메뉴 건너뛰기




Volumn 138, Issue 3, 2010, Pages 962-981

Predictability of the performance of an ensemble forecast system: Predictability of the space of uncertainties

Author keywords

[No Author keywords available]

Indexed keywords

DATA ASSIMILATION SYSTEMS; ENSEMBLE FORECAST SYSTEMS; ENSEMBLE PERFORMANCE; ENSEMBLE PERTURBATION; ENSEMBLE PREDICTION SYSTEMS; ERROR GROWTH; FORECAST TIME; FORECAST UNCERTAINTY; GLOBAL FORECAST SYSTEMS; LINEAR REPRESENTATION; LINEAR SPACES; LOCAL ERROR; LOCAL REGION; NATIONAL CENTERS FOR ENVIRONMENTAL PREDICTIONS; PERFECT MODEL; TIME EVOLUTIONS;

EID: 77953199182     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/2009MWR3049.1     Document Type: Article
Times cited : (9)

References (21)
  • 1
    • 34248655165 scopus 로고    scopus 로고
    • Exploring the need for localization in ensemble data assimilation using a hierarchical ensemble filter
    • Anderson, J. L., 2007: Exploring the need for localization in ensemble data assimilation using a hierarchical ensemble filter. Physica D, 230 (1-2), 99-111.
    • (2007) Physica D , vol.230 , Issue.1-2 , pp. 99-111
    • Anderson, J.L.1
  • 2
    • 69849107882 scopus 로고    scopus 로고
    • A spectral stochastic kinetic energy backscatter scheme and its impact on flow-dependent predictability in the ECMWF ensemble prediction system
    • Berner, J., G. Shutts, M. Leutbecher, and T. Palmer, 2009: A spectral stochastic kinetic energy backscatter scheme and its impact on flow-dependent predictability in the ECMWF ensemble prediction system. J. Atmos. Sci., 66, 603-626.
    • (2009) J. Atmos. Sci. , vol.66 , pp. 603-626
    • Berner, J.1    Shutts, G.2    Leutbecher, M.3    Palmer, T.4
  • 4
    • 0035891673 scopus 로고    scopus 로고
    • Linear regime duration: Is 24 hours a long time in synoptic weather forecasting?
    • Gilmour, I., L. A. Smith, and R. Buizza, 2001: Linear regime duration: Is 24 hours a long time in synoptic weather forecasting? J. Atmos. Sci., 58, 3525-3539.
    • (2001) J. Atmos. Sci. , vol.58 , pp. 3525-3539
    • Gilmour, I.1    Smith, L.A.2    Buizza, R.3
  • 5
    • 0035506430 scopus 로고    scopus 로고
    • Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter
    • Hamill, T., J. Whitaker, and C. Snyder, 2001: Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129, 2776-2790.
    • (2001) Mon. Wea. Rev. , vol.129 , pp. 2776-2790
    • Hamill, T.1    Whitaker, J.2    Snyder, C.3
  • 6
    • 0035129828 scopus 로고    scopus 로고
    • A sequential ensemble kalman Filter for atmospheric data assimilation
    • Houtekamer, P., and H. Mitchell, 2001: A sequential ensemble kalman Filter for atmospheric data assimilation. Mon. Wea. Rev., 129, 123-137.
    • (2001) Mon. Wea. Rev. , vol.129 , pp. 123-137
    • Houtekamer, P.1    Mitchell, H.2
  • 7
    • 0000705199 scopus 로고
    • Diabatic digital filtering initialization: Application to the HIRLAM model
    • Huang, X.-Y., and P. Lynch, 1993: Diabatic digital filtering initialization: Application to the HIRLAM model. Mon. Wea. Rev., 121, 589-603.
    • (1993) Mon. Wea. Rev. , vol.121 , pp. 589-603
    • Huang, X.-Y.1    Lynch, P.2
  • 8
    • 34248675795 scopus 로고    scopus 로고
    • Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter
    • Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D, 230 (1-2), 112-126.
    • (2007) Physica D , vol.230 , Issue.1-2 , pp. 112-126
    • Hunt, B.R.1    Kostelich, E.J.2    Szunyogh, I.3
  • 10
    • 34247589234 scopus 로고    scopus 로고
    • Assessing predictability with a local ensemble Kalman filter
    • Kuhl, D., and Coauthors, 2007: Assessing predictability with a local ensemble Kalman filter. J. Atmos. Sci., 64, 1116-1140.
