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Volumn 144, Issue 3, 2016, Pages 913-925

Reducing correlation sampling error in ensemble Kalman filter data assimilation

Author keywords

Bayesian methods; Data assimilation; Ensembles; Kalman filters; Mathematical and statistical techniques; Models and modeling

Indexed keywords

ALGORITHMS; BANDPASS FILTERS; BAYESIAN NETWORKS; EARTH ATMOSPHERE; GEOPHYSICS; KALMAN FILTERS; SAMPLING;

EID: 84961391800     PISSN: 00270644     EISSN: 15200493     Source Type: Journal    
DOI: 10.1175/MWR-D-15-0052.1     Document Type: Article
Times cited : (27)

References (44)
  • 1
    • 0035655814 scopus 로고    scopus 로고
    • An ensemble adjustment Kalman filter for data assimilation
    • Anderson, J. L., 2001: An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Rev., 129, 2884-2903, doi:10.1175/1520-0493(2001)129<2884:AEAKFF>2.0.CO;2.
    • (2001) Mon. Wea. Rev , vol.129 , pp. 2884-2903
    • Anderson, J.L.1
  • 2
    • 0042821672 scopus 로고    scopus 로고
    • A local least squares framework for ensemble filtering
    • Anderson, J. L., 2003: A local least squares framework for ensemble filtering. Mon. Wea. Rev., 131, 634-642, doi:10.1175/1520-0493(2003)131<0634:ALLSFF>2.0.CO;2.
    • (2003) Mon. Wea. Rev , vol.131 , pp. 634-642
    • Anderson, J.L.1
  • 3
    • 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, 99-111, doi:10.1016/j.physd.2006.02.011.
    • (2007) Physica D , vol.230 , pp. 99-111
    • Anderson, J.L.1
  • 4
    • 58049084742 scopus 로고    scopus 로고
    • Spatially and temporally varying adaptive covariance inflation for ensemble filters
    • Anderson, J. L., 2009a: Spatially and temporally varying adaptive covariance inflation for ensemble filters. Tellus, 61A, 72-83, doi:10.1111/j.1600-0870.2008.00361.x.
    • (2009) Tellus , vol.61A , pp. 72-83
    • Anderson, J.L.1
  • 5
    • 66849106318 scopus 로고    scopus 로고
    • Ensemble Kalman filters for large geophysical applications
    • Anderson, J. L., 2009b: Ensemble Kalman filters for large geophysical applications. IEEE Contr. Syst. Mag., 29, 66-82, doi:10.1109/MCS.2009.932222.
    • (2009) IEEE Contr. Syst. Mag , vol.29 , pp. 66-82
    • Anderson, J.L.1
  • 6
    • 84864864640 scopus 로고    scopus 로고
    • Localization and sampling error correction in ensemble Kalman filter data assimilation
    • Anderson, J. L., 2012: Localization and sampling error correction in ensemble Kalman filter data assimilation. Mon. Wea. Rev., 140, 2359-2371, doi:10.1175/MWR-D-11-00013.1.
    • (2012) Mon. Wea. Rev , vol.140 , pp. 2359-2371
    • Anderson, J.L.1
  • 7
    • 0033500692 scopus 로고    scopus 로고
    • A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts
    • 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, doi:10.1175/1520-0493(1999)127<2741:AMCIOT>2.0.CO;2.
    • (1999) Mon. Wea. Rev , vol.127 , pp. 2741-2758
    • Anderson, J.L.1    Anderson, S.L.2
  • 8
    • 34548625197 scopus 로고    scopus 로고
    • Scalable implementations of ensemble filter algorithms for data assimilation
    • Anderson, J. L., and N. Collins, 2007: Scalable implementations of ensemble filter algorithms for data assimilation. J. Atmos. Oceanic Technol., 24, 1452-1463, doi:10.1175/JTECH2049.1.
    • (2007) J. Atmos. Oceanic Technol , vol.24 , pp. 1452-1463
    • Anderson, J.L.1    Collins, N.2
  • 9
    • 84888414100 scopus 로고    scopus 로고
    • Empirical localization of observation impact in ensemble Kalman filters
    • Anderson, J. L., and L. Lei, 2013: Empirical localization of observation impact in ensemble Kalman filters. Mon. Wea. Rev., 141, 4140-4153, doi:10.1175/MWR-D-12-00330.1.
