Climate Analysis, Variability, and Prediction

Course Description

A graduate-level treatment of the analysis and prediction of the Earth's climate over subseasonal, seasonal, and decadal time scales. Following the preliminaries on how these scales are realized in climate observations, we will describe the drivers of the climate system across these scales. Modes of natural climate variability, which include El Nino/Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Madden-Julian Oscillation (MJO), will then be described, as will the statistical techniques used to reveal them. Statistical prediction models based on multivariate regressions often incorporate index-representations of ENSO and other relevant variables. Accordingly, we will devote some time and exercises on methods in which these models are developed as well as tested. Dynamical models are also used for climate prediction, but require computational capability and relatively more thought in design and application. Thus, we will complete the course with a significant treatment of global models as well as regional models. Both models are based on the same basic set of equations, but typically have different applications. Model setup and implementation will be illustrated through practical exercises with open-source community global and regional models. Prerequisite: ATMS 517 and ATMS 520, or equivalent; or Permission of Instructor.

Code

ATMS 521

Credits

4

Subject

Atmospheric Sciences

Programs That Include This Course

• Master's Master of Science in Weather And Climate Risk & Analysis