This work was completed as part of the Water Information Research and Development Alliance (WIRADA), a collaboration between CSIRO and the Bureau of Meteorology to facilitate the transfer of research to operations. The work was also partly funded by the CSIRO OCE Science Leader Scheme. We thank Dr. Eun-Pa Lim for providing the grid coordinates used in the Predictive Ocean Atmosphere Model for Australia (POAMA), Cathy Bowditch for proofreading and editing an early version of the manuscript, and Dr. William Wang for providing valuable comments on the work. We are most grateful to two anonymous reviewers, whose insightful critique and constructive suggestions have led us to improve the paper significantly.
Casanova, S., , and B. Ahrens, 2009: On the weighting of multimodel ensembles in seasonal and short-range weather forecasting. Mon. Wea. Rev., 137, 3811–3822.
Cheng, J., , J. Yang, , Y. Zhou, , and Y. Cui, 2006: Flexible background mixture models for foreground segmentation. Image Vision Comput., 24, 473–482.
Clarke, B., 2003: Comparing Bayesian model averaging and stacking when model approximation error cannot be ignored. J. Mach. Learn. Res., 4, 683–712.
Coelho, C. A. S., , S. Pezzulli, , M. Balmaseda, , F. J. Doblas-Reyes, , and D. B. Stephenson, 2004: Forecast calibration and combination: A simple Bayesian approach for ENSO. J. Climate, 17, 1504–1516.
Domingos, P., 2000: Bayesian averaging of classifiers and the overfitting problem. Proceedings of the Seventeenth International Conference on Machine Learning, Morgan Kaufmann Publishers, 223–230.
Drosdowsky, W., , and L. E. Chambers, 2001: Near-global sea surface temperature anomalies as predictors of Australian seasonal rainfall. J. Climate, 14, 1677–1687.
Eklund, J., , and S. Karlsson, 2007: Forecast combination and model averaging using predictive measures. Econ. Rev., 26, 329–363.
Fawcett, R., , D. Jones, , and G. Beard, 2005: A verification of publicly issued seasonal forecasts issued by the Australian Bureau of Meteorology: 1998-2003. Aust. Meteor. Mag., 54, 1–13.
Geweke, J., , and C. Whiteman, 2006: Bayesian forecasting. Handbook of Economic Forecasting, G. Elliot, C. W. J. Granger, and A. Timmermann, Eds., Handbooks in Economics, Vol. 1, North-Holland, 3–80.
Hoeting, J. A., , D. Madigan, , A. E. Raftery, , and C. T. Volinsky, 1999: Bayesian model averaging: A tutorial. Stat. Sci., 14, 382–401.
Jackson, C. H., , S. G. Thompson, , and L. D. Sharples, 2009: Accounting for uncertainty in health economic decision models by using model averaging. J. Roy. Stat. Soc., 172A, 383–404.
Jones, D. A., , W. Wang, , and R. Fawcett, 2009: High-quality spatial climate data-sets for Australia. Aust. Meteor. Oceanogr. J., 58, 233–248.
Luo, L., , E. F. Wood, , and M. Pan, 2007: Bayesian merging of multiple climate model forecasts for seasonal hydrological predictions. J. Geophys. Res., 112, D10102, doi:10.1029/2006JD007655.
Madigan, D., , and A. E. Raftery, 1994: Model selection and accounting for model uncertainty in graphical models using OCCAM’s window. J. Amer. Stat. Assoc., 89, 1535–1546.
Meyers, G., , P. McIntosh, , L. Pigot, , and M. Pook, 2007: The years of El Niño, La Niña, and interactions with the tropical Indian Ocean. J. Climate, 20, 2872–2880.
Minka, T., 2000: Bayesian model averaging is not model combination. MIT Media Lab Note, 2 pp.
Monteith, K., , J. Carroll, , K. Seppi, , and T. Martinez, 2011: Turning Bayesian model averaging into Bayesian model combination. Proceedings of the IEEE International Joint Conference on Neural Networks, IEEE, 2657–2663.
Raftery, A. E., , D. Madigan, , and J. A. Hoeting, 1997: Bayesian model averaging for linear regression models. J. Amer. Stat. Assoc., 92, 179–191.
Raftery, A. E., , T. Gneiting, , F. Balabdaoui, , and M. Polakowski, 2005: Using Bayesian model averaging to calibrate forecast ensembles. Mon. Wea. Rev., 133, 1155–1174.
Risbey, J. S., , M. J. Pook, , P. C. McIntosh, , M. C. Wheeler, , and H. H. Hendon, 2009: On the remote drivers of rainfall variability in Australia. Mon. Wea. Rev., 137, 3233–3253.
Robertson, D. E., , and Q. J. Wang, 2012: A Bayesian approach to predictor selection for seasonal streamflow forecasting. J. Hydrometeor., 13, 155–171.
Rust, R. T., , and D. C. Schmittlein, 1985: A Bayesian cross-validated likelihood method for comparing alternative specifications of quantitative models. Mark. Sci., 4, 20–40.
Schepen, A., , Q. J. Wang, , and D. E. Robertson, 2012: Evidence for using lagged climate indices to forecast Australian seasonal rainfall. J. Climate, 25, 1230–1246.
Shinozaki, T., , S. Furui, , and T. Kawahara, 2010: Gaussian mixture optimization based on efficient cross-validation. IEEE J. Sel. Top. Signal Process., 4, 540–547.
Smith, T. M., , R. W. Reynolds, , T. C. Peterson, , and J. Lawrimore, 2008: Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). J. Climate, 21, 2283–2296.
Smyth, P., 1996: Clustering using Monte Carlo cross-validation. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, E. Simoudis, J. Han, and U. Fayyad, Eds., AAAI Press, 126–133.
Stephenson, D. B., , C. A. S. Coelho, , F. J. Doblas-Reyes, , and M. Balmaseda, 2005: Forecast assimilation: A unified framework for the combination of multi-model weather and climate predictions. Tellus, 57A, 253–264.
Stone, M., 1977: An asymptotic equivalence of choice of model by cross-validation and Akaike’s criterion. J. Roy. Stat. Soc., 39B, 44–47.
Taschetto, A. S., , C. C. Ummenhofer, , A. Sen Gupta, , and M. H. England, 2009: Effect of anomalous warming in the central Pacific on the Australian monsoon. Geophys. Res. Lett., 36, L12704, doi:10.1029/2009GL038416.
Verdon, D. C., , and S. W. Franks, 2005: Indian Ocean sea surface temperature variability and winter rainfall: Eastern Australia. Water Resour. Res., 41, W09413, doi:10.1029/2004WR003845.
Wang, Q. J., , and D. E. Robertson, 2011: Multisite probabilistic forecasting of seasonal flows for streams with zero value occurrences. Water Resour. Res., 47, W02546, doi:10.1029/2010WR009333.
Wang, Q. J., , D. E. Robertson, , and F. H. S. Chiew, 2009: A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites. Water Resour. Res., 45, W05407, doi:10.1029/2008WR007355.
Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. Academic Press, 467 pp.
Yeo, I. K., , and R. A. Johnson, 2000: A new family of power transformations to improve normality or symmetry. Biometrika, 87, 954–959.
Zhao, M., , and H. H. Hendon, 2009: Representation and prediction of the Indian Ocean dipole in the POAMA seasonal forecast model. Quart. J. Roy. Meteor. Soc., 135, 337–352.
Zivkovic, Z., , and F. van der Heijden, 2004: Recursive unsupervised learning of finite mixture models. IEEE Trans. Pattern Anal. Mach. Intell., 26, 651–656.