• AchutaRao, K., , and K. R. Sperber, 2006: ENSO simulation in coupled ocean–atmosphere models: Are the current models better? Climate Dyn., 27, 115.

    • Search Google Scholar
    • Export Citation
  • Adler, R. A., and Coauthors, 2003: The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167.

    • Search Google Scholar
    • Export Citation
  • Alavi, N., , G. Drewitt, , A. A. Berg, , and W. J. Merryfield, 2011: Soil moisture initialization effects in the CCCMA GCM3: Relationship of seasonal climate forecast error to uncertainty in soil moisture initializations. Atmos.–Ocean, 49, 179188.

    • Search Google Scholar
    • Export Citation
  • Balmaseda, M. A., , and D. Anderson, 2009: Impact of initialization strategies and observations on seasonal forecast skill. Geophys. Res. Lett., 36, L01701, doi:10.1029/2008GL035561.

    • Search Google Scholar
    • Export Citation
  • Balmaseda, M. A., , G. C. Smith, , K. Haines, , D. Anderson, , T. N. Palmer, , and A. Vidard, 2007: Historical reconstruction of the Atlantic meridional overturning circulation from the ECMWF operational ocean reanalysis. Geophys. Res. Lett., 34, L23615, doi:10.1029/2007GL031645.

    • Search Google Scholar
    • Export Citation
  • Balmaseda, M. A., , L. Ferranti, , F. Molteni, , and T. N. Palmer, 2010: Impact of 2007 and 2008 Arctic ice anomalies on the atmospheric circulation: Implications for long-range predictions. Quart. J. Roy. Meteor. Soc., 136, 16551664.

    • Search Google Scholar
    • Export Citation
  • Barker, H. W., , J. N. S. Cole, , J.-J. Morcrette, , R. Pincus, , P. Raisanen, , K. von Salzen, , and P. A. Vaillancourt, 2008: The Monte Carlo independent column approximation: An assessment using several global atmospheric models. Quart. J. Roy. Meteor. Soc., 134, 14631478.

    • 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, 10131021.

    • Search Google Scholar
    • Export Citation
  • Bloom, S. C., , L. L. Takacs, , A. M. da Silva, , and D. Ledvina, 1996: Data assimilation using incremental analysis updates. Mon. Wea. Rev., 124, 12561271.

    • Search Google Scholar
    • Export Citation
  • Bond, N. A., , and G. A. Vecchi, 2003: The influence of the Madden–Julian oscillation on precipitation in Oregon and Washington. Wea. Forecasting, 18, 600613.

    • Search Google Scholar
    • Export Citation
  • Brodeau, L., , B. Barnier, , A.-M. Treguier, , T. Penduff, , and S. Gulev, 2010: An ERA40-based atmospheric forcing for global ocean circulation models. Ocean Modell., 31, 88104.

    • Search Google Scholar
    • Export Citation
  • Burgers, G., , and D. B. Stephenson, 1999: The “normality” of El Niño. Geophys. Res. Lett., 26, 10271030.

  • Carton, J. A., , and B. S. Giese, 2008: A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA). Mon. Wea. Rev., 136, 29993017.

    • Search Google Scholar
    • Export Citation
  • Carton, J. A., , G. Chepurin, , X. Cao, , and B. Giese, 2000a: A Simple Ocean Data Assimilation analysis of the global upper ocean 1950–1995. Part I: Methodology. J. Phys. Oceanogr., 30, 294309.

    • Search Google Scholar
    • Export Citation
  • Carton, J. A., , G. Chepurin, , and X. Cao, 2000b: A Simple Ocean Data Assimilation analysis of the global upper ocean 1950–1995. Part II: Results. J. Phys. Oceanogr., 30, 311326.

    • Search Google Scholar
    • Export Citation
  • Chang, Y.-S., , S. Zhang, , A. Rosati, , T. L. Delworth, , and W. F. Stern, 2012: An assessment of oceanic variability for 1960–2010 from the GFDL ensemble coupled data assimilation. Climate Dyn., 40, 775803, doi:10.1007/s00382-012-1412-2.

    • Search Google Scholar
    • Export Citation
  • Croft, B., , U. Lohmann, , and K. von Salzen, 2005: Black carbon ageing in the Canadian Centre for Climate Modelling and Analysis atmospheric general circulation model. Atmos. Chem. Phys., 5, 19311949.

    • Search Google Scholar
    • Export Citation
  • Cunningham, S. A., , S. G. Alderson, , B. A. King, , and M. A. Brandon, 2003: Transport and variability of the Antarctic circumpolar current in Drake Passage. J. Geophys. Res., 108, 8084, doi:10.1029/2001JC001147.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim Reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597.

