Statistical Analysis and Visual Explanation of Large Climate Data

Lecture, three hours; discussion, one hour. Introduction to statistical methods to analyze climate data and principles of visual presentation of quantitative information. Review of basic statistical concepts. Principles of visual display of quantitative information. Parametric and non-parametric tests for auto-correlated and non-stationary data, multiplicity, and field significance. Spatial-tempo pattern analyses including cross-spectral analysis, spatio-temporary spectral analysis, empirical orthogonal function (EOF) and extension of EOFs (complex EOF, multivariate EOF, extended EOF). Spatial-temporal canonical correlation analysis (CCA), time-lagged CCA, maximum correlation analysis (or singular value decomposition). Self-organizing map. S/U or letter grading.

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Course

Instructor
Fu, R.
Previously taught
24S 21S 19F 19S 18S

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