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Data assimilation and the use of satellite
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"Adaptive observations, the Hessian matrix and singular vectors" by Martin Leutbecher>>
1. Introduction
2. Adaptive observations in the Lorenz 95 system - Methodology
3. Adaptive observations in the Lorenz 95 system - Results
4. Reduced rank prediction of forecast error variance reductions in an operational NWP context
5. Discussion
6. Conclusions
ReferencesClick here to download a pdf file
"Assimilation algorithms" by Elias Valur Holm>>
1. Basic concepts
2. Variational data assimilation
3. Common assimilation algorithms
ReferencesClick here to download a pdf file
"Assimilation techniques (3): 3dVar. April 2001" by Mike Fisher >>
1. Introduction
2. The incremental method
3. The background cost function
ReferencesClick here to download a pdf file
"Assimilation techniques (4): 4dVar. April 2001" by Mike Fisher >>
1. Introduction
2. Comparison betwee the ECMWF 3dVar and 4dVar systems
3. The current operational configuration of 4dVar
4. Increments from a single observation
5. A cautionary example
ReferencesClick here to download a pdf file
"Assimilation techniques (5): Approximate Kalman filters and singular vectors. April 2001" by Mike Fisher >>
1. Introduction
2. Why is the Kalman filter impractical for very large systems?
3. The ensemble Kalman filter
4. Subspaces, projections and Hessian singular vectors
5. The ECMWF reduced-rank Kalman filter
6. Examples
ReferencesClick here to download a pdf file
"Data assimilation concepts and methods" by F. Bouttier and P. Courtier >>
1. Basic concepts of data assimilation
2. The state vector, control space and observations
3. The modelling of errors
4. Statistical interpolation with least-squares estimation
5. A simple scalar illustration of least-squares estimation
6. Models of error covariances
7. Optimal interpolation (OI) analysis
8. Three-dimensional variational analysis (3D-Var)
9. 1D-Var and other variational analysis systems
10. Four-dimensional variational assimilation (4D-Var)
11. Estimating the quality of the analyses
12. Implementation techniques
13. Dual formulation of 3D/4D-Var (PSAS)
14. The extended Kalman filter (EKF)
15. Conclusion
Appendix A. A primer on linear algebra
Appendix B. Practical adjoint coding
Appendix C. Exercises
Appendix D. Main symbols
ReferencesClick here to download a pdf file
"Observations and diagnostic tools for data assimilation" by H. Järvinen >>
1. Observational preprocessing
2. The observation screening
3. Use of feedback information
4. Diagnostic tools for an assimilation system
ReferencesClick here to download a pdf file
"The control of gravity waves in data assimilation" by A. Simmons >>
1. Introduction
2. Non-linear normal-mode initialization
3. Control of gravity waves in the ECMWF variational data asimilation
4. Digital filtering
Appendix A. Definition of operators for the ECMWF vertical finite-diference scheme
Appendix B. The Lamb wave
Appendix C. The non-recursive implementation of the recursive filter
References
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"Principles of remote sensing of atmospheric parameters from space" by R. Rizzi (revised by R. Saunders) >>
1. Introduction
2. Absorption and transmission of monochromatic radiation
3. Black-body radiation
4. Emissivity, Kirchoff law and local thermodynamical equilibrium
5. The equation for radiative transfer
6. Spectral distribution of radiance leaving the atmosphere
7. Modelling the interaction
8. Line shapes and the absorption coefficient
9. Continuum absorption
10. Integration over frequency
11. The direct problem
ReferencesClick here to download a pdf file
"Inversion methods for satellite sounding data" by J. Eyre >>
1. Basic ideas
2. Temperature profile inversion methods
3. Constituent profile inversion
4. Clouds
5. Satellite sounding in numerical weather prediction
ReferencesClick here to download a pdf file
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31.03.2005 |
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