    • Search Google Scholar
    • Export Citation
  • DelSole, T., , and X. Yang, 2011: Field significance of regression patterns. J. Climate, 24, 50945107.

  • Derber, J. D., , and A. Rosati, 1989: A global oceanic data assimilation system. J. Phys. Oceanogr., 19, 13331347.

  • Derome, J., and Coauthors, 2001: Seasonal predictions based on two dynamical models. Atmos.–Ocean, 39, 485501.

  • de Szoeke, S. P., , C. W. Fairall, , D. E. Wolfe, , L. Bariteau, , and P. Zuidema, 2010: Surface flux observations on the southeastern tropical Pacific Ocean and attribution of SST errors in coupled ocean–atmosphere models. J. Climate, 23, 41524174.

    • Search Google Scholar
    • Export Citation
  • Doblas-Reyes, F. J., , R. Hagedorn, , T. N. Palmer, , and J.-J. Morcrette, 2006: Impact of increasing greenhouse gas concentrations in seasonal ensemble forecasts. Geophys. Res. Lett., 33, L07708, doi:10.1029/2005GL025061.

    • Search Google Scholar
    • Export Citation
  • Doblas-Reyes, F. J., and Coauthors, 2009: Addressing model uncertainty in seasonal and annual dynamical seasonal forecasts. Quart. J. Roy. Meteor. Soc., 135, 15381559.

    • Search Google Scholar
    • Export Citation
  • Donald, A., and Coauthors, 2006: Near-global impact of the Madden–Julian oscillation on rainfall. Geophys. Res. Lett., 33, L09704, doi:10.1029/2005GL025155.

    • Search Google Scholar
    • Export Citation
  • Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Climate, 24, 34843519.

    • Search Google Scholar
    • Export Citation
  • Dunstone, N. J., , and D. M. Smith, 2010: Impact of atmosphere and sub-surface ocean data on decadal climate prediction. Geophys. Res. Lett., 37, L02709, doi:10.1029/2009GL041609.

    • Search Google Scholar
    • Export Citation
  • Fedorov, A. V., , and S. G. Philander, 2001: A stability analysis of tropical ocean–atmosphere interactions: Bridging measurements and theory for El Niño. J. Climate, 14, 30863101.

    • Search Google Scholar
    • Export Citation
  • Flato, G. M., , and W. D. I. Hibler, 1992: Modelling pack ice as a cavitating fluid. J. Phys. Oceanogr., 22, 626651.

  • Fu, X., , and B. Wang, 2001: A coupled modeling study of the seasonal cycle of the Pacific cold tongue. Part I: Simulation and sensitivity experiments. J. Climate, 14, 765779.

    • Search Google Scholar
    • Export Citation
  • Fyfe, J. C., , N. P. Gillett, , and D. W. J. Thompson, 2010: Comparing variability and trends in observed and modelled global-mean surface temperature. Geophys. Res. Lett., 37, L16802, doi:10.1029/2010GL044255.

    • Search Google Scholar
    • Export Citation
  • Fyfe, J. C., , W. J. Merryfield, , V. Kharin, , G. J. Boer, , W.-S. Lee, , and K. von Salzen, 2011: Skillful predictions of decadal trends in global mean surface temperature. Geophys. Res. Lett., 38, L22801, doi:10.1029/2011GL049508.

    • Search Google Scholar
    • Export Citation
  • Ganachaud, A., 2003: Large-scale mass transports, water mass formation, and diffusivities estimated from World Ocean Circulation Experiment (WOCE) hydrographic data. J. Geophys. Res., 108, 3213, doi:10.1029/2002JC001565.

    • Search Google Scholar
    • Export Citation
  • Gent, P. R., , J. Willebrand, , T. J. McDougall, , and J. C. McWilliams, 1995: Parameterizing eddy-induced tracer transports in ocean circulation models. J. Phys. Oceanogr., 25, 463474.

    • Search Google Scholar
    • Export Citation
  • Goddard, L., , and S. Mason, 2002: Sensitivity of seasonal climate forecasts to persisted SST anomalies. Climate Dyn., 19, 619631.

  • Goddard, L., and Coauthors, 2012: A verification framework for interannual-to-decadal predictions experiments. Climate Dyn., 40, 245272, doi:10.1007/s00382-012-1481-2.

    • Search Google Scholar
    • Export Citation
  • Griffies, S. M., and Coauthors, 2011: The GFDL CM3 coupled climate model: Characteristics of the ocean and sea ice simulations. J. Climate, 24, 35203544.

    • Search Google Scholar
    • Export Citation
  • Guilyardi, E., 2006: El Niño–mean state–seasonal cycle interactions in a multi-model ensemble. Climate Dyn., 26, 329348.