    • (2013) Mon. Wea. Rev , vol.141 , pp. 4140-4153
    • Anderson, J.L.1    Lei, L.2
  • 10
    • 26244457168 scopus 로고    scopus 로고
    • Assimilation of surface pressure observations using an ensemble filter in an idealized global atmospheric prediction system
    • Anderson, J. L., B. Wyman, S. Zhang, and T. Hoar, 2005: Assimilation of surface pressure observations using an ensemble filter in an idealized global atmospheric prediction system. J. Atmos. Sci., 62, 2925-2938, doi:10.1175/JAS3510.1.
    • (2005) J. Atmos. Sci , vol.62 , pp. 2925-2938
    • Anderson, J.L.1    Wyman, B.2    Zhang, S.3    Hoar, T.4
  • 12
    • 38849152191 scopus 로고    scopus 로고
    • Flow adaptive moderation of spurious ensemble correlations and its use in ensemble based data assimilation
    • Bishop, C. H., and D. Hodyss, 2007: Flow adaptive moderation of spurious ensemble correlations and its use in ensemble based data assimilation. Quart. J. Roy. Meteor. Soc., 133, 2029-2044, doi:10.1002/qj.169.
    • (2007) Quart. J. Roy. Meteor. Soc , vol.133 , pp. 2029-2044
    • Bishop, C.H.1    Hodyss, D.2
  • 13
    • 58049107252 scopus 로고    scopus 로고
    • Ensemble covariances adaptively localized with ECO-RA. Part 1: Tests on simple error models
    • Bishop, C. H., and D. Hodyss, 2009: Ensemble covariances adaptively localized with ECO-RAP. Part 1: Tests on simple error models. Tellus, 61A, 84-96, doi:10.1111/j.1600-0870.2008.00371.x.
    • (2009) Tellus , vol.61A , pp. 84-96
    • Bishop, C.H.1    Hodyss, D.2
  • 14
    • 0032439201 scopus 로고    scopus 로고
    • Analysis scheme in the ensemble Kalman filter
    • Burgers, G., P. J. van Leeuwen, and G. Evensen, 1998: Analysis scheme in the ensemble Kalman filter. Mon. Wea. Rev., 126, 1719-1724, doi:10.1175/1520-0493(1998)126<1719: ASITEK>2.0.CO;2.
    • (1998) Mon. Wea. Rev , vol.126 , pp. 1719-1724
    • Burgers, G.1    van Leeuwen, P.J.2    Evensen, G.3
  • 15
    • 84871880523 scopus 로고    scopus 로고
    • Evaluation of theAdvancedHurricane WRF data assimilation system for the 2009 Atlantic hurricane season
    • Cavallo, S. M., R. D. Torn, C. Snyder, C. Davis, W. Wang, and J.Done, 2013: Evaluation of theAdvancedHurricane WRF data assimilation system for the 2009 Atlantic hurricane season. Mon. Wea. Rev., 141, 523-541, doi:10.1175/MWR-D-12-00139.1.
    • (2013) Mon. Wea. Rev , vol.141 , pp. 523-541
    • Cavallo, S.M.1    Torn, R.D.2    Snyder, C.3    Davis, C.4    Wang, W.5    Done, J.6
  • 16
    • 77952887324 scopus 로고    scopus 로고
    • Cross-covariances and localization for EnKF in multiphase flow data assimilation
    • Chen, Y., and D. S. Oliver, 2010: Cross-covariances and localization for EnKF in multiphase flow data assimilation. Comput. Geosci., 14, 579-601, doi:10.1007/s10596-009-9174-6.
    • (2010) Comput. Geosci , vol.14 , pp. 579-601
    • Chen, Y.1    Oliver, D.S.2
  • 17
    • 79952438014 scopus 로고    scopus 로고
    • Combining sensitivities and prior information for covariance localization in the ensemble Kalman filter for petroleum reservoir applications
    • Emerick, A., and A. Reynolds, 2011: Combining sensitivities and prior information for covariance localization in the ensemble Kalman filter for petroleum reservoir applications. Comput. Geosci., 15, 251-269, doi:10.1007/s10596-010-9198-y.
    • (2011) Comput. Geosci , vol.15 , pp. 251-269
    • Emerick, A.1    Reynolds, A.2
  • 18
    • 33750502680 scopus 로고    scopus 로고
    • Estimation of highdimensional prior and posterior covariance matrices in Kalman filter variants
    • Furrer, R., and T. Bengtsson, 2007: Estimation of highdimensional prior and posterior covariance matrices in Kalman filter variants. J. Multivar. Anal., 98, 227-255, doi:10.1016/j.jmva.2006.08.003.
