Editorial Type:
Article
Article Type:
Research Article

Application of Coupled Bred Vectors to Seasonal-to-Interannual Forecasting and Ocean Data Assimilation

Shu-Chih Yang Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, and Earth System Science Interdisciplinary Center, and Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland

Search for other papers by Shu-Chih Yang in
Current site
Google Scholar
PubMed Close
,
Christian Keppenne Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, and Science Applications International Corporation, Greenbelt, Maryland

Search for other papers by Christian Keppenne in
Current site
Google Scholar
PubMed Close
,
Michele Rienecker Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

Search for other papers by Michele Rienecker in
Current site
Google Scholar
PubMed Close
, and
Eugenia Kalnay Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland

Search for other papers by Eugenia Kalnay in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jun 2009
DOI:
https://doi.org/10.1175/2008JCLI2427.1
Page(s):
2850–2870
Restricted access

Abstract

Coupled bred vectors (BVs) generated from the NASA Global Modeling and Assimilation Office (GMAO) coupled general circulation model are designed to capture the uncertainties related to slowly varying coupled instabilities. Two applications of the BVs are investigated in this study.

First, the coupled BVs are used as initial perturbations for ensemble-forecasting purposes. Results show that the seasonal-to-interannual variability forecast skill can be improved when the oceanic and atmospheric perturbations are initialized with coupled BVs. The impact is particularly significant when the forecasts are initialized from the cold phase of tropical Pacific SST (e.g., August and November), because at these times the early coupled model errors, not accounted for in the BVs, are small.

Second, the structure of the BVs is applied to construct hybrid background error covariances carrying flow-dependent information for the ocean data assimilation. Results show that the accuracy of the ocean analyses is improved when Gaussian background covariances are supplemented with a term obtained from the BVs. The improvement is especially noticeable for the salinity field.

Corresponding author address: Shu-Chih Yang, Department of Atmospheric Sciences, National Central University, Jhongli City 32001, Taiwan. Email: shuchih.yang@atm.ncu.edu.tw

Abstract

Coupled bred vectors (BVs) generated from the NASA Global Modeling and Assimilation Office (GMAO) coupled general circulation model are designed to capture the uncertainties related to slowly varying coupled instabilities. Two applications of the BVs are investigated in this study.

First, the coupled BVs are used as initial perturbations for ensemble-forecasting purposes. Results show that the seasonal-to-interannual variability forecast skill can be improved when the oceanic and atmospheric perturbations are initialized with coupled BVs. The impact is particularly significant when the forecasts are initialized from the cold phase of tropical Pacific SST (e.g., August and November), because at these times the early coupled model errors, not accounted for in the BVs, are small.

Second, the structure of the BVs is applied to construct hybrid background error covariances carrying flow-dependent information for the ocean data assimilation. Results show that the accuracy of the ocean analyses is improved when Gaussian background covariances are supplemented with a term obtained from the BVs. The improvement is especially noticeable for the salinity field.

Corresponding author address: Shu-Chih Yang, Department of Atmospheric Sciences, National Central University, Jhongli City 32001, Taiwan. Email: shuchih.yang@atm.ncu.edu.tw

Save
Cover Journal of Climate
Journal of Climate

  • Bacmeister, J., P. J. Pegion, S. D. Schubert, and M. J. Suarez, 2000: An atlas of seasonal means simulated by the NSIPP 1 atmospheric GCM. NASA Tech. Memo. 104606, Vol. 17, Goddard Space Flight Center, Greenbelt, MD, 194 pp.

    • Search Google Scholar
    • Export Citation

  • Beck, A., and M. Ehrendorfer, 2005: Singular-vector-based covariance propagation in a quasigeostrophic assimilation system. Mon. Wea. Rev., 133 , 1295–1310.

    • Search Google Scholar
    • Export Citation

  • Behringer, D. W., M. Ji, and A. Leetmaa, 1998: An improved coupled model for ENSO prediction and implications for ocean initialization. Part I: The ocean data assimilation system. Mon. Wea. Rev., 126 , 1013–1021.

    • Search Google Scholar
    • Export Citation

  • Borovikov, A., M. M. Rienecker, C. L. Keppenne, and G. C. Johnson, 2005: Multivariate error covariance estimates by Monte Carlo simulation for assimilation studies in the Pacific Ocean. Mon. Wea. Rev., 133 , 2310–2334.

    • Search Google Scholar
    • Export Citation

  • Boulanger, J-P., and C. Menkes, 1995: Propagation and reflection of long equatorial waves in the Pacific Ocean during 1991–1993 El Niño. J. Geophys. Res., 100 , 25041–25059.

    • Search Google Scholar
    • Export Citation

  • Cai, M., E. Kalnay, and Z. Toth, 2003: Bred vectors of the Zebiak–Cane model and their application to ENSO predictions. J. Climate, 16 , 40–55.

    • Search Google Scholar
    • Export Citation

  • Corazza, M., E. Kalnay, D. J. Patil, E. Ott, J. A. Yorke, B. R. Hunt, I. Szunyogh, and M. Cai, 2002: Use of the breeding technique in the estimation of the background covariance matrix for a quasi-geostrophic model. Preprints, Symp. on Observations, Data Assimilation, and Probabilistic Prediction, Orlando, FL, Amer. Meteor. Soc., 154–157.

    • Search Google Scholar
    • Export Citation

  • Etherton, B. J., and C. H. Bishop, 2004: Resilience of hybrid ensemble/3DVAR analysis schemes to model error and ensemble covariance error. Mon. Wea. Rev., 132 , 1065–1080.

    • Search Google Scholar
    • Export Citation

  • Gaspari, G., and S. E. Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125 , 723–757.

