메뉴 건너뛰기




Volumn 138, Issue 662, 2012, Pages 263-273

Maximum likelihood estimation of inflation factors on error covariance matrices for ensemble Kalman filter assimilation

Author keywords

Data assimilation; Error covariance inflation; Parameter estimation

Indexed keywords

CORRELATED OBSERVATIONS; DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; ERROR COVARIANCE INFLATION; ERROR COVARIANCES; FORECAST ERRORS; INFLATION FACTORS; INFLATION METHOD; LORENZ MODEL; OBSERVATION ERRORS; TIME-DEPENDENT; TWO-DIMENSIONAL SHALLOW WATER EQUATIONS;

EID: 84856232855     PISSN: 00359009     EISSN: 1477870X     Source Type: Journal    
DOI: 10.1002/qj.912     Document Type: Article
Times cited : (49)

References (22)
  • 1
    • 34247642674 scopus 로고    scopus 로고
    • An adaptive covariance inflation error correction algorithm for ensemble filters
    • Anderson JL. 2007. An adaptive covariance inflation error correction algorithm for ensemble filters. Tellus 59A: 210-224.
    • (2007) Tellus , vol.59 , pp. 210-224
    • Anderson, J.L.1
  • 2
    • 58049084742 scopus 로고    scopus 로고
    • Spatially and temporally varying adaptive covariance inflation for ensemble filters
    • Anderson JL. 2009. Spatially and temporally varying adaptive covariance inflation for ensemble filters. Tellus 61A: 72-83.
    • (2009) Tellus , vol.61 , pp. 72-83
    • Anderson, J.L.1
  • 3
    • 0033500692 scopus 로고    scopus 로고
    • A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts
    • Anderson JL, Anderson SL. 1999. A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts. Mon. Weather Rev. 127: 2741-2758.
    • (1999) Mon. Weather Rev. , vol.127 , pp. 2741-2758
    • Anderson, J.L.1    Anderson, S.L.2
  • 6
    • 0000991256 scopus 로고
    • On-line estimation of error covariance parameters for atmospheric data assimilation
    • Dee DP. 1995. On-line estimation of error covariance parameters for atmospheric data assimilation. Mon. Weather Rev. 123: 1128-1145.
    • (1995) Mon. Weather Rev. , vol.123 , pp. 1128-1145
    • Dee, D.P.1
  • 7
    • 0032750664 scopus 로고    scopus 로고
    • Maximum-likelihood estimation of forecast and observation error covariance parameters. Part I: Methodology.
    • Dee DP, da Silva AM. 1999. Maximum-likelihood estimation of forecast and observation error covariance parameters. Part I: Methodology. Mon. Weather Rev. 127: 1822-1834.
    • (1999) Mon. Weather Rev. , vol.127 , pp. 1822-1834
    • Dee, D.P.1    da Silva, A.M.2
  • 8
    • 0032728136 scopus 로고    scopus 로고
    • Maximum-likelihood estimation of forecast and observation error covariance parameters. Part II: Applications.
    • Dee DP, Gaspari G, Redder C, Rukhovets L, da Silva AM. 1999. Maximum-likelihood estimation of forecast and observation error covariance parameters. Part II: Applications. Mon. Weather Rev. 127: 1835-1849.
    • (1999) Mon. Weather Rev. , vol.127 , pp. 1835-1849
    • Dee, D.P.1    Gaspari, G.2    Redder, C.3    Rukhovets, L.4    da Silva, A.M.5
  • 9
    • 0028193070 scopus 로고
    • Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
    • C5
    • Evensen G. 1994a. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. 99C5 10143-10162.
    • (1994) J. Geophys. Res. , vol.99 , pp. 10143-10162
    • Evensen, G.1
  • 10
    • 0000601815 scopus 로고
    • Inverse methods and data assimilation in nonlinear ocean models
    • Evensen G. 1994b. Inverse methods and data assimilation in nonlinear ocean models. Physica D 77: 108-129.
    • (1994) Physica D , vol.77 , pp. 108-129