    • (2007) J. Multivar. Anal , vol.98 , pp. 227-255
    • Furrer, R.1    Bengtsson, T.2
  • 19
    • 0033023511 scopus 로고    scopus 로고
    • Construction of correlation functions in two and three dimensions
    • Gaspari, G., and S. E. Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125, 723-757, doi:10.1002/qj.49712555417.
    • (1999) Quart. J. Roy. Meteor. Soc , vol.125 , pp. 723-757
    • Gaspari, G.1    Cohn, S.E.2
  • 20
    • 19944434306 scopus 로고    scopus 로고
    • The new GFDL Global Atmosphere and Land Model AM2-LM2: Evaluation with prescribed SST simulations
    • GFDL Global AtmosphericModel Development Team, 2004: The new GFDL Global Atmosphere and Land Model AM2-LM2: Evaluation with prescribed SST simulations. J. Climate, 17, 4641-4673, doi:10.1175/JCLI-3223.1.
    • (2004) J. Climate , vol.17 , pp. 4641-4673
  • 21
    • 79953216060 scopus 로고    scopus 로고
    • Balance and ensemble Kalman filter localization techniques
    • Greybush, S. J., E. Kalnay, T. Miyoshi, K. Ide, and B. R. Hunt, 2011: Balance and ensemble Kalman filter localization techniques. Mon. Wea. Rev., 139, 511-522, doi:10.1175/2010MWR3328.1.
    • (2011) Mon. Wea. Rev , vol.139 , pp. 511-522
    • Greybush, S.J.1    Kalnay, E.2    Miyoshi, T.3    Ide, K.4    Hunt, B.R.5
  • 22
    • 0035506430 scopus 로고    scopus 로고
    • Distancedependent filtering of background error covariance estimates in an ensemble Kalman filter
    • Hamill, T. M., J. S. Whitaker, and C. Snyder, 2001: Distancedependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129, 2776-2790, doi:10.1175/1520-0493(2001)129<2776:DDFOBE>2.0.CO;2.
    • (2001) Mon. Wea. Rev , vol.129 , pp. 2776-2790
    • Hamill, T.M.1    Whitaker, J.S.2    Snyder, C.3
  • 23
    • 0028669607 scopus 로고
    • A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models
    • Held, I. M., and M. J. Suarez, 1994: A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models. Bull. Amer. Meteor. Soc., 75, 1825-1830, doi:10.1175/1520-0477(1994)075<1825:APFTIO>2.0.CO;2.
    • (1994) Bull. Amer. Meteor. Soc , vol.75 , pp. 1825-1830
    • Held, I.M.1    Suarez, M.J.2
  • 24
    • 0032024819 scopus 로고    scopus 로고
    • Data assimilation using an ensemble Kalman filter technique
    • Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126, 796-811, doi:10.1175/1520-0493(1998)126<0796: DAUAEK>2.0.CO;2.
    • (1998) Mon. Wea. Rev , vol.126 , pp. 796-811
    • Houtekamer, P.L.1    Mitchell, H.L.2
  • 25
    • 84896777380 scopus 로고    scopus 로고
    • Higher resolution in an operational ensemble Kalman filter
    • Houtekamer, P. L., X. Deng, H. L. Mitchell, S.-J. Baek, and N. Gagnon, 2014: Higher resolution in an operational ensemble Kalman filter. Mon. Wea. Rev., 142, 1143-1162, doi:10.1175/MWR-D-13-00138.1.
    • (2014) Mon. Wea. Rev , vol.142 , pp. 1143-1162
    • Houtekamer, P.L.1    Deng, X.2    Mitchell, H.L.3    Baek, S.-J.4    Gagnon, N.5
  • 27
    • 70149088574 scopus 로고    scopus 로고
    • Covariance localisation and balance in an ensemble Kalman filter
    • Kepert, J. D., 2009: Covariance localisation and balance in an ensemble Kalman filter. Quart. J. Roy. Meteor. Soc., 135, 1157-1176, doi:10.1002/qj.443.
    • (2009) Quart. J. Roy. Meteor. Soc , vol.135 , pp. 1157-1176
    • Kepert, J.D.1
  • 28
    • 53249092256 scopus 로고    scopus 로고
    • Error covariance modeling in the GMAO ocean ensemble Kalman filter
    • Keppenne, C. L., M. M. Rienecker, J. P. Jacob, and R. Kovach, 2008: Error covariance modeling in the GMAO ocean ensemble Kalman filter. Mon. Wea. Rev., 136, 2964-2982, doi:10.1175/2007MWR2243.1.
