Courses:

Prediction and Predictability in the Atmosphere and Oceans >> Content Detail



Calendar / Schedule



Calendar

SES #TOPICSKEY DATES
1Introduction/Prediction Needs

Course Description and Expectations

Motivation

Presentation of Possible Project Topics
2-4Attractors and Dimensions

Definitions (Ses #2)

Attractor Dimensions (Ses #3)

Embedding (Ses #4)
Problem Set 1 out (Ses #3)
5-10Sensitive 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)
11-18Probabilistic 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)
19-22Data 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)

 








© 2009-2020 HigherEdSpace.com, All Rights Reserved.
Higher Ed Space ® is a registered trademark of AmeriCareers LLC.