  • Guilyardi, E., , A. Wittenberg, , A. Fedorov, , M. Collins, , C. Wang, , A. Capotondi, , and G. van Oldenborgh, 2009: Understanding El Niño in ocean–atmosphere general circulation models: Progress and challenges. Bull. Amer. Meteor. Soc., 90, 325340.

    • Search Google Scholar
    • Export Citation
  • Guo, Z., , P. A. Dirmeyer, , and T. DelSole, 2011: Land surface impacts on subseasonal and seasonal predictability. Geophys. Res. Lett., 38, L24812, doi:10.1029/2011GL049945.

    • Search Google Scholar
    • Export Citation
  • Hansen, J. R., , R. Ruedy, , M. Sato, , and K. Lo, 2010: Global surface temperature change. Rev. Geophys., 48, RG4004, doi:10.1029/2010RG000345.

    • Search Google Scholar
    • Export Citation
  • Hazeleger, W., and Coauthors, 2011: EC-Earth V2.2: Description and validation of a new seamless earth system prediction model. Climate Dyn., 39, 26112629, doi:10.1007/s00382-011-1228-5.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J. W., , J. Hack, , D. Shea, , J. Caron, , and J. Rosinski, 2008: A new sea surface temperature and sea ice boundary dataset for the Community Atmosphere Model. J. Climate, 21, 51455153.

    • Search Google Scholar
    • Export Citation
  • Johns, W. E., and Coauthors, 2011: Continuous, array-based estimates of Atlantic Ocean heat transport at 26.5°N. J. Climate, 24, 24292449.

    • Search Google Scholar
    • Export Citation
  • Johnson, G. C., , M. J. McPhaden, , and E. Firing, 2001: Equatorial Pacific Ocean horizontal velocity, divergence, and upwelling. J. Phys. Oceanogr., 31, 839849.

    • Search Google Scholar
    • Export Citation
  • Jones, C., 2000: Occurrence of extreme precipitation events in California and relationships with the Madden–Julian oscillation. J. Climate, 13, 35763587.

    • Search Google Scholar
    • Export Citation
  • Joseph, R., , and S. Nigam, 2006: ENSO evolution and teleconnections in IPCC's twentieth-century climate simulations: Realistic representation? J. Climate, 19, 43604377.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471.

  • Kanamitsu, M., , W. Ebisuzaki, , J. Woolen, , S.-K. Yang, , J. J. Hnilo, , M. Fiorino, , and G. L. Potter, 2002: NCEP-DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311643.

    • Search Google Scholar
    • Export Citation
  • Kara, A. B., , P. A. Rochford, , and H. E. Hurlburt, 2000: An optimal definition for ocean mixed layer depth. J. Geophys. Res., 105, 16 80316 821.

    • Search Google Scholar
    • Export Citation
  • Keeley, S. P. E., , R. T. Sutton, , and L. C. Shaffrey, 2012: The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate. Quart. J. Roy. Meteor. Soc., 138, 17741783, doi:10.1002/qj.1912.

    • Search Google Scholar
    • Export Citation
  • Keenlyside, N. S., , M. Latif, , M. Botzet, , J. Jungclaus, , and U. Schulzweida, 2005: A coupled method for initializing El Niño Southern Oscillation forecasts using sea surface temperature. Tellus, 57A, 340356.

    • Search Google Scholar
    • Export Citation
  • Khairoutdinov, M., , and Y. Kogan, 2000: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus. Mon. Wea. Rev., 128, 229243.

    • Search Google Scholar
    • Export Citation
  • Kharin, V. V., , and J. F. Scinocca, 2012: The impact of model fidelity on seasonal predictive skill. Geophys. Res. Lett., 39, L18803, doi:10.1029/2012GL052815.

    • Search Google Scholar
    • Export Citation
  • Kharin, V. V., , F. W. Zwiers, , Q. Teng, , G. J. Boer, , J. Derome, , and J. S. Fontecilla, 2009: Skill assessment of seasonal hindcasts from the Canadian Historical Forecast Project. Atmos.–Ocean, 47, 204223.

    • Search Google Scholar
    • Export Citation
  • Kharin, V. V., , G. J. Boer, , W. J. Merryfield, , J. F. Scinocca, , and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate. Geophys. Res. Lett., 39, L19705, doi:10.1029/2012GL052647.

    • Search Google Scholar
    • Export Citation
  • Kim, D., and Coauthors, 2009: Application of MJO simulation diagnostics to climate models. J. Climate, 22, 64136436.

  • Kim, H.-M., , P. J. Webster, , and J. A. Curry, 2012: Evaluation of short-term climate change prediction in multi-model CMIP5 decadal hindcasts. Geophys. Res. Lett., 39, L10701, doi:10.1029/2012GL051644.