    • Search Google Scholar
    • Export Citation

  • Goddard, L., and S. G. Philander, 2000: The energetics of El Niño and La Niña. J. Climate, 13 , 1496–1516.

  • Hamill, T. M., and C. Snyder, 2000: A hybrid ensemble Kalman filter–3D variational analysis scheme. Mon. Wea. Rev, 128 , 2905–2919.

  • Houtekamer, P., and H. Mitchell, 2001: A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev., 129 , 123–137.

    • Search Google Scholar
    • Export Citation

  • Keppenne, C. L., and M. M. Rienecker, 2003: Assimilation of temperature into an isopycnal ocean general circulation model using a parallel ensemble Kalman filter. J. Mar. Syst., 40–41 , 363–380.

    • Search Google Scholar
    • Export Citation

  • 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.

    • Search Google Scholar
    • Export Citation

  • Kessler, W. S., 1999: Interannual variability of the subsurface high salinity tongue south of the equator at 165°E. J. Phys. Oceanogr., 29 , 2038–2049.

    • Search Google Scholar
    • Export Citation

  • Koster, R., and M. Suarez, 1992: Modeling the land surface boundary in climate models as a composite of independent vegetation stands. J. Geophys. Res., 97 , 2697–2715.

    • Search Google Scholar
    • Export Citation

  • Murtugudde, R., and A. Busalacchi, 1998: Salinity effects in a tropical ocean model. J. Geophys. Res., 103 , 3283–3300.

  • Peña, M., and E. Kalnay, 2004: Separating fast and slow modes in coupled chaotic systems. Nonlinear Processes Geophys., 11 , 319–327.

  • Perigaud, C., J. P. McCreary Jr., and K. Q. Zhang, 2003: Impact of interannual rainfall anomalies on Indian Ocean salinity and temperature variability. J. Geophys. Res., 108 , 3319. doi:10.1029/2002JC001699.

    • Search Google Scholar
    • Export Citation

  • Schopf, P., and A. Loughe, 1995: A reduced-gravity isopycnal ocean model: Hindcasts of El Niño. Mon. Wea. Rev., 123 , 2839–2863.

  • Sun, C., M. M. Rienecker, A. Rosati, M. Harrison, A. Wittenberg, C. L. Keppenne, J. P. Jacob, and R. M. Kovach, 2007: Comparison and sensitivity of ODASI ocean analyses in the tropical Pacific. Mon. Wea. Rev., 135 , 2242–2264.

    • Search Google Scholar
    • Export Citation

  • Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of perturbations. Bull. Amer. Meteor. Soc., 74 , 2317–2330.

  • Toth, Z., and E. Kalnay, 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev., 125 , 3297–3319.

  • Vintzileos, A., M. M. Rienecker, M. J. Suarez, S. K. Miller, P. J. Pegion, and J. T. Bacmeister, 2003: Simulation of the El Niño–Southern Oscillation phenomenon with NASA’s Seasonal-to-Interannual Prediction Project coupled general circulation model. CLIVAR Exchanges, No. 28, International CLIVAR Project Office, Silver Spring, MD, 25–27.

    • Search Google Scholar
    • Export Citation

  • Wang, X., T. M. Hamill, J. S. Whitaker, and C. H. Bishop, 2007a: A comparison of hybrid ensemble transform Kalman filter–optimum interpolation and ensemble square root filter analysis schemes. Mon. Wea. Rev., 135 , 1055–1076.

    • Search Google Scholar
    • Export Citation

  • Wang, X., C. Snyder, and T. M. Hamill, 2007b: On the theoretical equivalence of differently proposed ensemble–3DVAR hybrid analysis schemes. Mon. Wea. Rev., 135 , 222–227.

    • Search Google Scholar
    • Export Citation

  • Weaver, A. T., J. Vialard, and D. L. T. Anderson, 2003: Three- and four-dimensional variational assimilation with an ocean general circulation model of the tropical Pacific Ocean. Part I: Formulation, internal diagnostics, and consistency checks. Mon. Wea. Rev., 131 , 1360–1378.

    • Search Google Scholar
    • Export Citation

  • Weaver, A. T., C. Deltel, E. Machu, S. Ricci, and N. Daget, 2005: A multivariate balance operator for variational ocean data assimilation. Quart. J. Roy. Meteor. Soc., 131 , 3605–3625.

    • Search Google Scholar
    • Export Citation

  • Yang, S., K-M. Lau, and P. S. Schopf, 1999: Sensitivity of the tropical Pacific Ocean to precipitation-induced freshwater flux. Climate Dyn., 15 , 737–750.

    • Search Google Scholar
    • Export Citation

  • Yang, S-C., M. Cai, E. Kalnay, M. Rienecker, G. Yuan, and Z. Toth, 2006a: ENSO bred vectors in coupled ocean–atmosphere general circulation models. J. Climate, 19 , 1422–1436.

    • Search Google Scholar
    • Export Citation

  • Yang, S-C., M. Corazza, A. Carrassi, E. Kalnay, and T. Miyoshi, 2006b: Comparison of ensemble-based and variational-based data assimilation schemes in a quasi-geostrophic model. Proc. 10th Symp. on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface, Atlanta, GA, Amer. Meteor. Soc., 6.3a. [Available online at http://ams.confex.com/ams/pdfpapers/101581.pdf].

    • Search Google Scholar
    • Export Citation

  • Yang, S-C., E. Kalnay, M. Cai, and M. M. Rienecker, 2008: Bred vectors and forecast errors in the NASA coupled general circulation model. Mon. Wea. Rev., 136 , 1305–1326.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 216 70 4
PDF Downloads 77 26 1