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Home > Newsevents > Training > Lecture_notes >DA  

Data Assimilation and the Use of Satellite Data



Click on the titles below to access pdf files of the lecture notes


"Introduction to microwave radiative transfer" by Peter Bauer
        1. Radiative transfer
        2. Radiative transfer models
        3. Atmospheric absorption
        4. Surface emission / reflection
        5. Hydrometeors
        6. Fast models
        7. Outstanding issues

"Microwave radiative transfer modeling in clouds and precipitation. Part I Model description" by Peter Bauer
        1. Introduction
        2. Microwave radiative transfer
        3. Radiative transfer models
        4. Optical properties

"Microwave radiative transfer modeling in clouds and precipitation. Part II Model evaluation" by Emmanuel Moreau, Peter Bauer and Frédéric Chevallier
        1. Introduction
        2. Edington vs Doubling-Adding model
        3. Comparison with other models

"A data assimilation tutorial based on the Lorenz-95 system" by Martin Leutbecher
        1. Introduction
        2. Data assimilation experiments
        3. Outlook
        (Click here to download programs relating to the tutorial)

"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
        5. Discussion
        6. Conclusions

"Assimilation algorithms" by Elias Valur Holm
  1. Basic concepts
  2. Variational data assimilation
  3. Common assimilation algorithms
  4. References

"Assimilation techniques: 3dVar" by Mike Fisher
        1. Introduction
        2. The incremental method
        3. The background cost function

"Assimilation techniques: 4dVar" 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

"Assimilation techniques: Approximate Kalman filters and singular vectors" 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

"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

"Observation Impact on the Short Range Forecast" by C. Cardinali
        1. Introduction
        2. Observational Impact on the Forecast
        3. Results
        4. Conclusion

"Observation influence diagnostic of a data assimilation system" by C. Cardinali
        1. Introduction
        2. Classical Statistical Definitions of Influence Matrix and Self-Sensitivity
        3. Observational Influence and Self-Sensitivity for a DA Scheme
        4. Results 
        5. Conclusions
        A. Influence Matrix Calculation in Weighted Regression Data Assim. Scheme
        B. Approximate calculation of self-sensitivity in a large variational analysis

"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

"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

"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

"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



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