    • Search Google Scholar
    • Export Citation
  • Kirtman, B. P., , and D. Min, 2009: Multimodel ensemble ENSO prediction with CCSM and CFS. Mon. Wea. Rev., 137, 29082930.

  • Koster, R., and Coauthors, 2011: The second phase of the Global Land–Atmosphere Coupling Experiment: Soil moisture contributions to subseasonal forecast skill. J. Hydrometeor., 12, 805822.

    • Search Google Scholar
    • Export Citation
  • Kug, J.-S., , Y.-G. Ham, , M. Kimoto, , F.-F. Jin, , and I.-S. Kang, 2010: New approach for optimal perturbation method in ensemble climate prediction with empirical singular vector. Climate Dyn., 35, 331340.

    • Search Google Scholar
    • Export Citation
  • Landrum, L., , M. M. Holland, , D. Schneider, , and E. Hunke, 2012: Antarctic sea ice climatology, variability, and late twentieth-century change in CCSM4. J. Climate, 25, 48174838.

    • Search Google Scholar
    • Export Citation
  • Large, W. G., , J. C. Williams, , and S. C. Doney, 1994: Oceanic vertical mixing: A review and a model with a nonlocal boundary layer parameterization. Rev. Geophys., 32, 363403.

    • Search Google Scholar
    • Export Citation
  • Large, W. G., , G. Danabasoglu, , J. C. McWilliams, , P. R. Gent, , and F. O. Bryan, 2001: Equatorial circulation of a global ocean climate model with anisotropic horizontal viscosity. J. Phys. Oceanogr., 31, 518536.

    • Search Google Scholar
    • Export Citation
  • Li, J., , and H. W. Barker, 2005: A radiation algorithm with correlated k-distribution. Part I: Local thermal equilibrium. J. Atmos. Sci., 62, 286309.

    • Search Google Scholar
    • Export Citation
  • Lienert, F., , J. C. Fyfe, , and W. J. Merryfield, 2011: Do climate models capture the tropical influences on North Pacific sea surface temperature variability? J. Climate, 24, 62036209.

    • Search Google Scholar
    • Export Citation
  • Lin, H., , and G. Brunet, 2009: The influence of the Madden–Julian oscillation on Canadian wintertime surface air temperature. Mon. Wea. Rev., 137, 22502262.

    • Search Google Scholar
    • Export Citation
  • Lin, H., , G. Brunet, , and J. Derome, 2009: An observed connection between the North Atlantic oscillation and the Madden–Julian oscillation. J. Climate, 22, 364380.

    • Search Google Scholar
    • Export Citation
  • Lin, H., , G. Brunet, , and R. Mo, 2010: Impact of the Madden–Julian oscillation on wintertime precipitation in Canada. Mon. Wea. Rev., 138, 38223839.

    • Search Google Scholar
    • Export Citation
  • Lin, J.-L., 2007: The double-ITCZ problem in IPCC AR4 coupled GCMs: Ocean–atmosphere feedback analysis. J. Climate, 20, 44974525.

  • Lin, J.-L., and Coauthors, 2006: Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: Convective signals. J. Climate, 19, 26652690.

    • Search Google Scholar
    • Export Citation
  • Liniger, M. A., , H. Mathis, , C. Appenzeller, , and F. J. Doblas-Reyes, 2007: Realistic greenhouse gas forcing and seasonal forecasts. Geophys. Res. Lett., 34, L02402, doi:10.1029/2006GL028335.

    • Search Google Scholar
    • Export Citation
  • Livezey, R. E., 1990: Variability of skill of long-range forecasts and implications for their use and value. Bull. Amer. Meteor. Soc., 71, 300309.

    • Search Google Scholar
    • Export Citation
  • Lohmann, U. K., , and E. Roeckner, 1996: Design and performance of a new cloud microphysics scheme developed for the ECHAM general circulation model. Climate Dyn., 12, 557572.

    • Search Google Scholar
    • Export Citation
  • Lohmann, U. K., , K. von Salzen, , N. McFarlane, , H. G. Leighton, , and J. Feichter, 1999: Tropospheric sulfur cycle in the Canadian general circulation model. J. Geophys. Res., 104, 26 83326 858.

    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., , S. Masson, , S. Behera, , S. Shingu, , and T. Yamagata, 2005: Seasonal climate predictability in a coupled OAGCM using a different approach for ensemble forecasts. J. Climate, 18, 44744497.

    • Search Google Scholar
    • Export Citation
  • Ma, X., , K. von Salzen, , and J. Cole, 2010: Constraints on interactions between aerosols and clouds on a global scale from a combination of MODIS-CERES satellite data and climate simulations. Atmos. Chem. Phys., 10, 98519861.

