AOS 102 Climate Change and Modeling
Lecture, three hours; discussion, one hour. Enforced requisites: Mathematics 3C or 32A, Physics 1B or 6C, with grades of C or better. Global environmental issues in climate change due to human activities or natural climate variations. Quantitative introduction to new science of climate modeling to understand and predict these changes. Physical processes in climate system. Atmospheric and oceanic circulation. El niño and year-to-year climate prediction. Greenhouse effect and global warming. P/NP or letter grading.
Advanced Graduate Courses:
AOS 219 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.
AOS 286 Statistical Prediction and Verification
Seminar, on e hour; discussion, one hour. Statistical prediction and verification. Topics include multiple linear regression, logistic regression (probability prediction), objective prediction using traditional statistical methods, ensemble prediction. S/U grading.