboratory 561 Henderson Hall class web site: kkelly.apl.washington.edu/classes/ocean569_2010

    2. Organization 1 lecture, 1 lab period (2 hrs) per week Exercise assigned on Monday, finish in Friday lab (open lab hours during week) Presentation of solution in Monday class Working groups for exercises - everyone is to write Matlab code One class project: working group discussion and methodology, but each student writes a paper (GRL-style) Grade based on presentations and paper Office hours?

    3. Materials All materials available on class web site Schedule and deadlines also on web site Handouts will be discussed in lecture Exercise files to be downloaded from web site General purpose mfiles also on web site Solutions will be posted the following week (for your reference)

    4. Exercise 1: Merging data

    5. Exercise 1: Merging data

    6. Exercise 1: Merging data

    7. Exercise 1: Merging data

    8. Exercise 1: Merging data

    9. Exercise 1: Merging data

    10. Matlab functions

    11. Periodic Signals

    12. Introduction to Statistics

    13. Characterize Observations

    14. Normal Distribution

    15. Central Limit Theorem

    16. Error Estimates and Propagation

    17. Error Estimates for Differences or Derivatives

    18. More General Error Estimates

    19. Multiple Error Sources

    20. Exercise 2

    21. Exercise 2

    22. Analysis of Variance (ANOVA)

    23. More Statistical Concepts

    24. Covariance and Correlation

    25. Autocovariance

    26. Covariance and Errors

    27. Autocorrelation

    28. Decorrelation Times

    29. Integral Time Scale

    30. Significance of a Correlation

    31. Using Correlations to Evaluate Observations

    32. Taylor Diagram

    33. Vector Correlations

    34. Lowpass Filter

    35. Other Filters

    36. Linear Estimators

    37. Evaluating a Model

    38. Linear Algebra Review (1)

    39. Linear Algebra Review (2)

    40. Linear Algebra Review (3)

    41. Linear Algebra Review (4)

    42. Linear Regression

    43. Linear Regression (cont’d)

    44. Significance of Linear Regression

    45. Another Significance Test

    46. Linear Regression: SST Hindcasts

    47. Linear Regression: SST Forecasts

    48. Linear Regression: Wind Hindcasts

    49. Linear Regression: Wind Forecasts

    50. Principal Component Analysis Or Empirical Orthogonal Functions (EOFs)

    51. Singular Value Decomposition original method for computing EOFs

    52. Singular Value Decomposition EOFs on nonseasonal SSH in Gulf Stream region

    53. Covariance Matrix Eigenvectors conventional method for computing EOFs

    54. Covariance Matrix Eigenvectors conventional method for nonseasonal EOFs on wind vectors

    55. Equivalence of EOF Methods

    56. Significant EOF Modes

    57. Different Results from EOFs

    58. Asymmetry in SVD for Covariance Method

    59. Applying Analysis Tools practice exercise for your project

    60. Sea Level Variability in the Eastern Mediterranean Sea

    61. Sea Level Variability in the Eastern Mediterranean Sea

    62. Sea Level Variability in the Eastern Mediterranean Sea

    63. Applying Analysis Tools

    64. What Causes SST Variability in the Gulf Stream?

    65. What Causes SST Variability in the Gulf Stream?

    66. Writing Up Results

    67. Optimal Interpolation or Objective Mapping

    68. Linear Combination of Nearby Data

    69. Minimize Squared Error

    70. Coefficients Based on Data Covariances

    71. Estimate Mean and Map Anomalies

    72. Expected Errors for Maps

    73. Estimating a Covariance Function

    74. Estimating a Covariance Function

    75. Project Solution: Observations & Fields

    76. Project Solution: Heating Model Errors

    77. Project Solution: dT/dt and MLD correction

    78. Project Solution: Correlations of dT/dt residual

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