    • Search Google Scholar
    • Export Citation
  • Matthews, A. J., , B. J. Hoskins, , and M. Masutani, 2004: The global response to tropical heating in the Madden–Julian oscillation during northern winter. Quart. J. Roy. Meteor. Soc., 130, 19912011.

    • Search Google Scholar
    • Export Citation
  • McFarlane, N. A., , J. F. Scinocca, , M. Lazare, , R. Harvey, , D. Verseghy, , and J. Li, 2005: The CCCma third generation atmospheric general circulation model. CCCma Internal Rep., 25 pp.

  • Merryfield, W. J., 2006: Changes to ENSO under CO2 doubling in a multi-model ensemble. J. Climate, 19, 40094027.

  • Merryfield, W. J., , W.-S. Lee, , G. J. Boer, , V. V. Kharin, , B. Pal, , J. F. Scinocca, , and G. M. Flato, 2010: The first Coupled Historical Forecasting Project (CHFP1). Atmos.–Ocean, 48, 263283.

    • Search Google Scholar
    • Export Citation
  • Mo, K. C., , and R. W. Higgins, 1998: Tropical convection and precipitation regimes in the western United States. J. Climate, 11, 24042423.

    • Search Google Scholar
    • Export Citation
  • Monahan, A. H., , and A. Dai, 2004: The spatial and temporal structure of ENSO nonlinearity. J. Climate, 17, 30263036.

  • Namias, J., 1964: A 5-yr experiment in the preparation of seasonal outlooks. Mon. Wea. Rev., 92, 449464.

  • Namias, J., 1968: Long range weather forecasting—History, current status and outlook. Bull. Amer. Meteor. Soc., 49, 438470.

  • Palmer, T. N., 1999: Predicting uncertainty in forecasts of weather and climate. ECMWF Tech. Rep. 294, 51 pp. [Available online at http://www.ecmwf.int/newsevents/training/rcourse_notes/pdf_files/Uncertainty_prediction.pdf.]

  • Paolino, R. H., and Coauthors, 2010: The next generation of scenarios for climate change research and assessment. Nature, 463, 747756.

    • Search Google Scholar
    • Export Citation
  • Pohlmann, H., , D. M. Smith, , M. A. Balmaseda, , N. S. Keenlyside, , S. Masina, , D. Matei, , W. A. Müller, , and P. Rogel, 2013: Predictability of the mid-latitude Atlantic meridional overturning circulation in a multi-model system. Climate Dyn., doi:10.1007/s00382-013-1663-6, in press.

    • Search Google Scholar
    • Export Citation
  • Polavarapu, S., , S. Ren, , A. M. Clayton, , D. Sankey, , and Y. Rochon, 2004: On the relationship between incremental analysis updating and incremental digital filtering. Mon. Wea. Rev., 132, 24952502.

    • Search Google Scholar
    • Export Citation
  • Polavarapu, S., , T. G. Shepherd, , Y. Rochon, , and S. Ren, 2005: Some challenges of middle atmosphere data assimilation. Quart. J. Roy. Meteor. Soc., 131, 35133527.

    • Search Google Scholar
    • Export Citation
  • Randall, D. A., and Coauthors, 2007: Climate models and their evaluation. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 589–662.

  • Rayner, D., and Coauthors, 2011: Monitoring the Atlantic meridional overturning circulation. Deep-Sea Res., 58, 17441753.

  • Rayner, N. A., , D. E. Parker, , E. B. Horton, , C. K. Folland, , L. V. Alexander, , D. P. Rowell, , E. C. Kent, , and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.

    • Search Google Scholar
    • Export Citation
  • Reichler, T., , and J. Kim, 2008: How well do coupled models simulate today's climate? Bull. Amer. Meteor. Soc., 89, 303311.

  • Ren, X., , X.-Q. Yang, , B. Han, , and G.-Y. Xu, 2007: North Pacific storm track variations in winter season and the coupled pattern with the mid-latitude atmosphere–ocean system. Chin. J. Geophys., 50, 94103.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., , N. A. Rayner, , T. M. Smith, , D. C. Stokes, , and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625.

    • Search Google Scholar
    • Export Citation
  • Roach, A. T., , K. Aagaard, , C. H. Pease, , S. A. Salo, , T. Weingartner, , V. Pavlov, , and M. Kulakov, 1995: Direct measurements of transport and water properties through the Bering Strait. J. Geophys. Res., 100, 18 44318 457.

    • Search Google Scholar
    • Export Citation
  • Ropelewski, C. F., , and M. S. Halpert, 1986: North American precipitation and temperature patterns associated with the El Niño/Southern Oscillation (ENSO). Mon. Wea. Rev., 114, 23522362.

