Estimating and correcting global weather model error

Monthly Weather Review

Volumn 135, Issue 2, 2007, Pages 281-299

  Danforth, Christopher M ^a   Kalnay, Eugenia ^b   Miyoshi, Takemasa ^c  

^a UNIVERSITY OF MARYLAND   (United States)

^b Bldg 142   (United States)

^c JAPAN METEOROLOGICAL AGENCY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COVARIANCE MATRIX; DATA REDUCTION; ERROR ANALYSIS; MATHEMATICAL MODELS; METEOROLOGY; SINGULAR VALUE DECOMPOSITION; STATISTICAL METHODS; WEATHER FORECASTING;

DATA ASSIMILATION; LEITH COVARIANCE; MODEL INTEGRATION;

WEATHER MODIFICATION;

DATA ASSIMILATION; ERROR ANALYSIS; ESTIMATION METHOD; MODEL; STATISTICAL ANALYSIS; WEATHER FORECASTING;

EID: 33847379878     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/MWR3289.1     Document Type: Article

References (35)

1. Anderson, J., 2001: An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Rev., 129, 2884-2903.
2. Barnston, A., M. Glantz, and Y. He, 1999: Predictive skill of statistical and dynamical climate models in SST forecasts during the 1997-98 El Niño episode and the 1998 La Niña onset. Bull. Amer. Meteor. Soc., 80, 217-243.
3. Bishop, C., B. Etherton, and S. Majumdar, 2001: Adaptive sampling with the ensemble transform Kalman filter. Part I: The theoretical aspects. Mon. Wea. Rev., 129, 420-436.
4. Bretherton, C., C. Smith, and J. Wallace, 1992: An intercomparison of methods for finding coupled patterns in climate data. J. Climate, 5, 541-560.
5. Carter, G., J. Dallavalle, and H. Glahn, 1989: Statistical forecasts based on the National Meteorological Center's numerical weather prediction system. Wea. Forecasting, 4, 401-412.
6. Dalcher, A., and E. Kalnay, 1987: Error growth and predictability in operational ECMWF forecasts. Tellus, 39, 474-491.
7. D'Andrea, F., and R. Vautard, 2000: Reducing systematic errors by empirically correcting model errors. Tellus, 52A, 21-41.
8. Danforth, C. M., and J. A. Yorke, 2006: Making forecasts for chaotic physical processes. Phys. Rev. Lett., 96, 144102, doi:10.1103/ PhysRevLett.96.144102.
9. DelSole, T., and A. Y. Hou, 1999: Empirical correction of a dynamical model. Part I: Fundamental issues. Mon. Wea. Rev., 127, 2533-2545.
10. Faller, A., and C. Schemm, 1977: Statistical corrections to numerical prediction equations. II. Mon. Wea. Rev., 105, 37-56.
11. Ferranti, L., E. Klinker, A. Hollingsworth, and B. Hoskins, 2002: Diagnosis of systematic forecast errors dependent on flow anomalies. Quart. J. Roy. Meteor. Soc., 128, 1623-1640.
12. Glahn, H., and D. Lowry, 1972: The use of model output statistics in objective weather forecasting. J. Appl. Meteor., 11, 1203-1211.
13. Golub, G., and C. Van Loan, 1996: Matrix Computations. Johns Hopkins University Press, 694 pp.
14. Hamill, T., and C. Snyder, 2000: A hybrid ensemble Kalman filter-3D variational analysis scheme. Mon. Wea. Rev., 128, 2905-2919.
15. Hoke, J. E., and R. A. Anthes, 1976: The initialization of numerical models by a dynamic initialization technique. Mon. Wea. Rev., 104, 1551-1556.
16. Houtekamer, P., and H. Mitchell, 2001: A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev., 129, 796-811.
17. Hunt, B., and Coauthors, 2004: Four-dimensional ensemble Kalman filtering. Tellus, 56, 273-277.
18. Kaas, E., A. Guldberg, W. May, and M. Deque, 1999: Using tendency errors to tune parameterization of unresolved dynamical scale interactions in atmospheric general circulation models. Tellus, 51, 612-629.
19. Kalnay, E., 2003: Atmospheric Modelling, Data Assimilation and Predictability. Cambridge University Press, 341 pp.
20. Klinker, E., and P. Sardeshmukh, 1992: The diagnosis of mechanical dissipation in the atmosphere from large-scale balance requirements. J. Atmos. Sci., 49, 608-627.
21. Leith, C. E., 1978: Objective methods for weather prediction. Annu. Rev. Fluid Mech., 10, 107-128.
22. Leith, C. E., 1991: Data assimilation in meteorology and oceanography. Advances in Geophysics, Vol. 33, Academic Press, 141-266.
23. Marshall, C. H., K. C. Crawford, K. E. Mitchell, and D. J. Stensrud, 2003: The impact of the land surface physics in the operational NCEP Eta model on simulating the diurnal cycle: Evaluation and testing using Oklahoma Mesonet data. Wea. Forecasting, 18, 748-768.
24. Marshall, J., and F. Molteni, 1993: Toward a dynamical understanding of planetary-scale flow regimes. J. Atmos. Sci., 50, 1792-1818.
25. Miyoshi, T., 2005: Ensemble Kalman filter experiments with a primitive-equation global model. Ph.D. dissertation, University of Maryland, College Park, 226 pp.
26. Molteni, F., 2003: Atmospheric simulations using a GCM with simplified physical parametrizations. I: Model climatology and variability in multi-decadal experiments. Climate Dyn., 20, 175-191.
27. Ott, E., and Coauthors, 2004: A local ensemble Kalman filter for atmospheric data assimilation. Tellus, 56, 415-428.
28. Parrish, D., and J. Derber, 1992: The National Meteorological Center's spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747-1763.
29. Renwick, J., and J. Wallace, 1995: Predictable anomaly patterns and the forecast skill of Northern Hemisphere wintertime 500-mb height fields. Mon. Wea. Rev., 123, 2114-2131.
30. Reynolds, C., P. J. Webster, and E. Kalnay, 1994: Random error growth in NMC's global forecasts. Mon. Wea. Rev., 122, 1281-1305.
31. Saha, S., 1992: Response of the NMC MRF model to systematic error correction within integration. Mon. Wea. Rev., 120, 345-360.
32. Schemm, C., D. Unger, and A. Faller, 1981: Statistical corrections to numerical predictions III. Mon. Wea. Rev., 109, 96-109.
33. Schemm, J.-K., and A. Faller, 1986: Statistical corrections to numerical predictions. Part IV. Mon. Wea. Rev., 114, 2402-2417.
34. Wallace, J., C. Smith, and C. Bretherton, 1992: Singular value decomposition of wintertime sea surface temperature and 500-mb height anomalies. J. Climate, 5, 561-576.
35. Whitaker, J., and T. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913-1924.