A new measure of ensemble performance: Perturbation versus error correlation analysis (PECA)

Monthly Weather Review

Volumn 131, Issue 8 PART 1, 2003, Pages 1549-1565

  Wei, Mozheng ^a   Toth, Zoltan ^b  

^a CLIMATE PREDICTION CENTER   (United States)

^b SCIENCE APPLICATIONS INTERNATIONAL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; DATA REDUCTION; ERROR ANALYSIS; METEOROLOGY; PERTURBATION TECHNIQUES;

DATA ASSIMILATION;

WEATHER FORECASTING;

MODELING; NUMERICAL METHOD; WEATHER FORECASTING;

EID: 0141459914     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175//1520-0493(2003)131<1549:ANMOEP>2.0.CO;2     Document Type: Article

References (28)

1. Atger, F., 1999: The skill of ensemble prediction systems. Mon. Wea. Rev., 127, 1941-1953.
2. Barkmeijer, J., R. Buizza, and T. N. Palmer, 1999: 3D-Var Hessian singular vectors and their potential use in the ECMWF Ensemble Prediction System. Quart. J. Roy. Meteor. Soc., 125, 2333-2351.
3. Barkmeijer, J., R. Buizza, T. N. Palmer, K. Puri, and J.-F. Mahfouf, 2001: Tropical singular vectors computed with linearized diabatic physics. Quart. J. Roy. Meteor. Soc., 127, 685-708.
4. Bishop, C. H., B. J. Etherton, and S. J. Majumdar, 2001: Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects. Mon. Wea. Rev., 129, 420-436.
5. Buizza, R., and T. N. Palmer, 1995: The singular-vector structure of the atmospheric global circulation. J. Atmos. Sci., 52, 1434-1456.
6. Buizza, R., and T. N. Palmer, 1999: Ensemble data assimilation. Preprints, 17th Conf. on Weather Analysis and Forecasting, Denver, CO, Amer. Meteor. Soc., 231-234.
7. Frederiksen, J. S., 2000: Singular vectors, finite-time normal modes and error growth during blocking. J. Atmos. Sci., 57, 312-333.
8. Holton, J., 1992: An Introduction to Dynamic Meteorology. Academic Press, 511 pp.
9. Houtekamer, P. L., L. Lefaivre, J. Derome, H. Ritchie, and H. L. Mitchell, 1996: A system simulation approach to ensemble prediction. Mon. Wea. Rev., 124, 1225-1242.
10. Molteni, F., and R. Buizza, 1999: Validation of the ECMWF Ensemble Prediction System using empirical orthogonal functions. Mon. Wea. Rev., 127, 2346-2358.
11. Molteni, F., R. Buizza, T. Palmer, and T. Petroliagis, 1996: The ECMWF ensemble prediction system: Methodology and validation. Quart. J. Roy. Meteor. Soc., 122, 73-119.
12. Parrish, D. F., and J. Derber, 1992: The National Meteorological Center's spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747-1763.
13. Rabier, F., E. Klinker, P. Courtier, and A. Hollingsworth, 1996: Sensitivity of forecast errors to initial conditions. Quart. J. Roy. Meteor. Soc., 122, 121-150.
14. Reynolds, C. A., and R. M. Errico, 1999: Convergence of singular vectors toward Lyapunov vectors. Mon. Wea. Rev., 127, 2309-2323.
15. Richardson, D. S., 2000: Skill and economic value of the ECMWF Ensemble Prediction System. Quart. J. Roy. Meteor. Soc., 126, 649-668.
16. Saha, S., cited 2001: Empirical orthogonal teleconnections (EOT). An analysis of NCEP and ECMWF forecast error patterns. [Available online at http://www.emc.ncep.noaa.gov/gmb/ssaha.]
17. Stanski, H. R., L. J. Wilson, and W. R. Burrows, 1989: Survey of common verification methods in meteorology. World Weather Watch Tech. Rep. 8, WMO/TD 358, 144 pp.
18. Stephenson, D. B., and F. J. Doblas-Reyes, 2000: Statistical methods for interpreting Monte Carlo ensemble forecasts. Tellus, 52A, 300-322.
19. Szunyogh, I., E. Kalnay, and Z. Toth, 1997: A comparison of Lyapunov and optimal vectors in a low-resolution GCM. Tellus, 48A, 200-227.
20. Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of perturbations. Bull. Amer. Meteor. Soc., 74, 2317-2330.
21. Toth, Z., and E. Kalnay, 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev., 125, 3297-3319.
22. Toth, Z., and S. Vannitsem, 2002: Model errors and ensemble forecasting. Proc. Eighth ECMWF Workshop on Meteorological Operational Systems, Reading, United kingdom, ECMWF, 146-154.
23. Toth, Z., O. Talagrand, G. Candille, and Y. Zhu, 2002: Probability and ensemble forecasts. Environmental Forecast Verification: A Practitioner's Guide in Atmospheric Science, I. T. Jolliffe and D. B. Stephenson, Eds., John Wiley, in press.
24. Van den Dool, H. M., and L. Rukhovets, 1994: On the weights for an ensemble averaged 6-10-day forecast at NMC. Wea. Forecasting, 9, 457-465.
25. Van den Dool, H. M., S. Saha, and A. Johansson, 2000: Empirical orthogonal teleconnections. J. Climate, 13, 1421-1435.
26. Wang, X., and C. H. Bishop, 2002: A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes. Preprints, Symp. on Observations, Data Assimilation, and Probabilistic Prediction, Orlando, FL. J28-J31.
27. Wei, M., 2000: Quantifying local instability and predictability of chaotic dynamical system by means of local metric entropy. Int. J. Bifurcation Chaos, 10, 135-154.
28. Zhu, Y., Z. Toth, R. Wobus, D. Richardson, and K. Mylne, 2002: The economic value of ensemble-based weather forecasts. Bull. Amer. Meteor. Soc., 83, 73-83.