    • Search Google Scholar
    • Export Citation
  • Ropelewski, C. F., , and M. S. Halpert, 1987: Global and regional scale precipitation patterns associated with the El Niño/Southern Oscillation. Mon. Wea. Rev., 115, 16061626.

    • Search Google Scholar
    • Export Citation
  • Rotstayn, L. D., 1997: A physically based scheme for the treatment of stratiform clouds and precipitation in large-scale models. I: Description and evaluation of the microphysical processes. Quart. J. Roy. Meteor. Soc., 123, 12271282.

    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2006: The NCEP Climate Forecast System. J. Climate, 19, 34833517.

  • Saravanan, R., , and P. Chang, 1999: Oceanic mixed layer feedback and tropical Atlantic variability. Geophys. Res. Lett., 26, 36293632.

    • Search Google Scholar
    • Export Citation
  • Schlosser, C. A., , and D. M. Mocko, 2003: Impact of snow conditions in spring dynamical seasonal predictions. J. Geophys. Res., 108, 86168629.

    • Search Google Scholar
    • Export Citation
  • Scinocca, J. F., , and N. McFarlane, 2004: The variability of modeled tropical precipitation. J. Atmos. Sci., 61, 19932015.

  • Scinocca, J. F., , N. McFarlane, , M. Lazare, , and J. Li, 2008: The CCCma third generation AGCM and its extension into the middle atmosphere. Atmos. Chem. Phys., 8, 70557074.

    • Search Google Scholar
    • Export Citation
  • Seiki, A., , and Y. N. Takayabu, 2007: Westerly wind bursts and their relationship with intraseasonal variations and ENSO. Part I: Statistics. Mon. Wea. Rev., 135, 33253345.

    • Search Google Scholar
    • Export Citation
  • Shabbar, A., 2006: The impact of El Niño-Southern Oscillation on the Canadian climate. Advances in Geophysics, Vol. 6, Academic Press, 149153.

    • Search Google Scholar
    • Export Citation
  • Shabbar, A., , and A. G. Barnston, 1996: Skill of seasonal climate forecasts in Canada using canonical correlation analysis. Mon. Wea. Rev., 124, 23702385.

    • Search Google Scholar
    • Export Citation
  • Shabbar, A., , B. Bonsal, , and M. Khandekar, 1997: Canadian precipitation patterns associated with the Southern Oscillation. J. Climate, 10, 30163027.

    • Search Google Scholar
    • Export Citation
  • Simmons, H. L., , S. R. Jayne, , L. C. S. Laurent, , and A. J. Weaver, 2004: Tidally driven mixing in a numerical model of the ocean general circulation. Ocean Modell., 6, 245263.

    • Search Google Scholar
    • Export Citation
  • Smith, D. M., , A. A. Scaife, , and B. P. Kirtman, 2012: What is the current state of scientific knowledge with regard to seasonal and decadal forecasting? Environ. Res. Lett., 7, 015602, doi:10.1088/1748-9326/7/1/015602.

    • Search Google Scholar
    • Export Citation
  • Smith, T. M., , and R. Reynolds, 2004: Improved extended reconstruction of SST (1854–1997). J. Climate, 17, 24662477.

  • Sprintall, J., , S. E. Wijffels, , R. Molcard, , and I. Jaya, 2009: Direct estimates of the Indonesian throughflow entering the Indian Ocean: 2004–2006. J. Geophys. Res., 114, C07001, doi:10.1029/2008JC005257.

    • Search Google Scholar
    • Export Citation
  • Steele, M., , R. Morley, , and W. Ermold, 2001: PHC: A global ocean hydrography with a high-quality Arctic Ocean. J. Climate, 14, 20792087.

    • Search Google Scholar
    • Export Citation
  • Sterl, A., and Coauthors, 2012: A look at the ocean in the EC-Earth climate model. Climate Dyn., 39, 26312657.

  • Stockdale, T. N., , M. A. Balmaseda, , and A. Vidard, 2006: Tropical Atlantic SST prediction with coupled ocean–atmosphere GCMs. J. Climate, 19, 60476061.

    • Search Google Scholar
    • Export Citation
  • Talley, L. D., 1999: Some aspects of ocean heat transport by the shallow, intermediate and deep overturning circulations. Mechanisms of Global Climate Change at Millennial Time Scales, Geophys. Monogr., Vol. 112, Amer. Geophys. Union, 1–22.

  • Tang, Y., , R. Kleeman, , A. M. Moore, , J. Vialard, , and A. Weaver, 2004: An off-line, numerically efficient initialization scheme in an oceanic general circulation model for El Niño-Southern Oscillation prediction. J. Geophys. Res., 109, C05014, doi:10.1029/2003JC002159.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., , R. J. Stouffer, , and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498.