    • (2007) J. Atmos. Sci. , vol.64 , pp. 1116-1140
    • Kuhl, D.1
  • 11
    • 14944338900 scopus 로고    scopus 로고
    • Mechanisms for the development of locally low-dimensional atmospheric dynamics
    • Oczkowski, M., I. Szunyogh, and D. J. Patil, 2005: Mechanisms for the development of locally low-dimensional atmospheric dynamics. J. Atmos. Sci., 62, 1135-1156.
    • (2005) J. Atmos. Sci. , vol.62 , pp. 1135-1156
    • Oczkowski, M.1    Szunyogh, I.2    Patil, D.J.3
  • 12
    • 77953180433 scopus 로고    scopus 로고
    • Palmer, T., Hagedorn R. Eds., Cambridge University Press
    • Palmer, T., and R. Hagedorn, Eds., 2006: Predictability of Weather and Climate. Cambridge University Press, 718 pp.
    • (2006) Predictability of Weather and Climate , pp. 718
  • 13
  • 15
    • 0142153709 scopus 로고    scopus 로고
    • Nonlinear growth of singular-vector-based perturbations
    • Reynolds, C. A., and T. E. Rosmond, 2003: Nonlinear growth of singular-vector-based perturbations. Quart. J. Roy. Meteor. Soc., 129, 3059-3078.
    • (2003) Quart. J. Roy. Meteor. Soc. , vol.129 , pp. 3059-3078
    • Reynolds, C.A.1    Rosmond, T.E.2
  • 16
    • 43449125128 scopus 로고    scopus 로고
    • Impact of data assimilation filtering methods on the mesosphere
    • D24104, doi:10.1029/2007JD008885
    • Sankey, D., S. Ren, S. Polavarapu, Y. J. Rochon, Y. Nezlin, and S. Beagley, 2007: Impact of data assimilation filtering methods on the mesosphere. J. Geophys. Res., 112, D24104, doi:10.1029/2007JD008885.
    • (2007) J. Geophys. Res. , vol.112
    • Sankey, D.1    Ren, S.2    Polavarapu, S.3    Rochon, Y.J.4    Nezlin, Y.5    Beagley, S.6
  • 17
    • 27744434698 scopus 로고    scopus 로고
    • Assessing a local ensemble Kalman filter: Perfect model experiments with the National Centers for Environmental Prediction global model
    • Szunyogh, I., E. J. Kostelich, G. Gyarmati, D. J. Patil, B. R. Hunt, E. Ott, E. Kalnay, and J. A. York, 2005: Assessing a local ensemble Kalman filter: Perfect model experiments with the National Centers for Environmental Prediction global model. Tellus, 57A, 528-545.
    • (2005) Tellus , vol.57 A , pp. 528-545
    • Szunyogh, I.1    Kostelich, E.J.2    Gyarmati, G.3    Patil, D.J.4    Hunt, B.R.5    Ott, E.6    Kalnay, E.7    York, J.A.8
  • 18
    • 53649103809 scopus 로고    scopus 로고
    • The local ensemble transform Kalman filter and its implementation on the NCEP global model at the University of Maryland
    • Reading, United Kingdom, ECMWF
    • Szunyogh, I., and Coauthors, 2007: The local ensemble transform Kalman filter and its implementation on the NCEP global model at the University of Maryland. Proc. Workshop on Flow-Dependent Aspects of Data Assimilation, Reading, United Kingdom, ECMWF, 47-63.
    • (2007) Proc. Workshop on Flow-Dependent Aspects of Data Assimilation , pp. 47-63
    • Szunyogh, I.1
  • 20
    • 0141459914 scopus 로고    scopus 로고
    • A new measure of ensemble performance: Perturbation versus error correlation analysis (PECA)
    • Wei, M., and Z. Toth, 2003: A new measure of ensemble performance: Perturbation versus error correlation analysis (PECA). Mon. Wea. Rev., 131, 1549-1565.
    • (2003) Mon. Wea. Rev. , vol.131 , pp. 1549-1565
    • Wei, M.1    Toth, Z.2
  • 21
    • 0036646009 scopus 로고    scopus 로고
    • Ensemble data assimilation without perturbed observations
    • Whitaker, J., and T. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913-1924.
    • (2002) Mon. Wea. Rev. , vol.130 , pp. 1913-1924
    • Whitaker, J.1    Hamill, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.