    • Evensen, G.1
  • 11
    • 84884550570 scopus 로고    scopus 로고
    • The ensemble Kalman filter: Theoretical formulation and practical implementation
    • Evensen G. 2003. The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn. 53: 343-367.
    • (2003) Ocean Dyn. , vol.53 , pp. 343-367
    • Evensen, G.1
  • 13
    • 22444452396 scopus 로고    scopus 로고
    • Unified notation for data assimilation: Operational, sequential and variational
    • Ide K, Courtier P, Ghil M, Lorenc AC. 1997. Unified notation for data assimilation: Operational, sequential and variational. J. Meteorol. Soc. Jpn 75: 181-189.
    • (1997) J. Meteorol. Soc. Jpn , vol.75 , pp. 181-189
    • Ide, K.1    Courtier, P.2    Ghil, M.3    Lorenc, A.C.4
  • 14
    • 84856209867 scopus 로고    scopus 로고
    • rd Conference on Weather analysis and forecasting/19th Conference on Numerical weather prediction, Omaha, Nebraska, 1-5 Jun 2009. American Meteorological Society: Boston, MA.
    • rd Conference on Weather analysis and forecasting/19th Conference on Numerical weather prediction, Omaha, Nebraska, 1-5 Jun 2009. American Meteorological Society: Boston, MA.
    • (2009)
    • Lei, L.L.1    Stauffer, D.R.2
  • 15
    • 66849124453 scopus 로고    scopus 로고
    • Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter
    • Li H, Kalnay E, Miyoshi T. 2009. Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter. Q. J. R. Meteorol. Soc. 135: 523-533.
    • (2009) Q. J. R. Meteorol. Soc. , vol.135 , pp. 523-533
    • Li, H.1    Kalnay, E.2    Miyoshi, T.3
  • 16
    • 84856230566 scopus 로고    scopus 로고
    • Predictability: A problem partly solved'. In Proc. Seminar on Predictability, Shinfield Park, Reading, UK, 4-8 September 1995. European Centre for Medium-Range Weather Forecasts: Reading.
    • Lorenz EN. 1996. 'Predictability: A problem partly solved'. In Proc. Seminar on Predictability, Shinfield Park, Reading, UK, 4-8 September 1995. European Centre for Medium-Range Weather Forecasts: Reading.
    • (1996)
    • Lorenz, E.N.1
  • 17
    • 0032004313 scopus 로고    scopus 로고
    • Optimal sites for supplementary weather observations: Simulation with a small model
    • Lorenz EN, Emanuel KA. 1998. Optimal sites for supplementary weather observations: Simulation with a small model. J. Atmos. Sci. 55: 399-414.
    • (1998) J. Atmos. Sci. , vol.55 , pp. 399-414
    • Lorenz, E.N.1    Emanuel, K.A.2
  • 20
    • 0037980372 scopus 로고    scopus 로고
    • A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes
    • Wang X, Bishop CH. 2003. A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes. J. Atmos. Sci. 60: 1140-1158.
    • (2003) J. Atmos. Sci. , vol.60 , pp. 1140-1158
    • Wang, X.1    Bishop, C.H.2
  • 21
    • 0036646009 scopus 로고    scopus 로고
    • Ensemble data assimilation without perturbed observations
    • Whitaker JS, Hamill TH. 2002. Ensemble data assimilation without perturbed observations. Mon. Weather Rev. 130: 1913-1924.
    • (2002) Mon. Weather Rev. , vol.130 , pp. 1913-1924
    • Whitaker, J.S.1    Hamill, T.H.2
  • 22
    • 67649379073 scopus 로고    scopus 로고
    • An adaptive estimation of forecast error covariance parameters for Kalman filtering data assimilation
    • Zheng XG. 2009. An adaptive estimation of forecast error covariance parameters for Kalman filtering data assimilation. Adv. Atmos. Sci. 26: 154-160.
    • (2009) Adv. Atmos. Sci. , vol.26 , pp. 154-160
    • Zheng, X.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.