    • Search Google Scholar
    • Export Citation
  • Thompson, D. W. J., , J. M. Wallace, , P. D. Jones, , and J. J. Kennedy, 2009: Identifying signatures of natural climate variability in time series of global-mean surface temperature: Methodology and insights. J. Climate, 22, 61206141.

    • Search Google Scholar
    • Export Citation
  • Thompson, K. R., , D. G. Wright, , Y. Lu, , and E. Demirov, 2006: A simple method for reducing seasonal bias and drift in eddy resolving ocean models. Ocean Modell., 8, 109125.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., , G. W. Branstator, , D. Karoly, , A. Kumar, , N.-C. Lau, , and C. Ropelewski, 1998: Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res., 103, 14 29114 324.

    • Search Google Scholar
    • Export Citation
  • Troccoli, A., and Coauthors, 2002: Salinity adjustments in the presence of temperature data assimilation. Mon. Wea. Rev., 130, 89102.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 29613012.

  • Vecchi, G. A., , and N. A. Bond, 2004: The Madden–Julian oscillation (MJO) and northern high latitude wintertime surface air temperatures. Geophys. Res. Lett., 31, L04104, doi:10.1029/2003GL018645.

    • Search Google Scholar
    • Export Citation
  • Verseghy, D. L., 2000: The Canadian Land Surface Scheme (CLASS): Its history and future. Atmos.–Ocean, 38, 113.

  • von Salzen, K., , N. A. McFarlane, , and M. Lazare, 2005: The role of shallow convection in the water and energy cycles of the atmosphere. Climate Dyn., 25, 671688.

    • Search Google Scholar
    • Export Citation
  • von Salzen, K., and Coauthors, 2013: The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: Physical processes. Atmos.–Ocean, 51, 104125, doi:10.1080/07055900.2012.755610.

    • Search Google Scholar
    • Export Citation
  • Wagner, A. J., 1989: Medium- and long-range forecasting. Wea. Forecasting, 4, 413426.

  • Waliser, D., and Coauthors, 2009: MJO simulation diagnostics. J. Climate, 22, 30063030.

  • Wang, Z., , C.-P. Chang, , and B. Wang, 2007: Impacts of El Niño and La Niña on the U.S. climate during northern summer. J. Climate, 20, 21652177.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M., , and G. N. Kiladis, 1999: Convectively coupled equatorial waves: Analysis of clouds and temperature in the wavenumber–frequency domain. J. Atmos. Sci., 56, 374399.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M., , and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 19171932.

    • Search Google Scholar
    • Export Citation
  • Wittenberg, A. T., , A. Rosati, , N.-C. Lau, , and J. J. Ploshay, 2006: GFDL's CM2 global coupled climate models. Part III: Tropical Pacific climate and ENSO. J. Climate, 19, 698722.

    • Search Google Scholar
    • Export Citation
  • Wu, A., , and W. W. Hsieh, 2004: The nonlinear Northern Hemisphere winter atmospheric response to ENSO. Geophys. Res. Lett., 31, L02203, doi:10.1029/2003GL018885.

    • Search Google Scholar
    • Export Citation
  • Xie, P., , and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 25392558.

    • Search Google Scholar
    • Export Citation
  • Yang, H., , and F. Wang, 2009: Revisiting the thermocline depth in the equatorial Pacific. J. Climate, 22, 38563863.

  • Yang, S.-C., , E. Kalnay, , M. Cai, , M. Rienecker, , G. Yuan, , and Z. Toth, 2006: ENSO bred vectors in coupled ocean–atmosphere general circulation models. J. Climate, 19, 14221436.

    • Search Google Scholar
    • Export Citation
  • Yang, X., , and T. DelSole, 2012: Systematic comparison of ENSO teleconnection patterns between models and observations. J. Climate, 25, 425446.

    • Search Google Scholar
    • Export Citation
  • Yoder, J. A., , and M. A. Kennelly, 2003: Seasonal and ENSO variability in global ocean phytoplankton chlorophyll derived from 4 years of SeaWiFS measurements. Global Biogeochem. Cycles, 17, 1112, doi:10.1029/2002GB001942.

    • Search Google Scholar
    • Export Citation
  • Yu, B., , and G. J. Boer, 2006: The variance of sea surface temperature and projected changes with global warming. Climate Dyn., 26, 801821.

    • Search Google Scholar
    • Export Citation
  • Zahariev, K., , J. R. Christian, , and K. L. Denman, 2008: Preindustrial, historical, and fertilization simulations using a global ocean carbon model with new parameterizations of iron limitation, calcification, and N2 fixation. Prog. Oceanogr., 77, 5682.