    • (2008) Mon. Wea. Rev , vol.136 , pp. 2964-2982
    • Keppenne, C.L.1    Rienecker, M.M.2    Jacob, J.P.3    Kovach, R.4
  • 29
    • 84893859982 scopus 로고    scopus 로고
    • Comparisons of empirical localization techniques for serial ensemble Kalman filters in a simple atmospheric general circulation model
    • Lei, L., and J. L. Anderson, 2014a: Comparisons of empirical localization techniques for serial ensemble Kalman filters in a simple atmospheric general circulation model. Mon. Wea. Rev., 142, 739-754, doi:10.1175/MWR-D-13-00152.1.
    • (2014) Mon. Wea. Rev , vol.142 , pp. 739-754
    • Lei, L.1    Anderson, J.L.2
  • 30
    • 84899874533 scopus 로고    scopus 로고
    • Empirical localization of observations for serial ensemble Kalman filter data assimilation in an atmospheric general circulation model
    • Lei, L., and J. L. Anderson, 2014b: Empirical localization of observations for serial ensemble Kalman filter data assimilation in an atmospheric general circulation model. Mon. Wea. Rev., 142, 1835-1851, doi:10.1175/MWR-D-13-00288.1.
    • (2014) Mon. Wea. Rev , vol.142 , pp. 1835-1851
    • Lei, L.1    Anderson, J.L.2
  • 31
    • 66849124453 scopus 로고    scopus 로고
    • Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter
    • Li, H., E. Kalnay, and T. Miyoshi, 2009a: Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter. Quart. J. Roy. Meteor. Soc., 135, 523-533, doi:10.1002/qj.371.
    • (2009) Quart. J. Roy. Meteor. Soc , vol.135 , pp. 523-533
    • Li, H.1    Kalnay, E.2    Miyoshi, T.3
  • 32
    • 70449106810 scopus 로고    scopus 로고
    • Accounting for model errors in ensemble data assimilation
    • Li, H., E. Kalnay, and T. Miyoshi, and C. M. Danforth, 2009b: Accounting for model errors in ensemble data assimilation. Mon. Wea. Rev., 137, 3407-3419, doi:10.1175/2009MWR2766.1.
    • (2009) Mon. Wea. Rev , vol.137 , pp. 3407-3419
    • Li, H.1    Kalnay, E.2    Miyoshi, T.3    Danforth, C.M.4
  • 33
    • 0032004313 scopus 로고    scopus 로고
    • Optimal sites for supplementary weather observations: Simulation with a small model
    • Lorenz, E. N., and K. A. Emanuel, 1998: Optimal sites for supplementary weather observations: Simulation with a small model. J. Atmos. Sci., 55, 399-414, doi:10.1175/1520-0469(1998)055<0399:OSFSWO>2.0.CO;2.
    • (1998) J. Atmos. Sci , vol.55 , pp. 399-414
    • Lorenz, E.N.1    Emanuel, K.A.2
  • 34
    • 33847294302 scopus 로고    scopus 로고
    • Impacts of localisation in the EnKF and EnOI: Experiments with a small model
    • Oke, P. R., P. Sakov, and S. P. Corney, 2007: Impacts of localisation in the EnKF and EnOI: Experiments with a small model. Ocean Dyn., 57, 32-45, doi:10.1007/s10236-006-0088-8.
    • (2007) Ocean Dyn , vol.57 , pp. 32-45
    • Oke, P.R.1    Sakov, P.2    Corney, S.P.3
  • 35
    • 8844258829 scopus 로고    scopus 로고
    • A local ensemble Kalman filter for atmospheric data assimilation
    • Ott, E., and Coauthors, 2004: A local ensemble Kalman filter for atmospheric data assimilation. Tellus, 56A, 415-428, doi:10.1111/j.1600-0870.2004.00076.x.
    • (2004) Tellus , vol.56A , pp. 415-428
    • Ott, E.1
  • 36
    • 0036322061 scopus 로고    scopus 로고
    • Hydrologic data assimilation with the ensemble Kalman filter
    • Reichle, R. H., D. B. McLaughlin, and D. Entekhabi, 2002: Hydrologic data assimilation with the ensemble Kalman filter. Mon. Wea. Rev., 130, 103-114, doi:10.1175/1520-0493(2002)130<0103: HDAWTE>2.0.CO;2.
