This research was supported by joint funding from the National Science Foundation (ATM-0830068), National Oceanic and Atmospheric Administration (NOAA; NA09OAR4310058), and the National Aeronautics and Space Administration (NASA; NNX09AN50G and NNX09AI84G) in the United States. We wish to thank all of the GLACE-2 participants. We also thank NOAA/MAPP and NASA Hydrology for their support of the overall coordination of the GLACE-2 project.
Alexander, M. A., , C. Deser, , and M. S. Timlin, 1999: The reemergence of SST anomalies in the North Pacific Ocean. J. Climate, 12, 2419–2433.
Anderson, J. L., , and H. M. Van den Dool, 1994: Skill and return of skill in dynamic extended-range forecasts. Mon. Wea. Rev., 122, 507–516.
Bacmeister, J., , P. J. Pegion, , S. D. Schubert, , and M. J. Suarez, 2000: Atlas of seasonal means simulated by the NSIPP 1 atmospheric GCM. NASA Tech. Memo. 2000-104606, Vol. 17, 194 pp.
Cover, T. M., , and J. A. Thomas, 1991: Elements of Information Theory. Wiley-Interscience, 542 pp.
DelSole, T., , and M. K. Tippett, 2007: Predictability: Recent insights from information theory. Rev. Geophys., 45, RG4002, doi:10.1029/2006RG000202.
Dirmeyer, P. A., , C. A. Schlosser, , and K. L. Brubaker, 2009: Precipitation, recycling and land memory: An integrated analysis. J. Hydrometeor., 10, 278–288.
Guo, Z., and Coauthors, 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part II: Analysis. J. Hydrometeor., 7, 611–625.
Koster, R. D., and Coauthors, 2010: Contribution of land surface initialization to subseasonal forecast skill: First results from a multi-model experiment. Geophys. Res. Lett., 37, L02402, doi:10.1029/2009GL041677.
Koster, R. D., and Coauthors, 2011: The second phase of the Global Land–Atmosphere Coupling Experiment: Soil moisture contributions to subseasonal forecast skill. J. Hydrometeor., 12, 805–822.
Lorenz, E. N., 1973: Predictability and periodicity: A review and extension. Proc. Third Conf. on Predictability and Statistics in the Atmospheric Sciences, Boulder, CO, Amer. Meteor. Soc., 1–4.
Misra, V., and Coauthors, 2007: Validating and understanding ENSO simulation in two coupled climate models. Tellus, 59A, 292–308.
Philander, S. G. H., 1990: El Niño, La Niña, and the Southern Oscillation. Academic Press, 293 pp.
Raddatz, T. J., and Coauthors, 2007: Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century? Climate Dyn., 29, 565–574, doi:10.1007/s00382-007-0247-8.
Roeckner, E., and Coauthors, 2003: The atmospheric general circulation model ECHAM5. Part I: Model description. Max-Planck-Institute for Meteorology Rep. 349, 140 pp.
Scinocca, J. F., , N. A. McFarlane, , M. Lazare, , J. Li, , and D. Plummer, 2008: The CCCma third generation AGCM and its extension into the middle atmosphere. Atmos. Chem. Phys., 8, 7055–7074.
Shukla, J., , and J. L. Kinter, 2006: Predictability of seasonal climate variations: A pedagogical view. Predictability of Weather and Climate, T. N. Palmer and R. Hagedorn, Eds., Cambridge University Press, 306–341.
Simmons, A. J., , and A. Hollingsworth, 2002: Some aspects of the improvement in skill of numerical weather prediction. Quart. J. Roy. Meteor. Soc., 128, 647–677.
Wajsowicz, R. C., 2007: Seasonal-to-interannual forecasting of tropical Indian Ocean sea surface temperature anomalies: Potential predictability and barriers. J. Climate, 20, 3320–3343.