    • Search Google Scholar
    • Export Citation
  • Zheng, Y., , T. Shinoda, , J.-L. Lin, , and G. N. Kiladis, 2011: Sea surface temperature biases under the stratus cloud deck in the southeast Pacific Ocean in 19 IPCC AR4 coupled general circulation models. J. Climate, 24, 41394164.

    • Search Google Scholar
    • Export Citation
  • Zhou, S., , M. L'Heureux, , S. Weaver, , and A. Kumar, 2012: A composite study of the MJO influence on the surface air temperature and precipitation over the continental United States. Climate Dyn., 38, 14591471.

    • Search Google Scholar
    • Export Citation
  • Zhu, J., , B. Huang, , L. Marx, , J. L. Kinter III, , M. A. Balmaseda, , R.-H. Zhang, , and Z.-Z. Hu, 2012: Ensemble ENSO hindcasts initialized from multiple ocean analyses. Geophys. Res. Lett., 39, L09602, doi:10.1029/2012GL051503.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 410 410 193
PDF Downloads 176 176 25

The Canadian Seasonal to Interannual Prediction System. Part I: Models and Initialization

View More View Less
  • 1 Canadian Centre for Climate Modelling and Analysis, Environment Canada, University of Victoria, Victoria, British Columbia, Canada
  • | 2 Environmental Science and Engineering, University of Northern British Columbia, Prince George, British Columbia, Canada
  • | 3 Environment Canada, Downsview, Ontario, Canada
© Get Permissions
Restricted access

Abstract

The Canadian Seasonal to Interannual Prediction System (CanSIPS) became operational at Environment Canada's Canadian Meteorological Centre (CMC) in December 2011, replacing CMC's previous two-tier system. CanSIPS is a two-model forecasting system that combines ensemble forecasts from the Canadian Centre for Climate Modeling and Analysis (CCCma) Coupled Climate Model, versions 3 and 4 (CanCM3 and CanCM4, respectively). Mean climate as well as climate trends and variability in these models are evaluated in freely running historical simulations. Initial conditions for CanSIPS forecasts are obtained from an ensemble of coupled assimilation runs. These runs assimilate gridded atmospheric analyses by means of a procedure that resembles the incremental analysis update technique, but introduces only a fraction of the analysis increment in order that differences between ensemble members reflect the magnitude of observational uncertainties. The land surface is initialized through its response to the assimilative meteorology, whereas sea ice concentration and sea surface temperature are relaxed toward gridded observational values. The subsurface ocean is initialized through surface forcing provided by the assimilation run, together with an offline variational assimilation of gridded observational temperatures followed by an adjustment of the salinity field to preserve static stability. The performance of CanSIPS historical forecasts initialized every month over the period 1981–2010 is documented in a companion paper. The CanCM4 model and the initialization procedures developed for CanSIPS have been employed as well for decadal forecasts, including those contributing to phase 5 of the Coupled Model Intercomparison Project.

Corresponding author address: William Merryfield, Canadian Centre for Climate Modelling and Analysis, University of Victoria, P.O. Box 1700 STN CSC, Victoria, BC V8W 2Y2, Canada. E-mail: bill.merryfield@ec.gc.ca

Abstract

The Canadian Seasonal to Interannual Prediction System (CanSIPS) became operational at Environment Canada's Canadian Meteorological Centre (CMC) in December 2011, replacing CMC's previous two-tier system. CanSIPS is a two-model forecasting system that combines ensemble forecasts from the Canadian Centre for Climate Modeling and Analysis (CCCma) Coupled Climate Model, versions 3 and 4 (CanCM3 and CanCM4, respectively). Mean climate as well as climate trends and variability in these models are evaluated in freely running historical simulations. Initial conditions for CanSIPS forecasts are obtained from an ensemble of coupled assimilation runs. These runs assimilate gridded atmospheric analyses by means of a procedure that resembles the incremental analysis update technique, but introduces only a fraction of the analysis increment in order that differences between ensemble members reflect the magnitude of observational uncertainties. The land surface is initialized through its response to the assimilative meteorology, whereas sea ice concentration and sea surface temperature are relaxed toward gridded observational values. The subsurface ocean is initialized through surface forcing provided by the assimilation run, together with an offline variational assimilation of gridded observational temperatures followed by an adjustment of the salinity field to preserve static stability. The performance of CanSIPS historical forecasts initialized every month over the period 1981–2010 is documented in a companion paper. The CanCM4 model and the initialization procedures developed for CanSIPS have been employed as well for decadal forecasts, including those contributing to phase 5 of the Coupled Model Intercomparison Project.

Corresponding author address: William Merryfield, Canadian Centre for Climate Modelling and Analysis, University of Victoria, P.O. Box 1700 STN CSC, Victoria, BC V8W 2Y2, Canada. E-mail: bill.merryfield@ec.gc.ca
Save