Optimal approximation of kalman filtering with temporally local 4D-var in operational weather forecasting

Proceedings of the 11th ECMWF Workshop on the Use of High Performance Computing in Meteorology

Volumn , Issue , 2005, Pages 84-99

  Auvinen, H ^a   Haario, H ^b   Kauranne, T ^b  

^a UNIVERSITY OF HELSINKI   (Finland)

^b LAPPEENRANTA UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COVARIANCE MATRIX; ERRORS; EXTENDED KALMAN FILTERS; METEOROLOGY; SUPERCOMPUTERS;

COMPUTATIONAL COSTS; DATA ASSIMILATION; DISPERSION EQUATIONS; ERROR COVARIANCE MATRIX; FOUR DIMENSIONAL VARIATIONAL; LOW RANK APPROXIMATIONS; OPTIMAL APPROXIMATION; PARALLEL SUPERCOMPUTER;

WEATHER FORECASTING;

EID: 76049128299     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1142/9789812701831_0007     Document Type: Conference Paper

References (13)

1. R. N. Bannister: Elementary 4D-Var, DARC Technical Report No. 2, Data Assimilation Research Centre, University of Reading, (2001).
2. M. Ehrendorfer, A. Beck: Singular vector based multivariate normal sampling in ensemble prediction. ECMWF Technical Memoranda 416 (2003).
3. G. Evensen: Sequential data assimilation with a non-linear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. 97 17905- 17924 (1994).
4. M. Fisher: On the equivalence between Kalman smoothing and weak constraint four-dimensional variational data assimilation. ECMWF Technical Memoranda 447 (2004).
5. M. Fisher and E. Andersson: Developments in 4D-Var and Kalman filtering. ECMWF Techical Memoranda 347 (2001).
6. J. Derber: A variational continuous assimilation technique. Mora. Weather Rev. 117 2437-2446 (1989).
7. L. Isaksen, M. Fisher, E. Andersson: The structure and realism of sensitivity perturbations and their interpretation as 'Key Analysis Errors'. ECMWF Technical Memoranda 445 (2004).
8. T. Kauranne: 4D Variational assimilation, ensemble forecasting and parallel computing. Parallel supercomputing in atmospheric science (Eds. Hoffmann and Kauranne 286-311. World Scientific (1993).
9. T. Kauranne: Introducing parallel computers into operational weather forecasting, Acta Umversitatis Lappeenrantaensis 142 (2002).
10. F.-X. LeDimet and O. Talagrand: Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus 33A 97-110 (1986).
11. L. Nerger: Parallel filter algorithms for data assimilation in oceanography. PhD Thesis. University of Bremen (2004).
12. F. Rabier, H. Jarvinen, E. Klinker, J-F. Mahfouh and A. Simmons: The ECMWF operational implementation of four dimensional variational assimilation. Part I: Experimental results with simplified physics. Q. J, R. Meteorol. Soc. 126, 1143-1170 (2000).
13. CD. Rodgers: Inverse Methods for Atmospheric Sounding Theory and Practice, World Scientific, London, (2000).