Prediction and Predictability in the Atmosphere and Oceans

Calendar

SES	TOPICS	KEY DATES
1	**Introduction/Prediction Needs ** Course Description and Expectations Motivation Presentation of Possible Project Topics
2-4	**Attractors and Dimensions ** Definitions (Ses #2) Attractor Dimensions (Ses #3) Embedding (Ses #4)	Problem Set 1 out (Ses #3)
5-10	Sensitive Dependence to Initial Conditions Lyapunov Exponents (Ses #5-6) Singular Vectors and Norms (Ses #7-9) Validity of Linearity Assumption (Ses #10)	Problem Set 1 due (Ses #5) Problem Set 2 out (Ses #6) Problem Set 1 returned (Ses #7) Problem Set 2 due (Ses #8) Problem Set 2 returned (Ses #10) Problem Set 3 out (Ses #10)
11-18	**Probabilistic Forecasting **Probability Primer (Ses #12) Stochastic-Dynamic Prediction (Ses #11-12) Monte-Carlo (Ensemble) Approximation (Ses #12) Ensemble Forecasting Climate Change (Ses #13, 15, 17) Ensemble Construction (Perfect, Unconstrained, Constrained) (Ses #16) Ensemble Assessment (Ses #18)	Problem Set 3 due (Ses #12) Problem Set 3 returned (Ses #13)
19-22	**Data Assimilation **Definition and Kalman Filter Derivations (Ses #19-20) 3dVar and 4dVar Derivations (Ses #20) Adjoint Models (Ses #21) Nonlinear Data Assimilation (Ses #21) Ensemble-Based Data Assimilation (Ses #22)	Problem Set 4 out (Ses #19) Problem Set 4 due (Ses #22)