An evaluation study of the DRP-4-DVar approach with the Lorenz-96 model

Tellus, Series A: Dynamic Meteorology and Oceanography

Volumn 63, Issue 2, 2011, Pages 256-262

  Liu, Juanjuan ^a   Wang, Bin ^a   Xiao, Qingnong ^b  

^a INSTITUTE OF ATMOSPHERIC PHYSICS   (China)

^b UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ASSIMILATION; ENSEMBLE FORECASTING; KALMAN FILTER; OBSERVATIONAL METHOD; WEATHER FORECASTING;

EID: 79751499447     PISSN: 02806495     EISSN: 16000870     Source Type: Journal    
DOI: 10.1111/j.1600-0870.2010.00487.x     Document Type: Article

References (33)

1. Buehner, M. 2005. Ensemble-derived stationary and flow-dependent background error covariances: evaluation in a quasi-operational setting for NWP setting. Quart. J. Roy. Meteor. Soc. 131, 1013-1043.
2. Caya, A., Sun, J. and Snyder, C. 2005. A comparison between the 4DVAR and the ensemble Kalman filter techniques for radar data assimilation. Mon. Wea. Rev. 133, 3081-3094.
3. Courtier, P., Thépaut, J.-N. and Hollingsworth, A. 1994. A strategy for operational implementation of 4D-Var using an incremental approach. Quart. J. Roy. Meteor. Soc. 120, 1367-1387.
4. Courtier, P. and Talagrand, O. 1987. Variational assimilation of meteorological observations with the adjoint vorticity equation. II: numerical results. Quart. J. Roy. Meteor. Soc. 113, 1329-1347.
5. Evensen, G. 1994. Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J. geophys. Res. 99(C5), 10143-10162.
6. Evensen, G. and van Leeuwen, P. J. 2000. An ensemble Kalman smoother for nonlinear dynamics. Mon. Wea. Rev. 128, 1852-1867.
7. Fertig, E., Harlim J. and Hunt, B. 2007. A comparative study of 4D-Var and 4D. Ensemble Kalman Filter: perfect model simulations with Lorenz-96. Tellus 59A, 96-100.
8. Gustafsson, N. 2007. Discussion on '4D-Var or EnKF?' Tellus 59A, 774-777.
9. Guo, Y.-R., Kuo, Y.-H., Dudhia, J., Parsons, D. and Rocken, C. 2000. Four-dimensional variational data assimilation of heterogeneous mesoscale observations for a strong convective case. Mon. Wea. Rev. 128, 619-643.
10. Hamill, T. M. and Snyder, C. 2000. A hybrid ensemble Kalman filter-3D variational analysis scheme. Mon. Wea. Rev. 128, 2905-2919.
11. Hamill, T. M., Snyder, C. and Morss, R. E. 2002. Analysis-error statistics of a quasi-geostrophic model using 3-dimensional variational assimilation. Mon Wea. Rev. 130, 2777-2790.
12. Houtekamer, P. L. and Mitchell, H. L. 1998. Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev. 126, 796-811.
13. Houtekamer, P. L. and Mitchell, H. L. 2001. A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev. 129, 123-137.
14. Hunt, B. R., Kalnay, E., Kostelich, E. J., Ott, E., Patil, D. J. and co-authors. 2004. Four-dimensional ensemble Kalman filtering. Tellus 56A, 273-277.
15. Kalnay, E., Li, H., Miyoshi, T., Yang, S.-C. and Ballabrera-Poy, J. 2007a. 4D-Var or ensemble Kalman filter? Tellus 59A, 758-773.
16. Kalnay, E., Li, H., Miyoshi, T., Yang, S.-C. and Ballabrera-Poy, J. 2007b. Response to the discussion on "4-D-Var or EnKF?" by Nils Gustafsson. Tellus 59A, 778-780.
17. Khare, S. P., Anderson, J., Hoar, T. J. and Nychka, D. 2008. An investigation into the application of an ensemble Kalman smoother to high-dimensional geophysical systems. Tellus 60A, 97-112.
18. Le Dimet, F.-X. and Talagrand, O. 1986. Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus 38A, 97-110.
19. Liu, C. S., Xiao, Q. and Wang, B. 2009. An Ensemble-based four-dimensional variational data assimilation scheme: part II: observing system simulation experiments with the Advanced Research WRF (ARW). Mon. Wea. Rev. 137, 1687-1704.
20. Liu, C. S., Xiao, Q. and Wang, B. 2008. An Ensemble-based four-dimensional variational data assimilation scheme: part I: technical formulation and preliminary test. Mon. Wea. Rev. 136, 3363-3373.
21. Lorenc, A. C. 2003. The potential of the ensemble Kalman filter for NWP-a comparison with 4D-VAR. Quart. J. R. Meteorol. Soc. 129, 3183-3203.
22. Lorenz, E. and Emanuel, K. 1998. Optimal sites for supplementary weather observations: simulation with a small model. J. Atmos. Sci. 55, 399-414.
23. Lorenz, E. 1996. Predictability: a problem partly solved. In: Proc. Seminar on Predictability. Volume 1, reading, ECMWF, United Kingdom, 1-19.
24. Rabier, F., Järvinen, J., Klinker, E., Mahfouf, J. F. and Simmons, A. 2000. The ECMWF implementation of four-dimensional variational assimilation. I: experimental results with simplified physics. Quart. J. Roy. Meteor. Soc. 126, 1143-1170.
25. Rawlins, F., Ballard, S. P., Bovis, K. J., Clayton, A. M., Li, D. and co-authors. 2007. The Met Office global four-dimensional variational data assimilation scheme. Quart. J. Roy. Meteor. Soc 133, 347-362.
26. Wang, B., Zou, X. and Zhu, J. 2000. Data assimilation and its application. Proc. Natl. Acad. Sci. USA 97, 11143-11144.
27. Wang, B., Liu, J.-J., Wang, S., Cheng, W., Liu, J. and co-authors. 2010. An economical approach to four-dimensional variational data assimilation. Adv. Atmos. Sci. 27, 715-727, doi.
28. Wang, X., Snyder, C. and Hamill, T. M. 2007. On the theoretical equivalence of differently proposed ensemble- 3DVAR hybrid analysis schemes. Mon. Wea. Rev. 135, 222-227.
29. Xiao, Q.-N., Zou, X. and Wang, B. 2000. Initialization and simulation of a landfalling hurricane using a variational bogus data assimilation scheme. Mon. Wea. Rev. 128, 2252-2269.
30. Yang, S. C., Corazza, M., Carrassi, A., Kalnay, E. and Miyoshi, T. 2009. Comparison of local ensemble transform Kalman filter, 3DVAR, and 4DVAR in a quasigeostrophic model. Mon. Wea. Rev. 137, 693-709.
31. Zhang, F., Zhang, M. and Hansen, J. A. 2009. Coupling ensemble Kalman filter with four- dimensional variational data assimilation. Adv. Atmos. Sci. 26, 1-8.
32. Zhao, J., Wang, B. and Liu, J.J. 2010. Impact of analysis-time tuning on the performance of DRP-4DVar approach. Adv. Atmos. Sci., doi.
33. Zou, X., and Kuo, Y.-H. 1996. Rainfall assimilation through an optimal control of initial and boundary conditions in a limited-area mesoscale model. Mon. Wea. Rev. 124, 2859-2882.