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Winter Quarter 2009.
Instructor: Greg Hakim
| syllabus | resources | lecture log |
Winter Quarter 2009.
Instructor: Greg Hakim
Class meets: MW 10:30-11:50. ATG 610.
Recommended Texts:
Wunsch, C. "Discrete Inverse and State Estimation Problems" (2006)
Kalnay, E. "Atmospheric Modeling, Data Assimilation and Predictability" (2003)
Daley, R. "Atmospheric Data Analysis" (1993)
Prerequisites: interest in geophysical modeling; basic linear algebra.
Grading: class project.
Course description
Syllabus:
- Overview and background review.
- Least squares; adjoints; Lagrange multipliers.
- Conditional probability; Bayesian methods.
- Information theory.
- Highlights from dynamical systems theory.
- flow stability and error growth.
- Lyapunov exponents and vectors.
- finite-time stability.
- Deterministic and probabilistic forecasting.
- Liouville & Fokker-Planck equations.
- Monte Carlo approaches.
- ensembles.
- information metrics.
- State estimation
- Bayesian estimation.
- Linear dynamics & Gaussian statistics: Kalman filtering.
- Variational approaches: 3DVAR and 4DVAR.
- Monte Carlo ensemble filters.
- Square-root ensemble filters.
- Kalman smoothers.
- Sensitivity analysis
- Adjoint and ensemble methods.
- Targeting and control.
- Network design.
- Model error
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