    • (2002) Mon. Wea. Rev , vol.130 , pp. 103-114
    • Reichle, R.H.1    McLaughlin, D.B.2    Entekhabi, D.3
  • 37
    • 84926471102 scopus 로고    scopus 로고
    • Assimilation of near-surface cosmic-ray neutrons improves summertime soil moisture profile estimates at three distinct biomes in the USA
    • Rosolem, R., T. Hoar, A. Arellano, J. L. Anderson, W. J. Shuttleworth, X. Zeng, and T. E. Franz, 2014: Assimilation of near-surface cosmic-ray neutrons improves summertime soil moisture profile estimates at three distinct biomes in the USA. Hydrol. Earth Syst. Sci. Discuss., 11, 5515-5558, doi:10.5194/hessd-11-5515-2014.
    • (2014) Hydrol. Earth Syst. Sci. Discuss , vol.11 , pp. 5515-5558
    • Rosolem, R.1    Hoar, T.2    Arellano, A.3    Anderson, J.L.4    Shuttleworth, W.J.5    Zeng, X.6    Franz, T.E.7
  • 38
    • 84870859794 scopus 로고    scopus 로고
    • Forecasting seasonal outbreaks of influenza
    • Shaman, J., and A. Karspeck, 2012: Forecasting seasonal outbreaks of influenza. Proc. Natl. Acad. Sci. USA, 109, 20 425-20 430, doi:10.1073/pnas.1208772109.
    • (2012) Proc. Natl. Acad. Sci. USA , vol.109 , pp. 20425-20430
    • Shaman, J.1    Karspeck, A.2
  • 40
    • 84867956219 scopus 로고    scopus 로고
    • Evaluating methods to account for system errors in ensemble data assimilation
    • Whitaker, J. S., and T. M. Hamill, 2012: Evaluating methods to account for system errors in ensemble data assimilation. Mon. Wea. Rev., 140, 3078-3089, doi:10.1175/MWR-D-11-00276.1.
    • (2012) Mon. Wea. Rev , vol.140 , pp. 3078-3089
    • Whitaker, J.S.1    Hamill, T.M.2
  • 41
    • 44449095043 scopus 로고    scopus 로고
    • Ensemble data assimilation with the NCEP Global Forecast System
    • Whitaker, J. S., and T. M. Hamill, X. Wei, Y. Song, and Z. Toth, 2008: Ensemble data assimilation with the NCEP Global Forecast System. Mon. Wea. Rev., 136, 463-482, doi:10.1175/2007MWR2018.1.
    • (2008) Mon. Wea. Rev , vol.136 , pp. 463-482
    • Whitaker, J.S.1    Hamill, T.M.2    Wei, X.3    Song, Y.4    Toth, Z.5
  • 42
    • 2442717392 scopus 로고    scopus 로고
    • Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter
    • Zhang, F., C. Snyder, and J. Sun, 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132, 1238-1253, doi:10.1175/1520-0493(2004)132<1238: IOIEAO>2.0.CO;2.
    • (2004) Mon. Wea. Rev , vol.132 , pp. 1238-1253
    • Zhang, F.1    Snyder, C.2    Sun, J.3
  • 43
    • 77952885727 scopus 로고    scopus 로고
    • Improving the ensemble estimate of the Kalman gain by bootstrap sampling
    • Zhang, Y., and D. S. Oliver, 2010: Improving the ensemble estimate of the Kalman gain by bootstrap sampling. Math. Geosci., 42, 327-345, doi:10.1007/s11004-010-9267-8.
    • (2010) Math. Geosci , vol.42 , pp. 327-345
    • Zhang, Y.1    Oliver, D.S.2
  • 44
    • 84888409714 scopus 로고    scopus 로고
    • A regional GSI-based ensemble Kalman filter data assimilation system for the rapid refresh configuration: Testing at reduced resolution
    • Zhu, K., Y. Pan, M. Xue, X. Wang, J. S. Whitaker, S. G. Benjamin, S. S. Weygandt, and M. Hu, 2013: A regional GSI-based ensemble Kalman filter data assimilation system for the rapid refresh configuration: Testing at reduced resolution. Mon. Wea. Rev., 141, 4118-4139, doi:10.1175/MWR-D-13-00039.1.
    • (2013) Mon. Wea. Rev , vol.141 , pp. 4118-4139
    • Zhu, K.1    Pan, Y.2    Xue, M.3    Wang, X.4    Whitaker, J.S.5    Benjamin, S.G.6    Weygandt, S.S.7    Hu, M.8


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