Ensemble kalman filter configurations and their performance with the logistic map

Monthly Weather Review

Volumn 137, Issue 12, 2009, Pages 4325-4343

  Mitchell, Herschel L ^a   Houtekamer, P L ^a  

^a ENVIRONMENT CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; ENSEMBLE MEMBERS; FORECAST MODEL; LOGISTIC MAPS; MEAN ERRORS;

KALMAN FILTERS; WEATHER FORECASTING;

UNCERTAINTY ANALYSIS;

DATA ASSIMILATION; ENSEMBLE FORECASTING; ESTIMATION METHOD; FORECASTING METHOD; KALMAN FILTER; LOGISTICS; STOCHASTICITY; UNCERTAINTY ANALYSIS; WEATHER FORECASTING;

EID: 70350341250     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/2009MWR2823.1     Document Type: Article

References (35)

1. Anderson, J.L., 2001: An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Rev., 129, 2884-2903.
2. Anderson, J.L., 2007: An adaptive covariance inflation error correction algorithm for ensemble filters. Tellus, 59A, 210-224.
3. Anderson, J.L., 2009: Spatially and temporally varying adaptive covariance inflation for ensemble filters. Tellus, 61A, 72-83.
4. Anderson, J.L., and S.L. Anderson, 1999: A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts. Mon. Wea. Rev., 127, 2741-2758.
5. Burgers, G., P. J. van Leeuwen, and G. Evensen, 1998: Analysis scheme in the ensemble Kalman filter. Mon. Wea. Rev., 126, 1719-1724.
6. Daley, R., 1991: Atmospheric Data Analysis. Cambridge University Press, 457 pp.
7. Dee D. P. 1995: On-line estimation of error covariance parameters for atmospheric data assimilation. Mon. Wea. Rev., 123, 1128-1145.
8. Dudewicz, E.J., and S.N. Mishra, 1988: Modern Mathematical Statistics. Wiley, 838 pp.
9. Efron B. 1982: The Jackknife, the Bootstrap and Other Resampling Plans. CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 38, SIAM, 92 pp.
10. Efron B., and R.J. Tibshirani 1993: An Introduction to the Bootstrap. Chapman and Hall, 436 pp.
11. Evensen G. 1994: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte-Carlo methods to forecast error statistics. J. Geophys. Res. 99, 10 143-10 162.
12. Evensen, G., 1997: Advanced data assimilation for strongly nonlinear dynamics. Mon. Wea. Rev. 125, 1342-1354.
13. Evensen, G., 2007: Data Assimilation: The Ensemble Kalman Filter. Springer, 279 pp.
14. Evensen G., and P. J. van Leeuwen 1996: Assimilation of Geosat altimeter data for the Agulhas Current using the ensemble Kalman filter with a quasigeostrophic model. Mon. Wea. Rev., 124, 85-96.
15. Gauthier, P., P. Courtier, and P. Moll, 1993: Assimilation of simulated wind lidar data with a Kalman filter. Mon. Wea. Rev., 121, 1803-1820.
16. Ghil, M., 1989: Meteorological data assimilation for oceanographers. Part I: Description and theoretical framework. Dyn. Atmos. Oceans, 13, 171-218.
17. Ghil, M., and P. Malanotte-Rizzoli, 1991: Data assimilation in meteorology and oceanography. Advances in Geophysics, Vol. 33, Academic Press, 141-266.
18. Hamill, T.M., and C. Snyder, 2000: A hybrid ensemble Kalman filter-3D variational analysis scheme. Mon. Wea. Rev., 128, 2905-2919.
19. Hamill, T.M., and J.S. Whitaker, 2005: Accounting for the error due to unresolved scales in ensemble data assimilation: A comparison of different approaches. Mon. Wea. Rev., 133, 3132-3147.
20. Houtekamer, P.L., and H.L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126, 796-811.
21. Houtekamer, P.L., and H.L. Mitchell, 2001: A sequential ensemble Kalman filter for at-mospheric data assimilation. Mon. Wea. Rev., 129, 123-137.
22. Houtekamer, P.L., and H.L. Mitchell, 2005: Ensemble Kalman filtering. Quart. J. Roy. Meteor. Soc., 131, 3269-3289.
23. Houtekamer, P.L., and H.L. Mitchell, and X. Deng, 2009: Model error representation in an operational ensemble Kalman filter. Mon. Wea. Rev., 137, 2126-2143.
24. Lawson, W.G., and J.A. Hansen, 2004: Implications of stochastic and deterministic filters as ensemble-based data assimilation methods in varying regimes of error growth. Mon. Wea. Rev., 132, 1966-1981.
25. Mitchell, H.L., and P.L. Houtekamer, 2000: An adaptive ensemble Kalman filter. Mon. Wea. Rev., 128, 416-433.
26. Mitchell, H.L., and P.L. Houtekamer, and G. Pellerin, 2002: Ensemble size, balance, and model-error representation in an ensemble Kalman filter. Mon. Wea. Rev., 130, 2791-2808.
27. Pham, D.T., 2001: Stochastic methods for sequential data assimilation in strongly nonlinear systems. Mon. Wea. Rev., 129, 1194-1207.
28. Sacher, W., and P. Bartello, 2008: Sampling errors in ensemble Kalman filtering. Part I: Theory. Mon. Wea. Rev., 136, 3035-3049.
29. Schuster, H.G., and W. Just, 2005: Deterministic Chaos: An Introduction. 4th ed. Wiley, 287 pp.
30. Strogatz S. H. 1994: Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. Addison-Wesley, 498 pp.
31. Talagrand O., G. Candille, and L. Deschamps 2007: On some aspects of validation of probabilistic prediction. Proc. ECMWF Workshop on Ensemble Prediction, Reading, United Kingdom, ECMWF, 1-12.
32. Tippett, M.K., J.L. Anderson, C.H. Bishop, T.M. Hamill, and J.S. Whitaker, 2003: Ensemble square root filters. Mon. Wea. Rev., 131, 1485-1490.
33. Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of perturbations. Bull. Amer. Meteor. Soc., 74, 2317-2330.
34. Whitaker, J.S., and T.M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913-1924.
35. Wilks, D.S., 2006: Statistical Methods in the Atmospheric Sciences. 2d ed. Academic Press, 627 pp.