Catalogue Description: Introduction to multivariate statistical techniques commonly used in climate science, with special emphasis on estimation in large dimensional spaces. Topics include: multivariate regression, canonical correlation analysis, predictable component analysis, field significance tests, data assimilation (especially the ensemble Kalman Filter), discriminant analysis, and multivariate detection and attribution of climate change.
| 1/25/2016 | Model Selection | Homework | Solutions |
| 2/01/2016 | No Class | - | - |
| 2/08/2016 | Field Significance Tests | Homework | Solutions |
| 2/15/2016 | CANCELLED DUE TO INCLEMENT WEATHER | - | - |
| 2/22/2016 | Canonical Correlation Analysis | Homework | Solutions |
| 2/29/2016 | Analysis of Variance (ANOVA) | Homework | Solutions |
| 3/07/2016 | Spring Break | - | - |
| 3/14/2016 | Predictable Component Analysis (PrCA) | Homework | Solutions |
| 3/21/2016 | Predictability | - | - |
| 3/28/2016 | Data Assimilation | Homework | Solutions |
| 4/04/2016 | Ensemble Square Root Filter | - | - |
| 4/11/2016 | Filter Divergence and Adaptive Inflation | Homework | Solutions |
| 4/18/2016 | Detection and Attribution of Climate Change | Homework | Solutions |
| 4/25/2016 | Historical Review of Data Assimilation | Homework | Solutions |
| 5/02/2016 | Extremes | Homework | Solutions |
| 5/09/2016 | Class Presentations |