We acknowledge the assistance of Upmanu Lall, Andrew Robertson, and Lisa Goddard of the Lamont Doherty Earth Observatory Centre of Columbia University, New York, and for access to their component model prediction database. This research was funded by the Australian Research Council and the Sydney Catchment Authority. The computation was performed using the freely available R statistical computing platform (R Development Core Team 2006, available online at http://www.r-project.org/). The helpful comments of anonymous Journal of Climate reviewers are gratefully acknowledged.
Aksu, C., , and S. Gunter, 1992: An empirical analysis of the accuracy of SA, OLS, ERLS and NRLS combination forecasts. Int. J. Forecasting, 8 , 27–43.
Armstrong, J. S., 1989: Combining forecasts: The end of the beginning or the beginning of the end? Int. J. Forecasting, 5 , 585–588.
Armstrong, J. S., , and J. S. Armstrong, 2001: Combining forecasts. Principles of Forecasting: A Handbook for Researchers and Practitioners, J. S. Armstrong, Ed., Kluwer Academic, 417–439.
Barnston, A. G., , S. J. Mason, , L. Goddard, , D. G. Dewitt, , and S. E. Zebiak, 2003: Multimodel ensembling in seasonal climate forecasting at IRI. Bull. Amer. Meteor. Soc., 84 , 1783–1796.
Bottomley, M., , C. K. Folland, , J. Hsiung, , R. E. Newell, , and D. E. Parker, 1990: Global Ocean Surface Temperature Atlas. Met Office, and Massachusetts Institute of Technology, 20 pp. and 313 plates.
Chandler, R. E., 2005: On the use of generalized linear models for interpreting climate variability. Environmetrics, 16 , 699–715.
Cleveland, W. S., , S. J. Devlin, , and E. Grosse, 1988: Regression by local fitting: Methods, properties, and computational algorithms. J. Econometrics, 37 , 87–114.
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.
Colman, A. W., , and M. K. Davey, 2003: Statistical prediction of global sea-surface temperature anomalies. Int. J. Climatol., 23 , 1677–1697.
Dawes, R., , R. Fildes, , M. Lawrence, , and K. Ord, 1994: The past and the future of forecasting research. Int. J. Forecasting, 10 , 151–159.
de Menezes, L. M., , D. W. Bunn, , and J. W. Taylor, 2000: Review of guidelines for the use of combined forecasts. Eur. J. Oper. Res., 120 , 190–204.
Deutsch, M., , C. W. J. Granger, , and T. Terasvirta, 1994: The combination of forecasts using changing weights. Int. J. Forecasting, 10 , 47–57.
Doblas-Reyes, F. J., , R. Hagedorn, , and T. N. Palmer, 2005: The rationale behind the success of multi-model ensembles in seasonal forecasting: II. Calibration and combination. Tellus, 57A , 234–252.
Dunteman, G. H., , and M. R. Ho, 2006: An Introduction to Generalized Linear Models. Quantitative Applications in the Social Sciences, Vol. 145, Sage Publications, 72 pp.
Ferrari, S. L. P., , and F. Cribari-Neto, 2004: Beta regression for modelling rates and proportions. J. Appl. Stat., 31 , 799–815.
Gelman, A., , and J. Hill, 2006: Data Analysis Using Regression and Multilevel/Hierarchical Models. 1st ed. Cambridge University Press, 625 pp.
Greene, A. M., , L. Goddard, , and U. Lall, 2006: Probabilistic multimodel regional temperature change projections. J. Climate, 19 , 4326–4343.
Hastie, T., , and D. Pregibon, 1992: Generalised linear models. Statistical Models in S, J. M. Chambers and T. Hastie, Eds., Wadsworth & Brooks, 195–248.
Hastie, T., , R. Tibshirani, , and J. Friedman, 2000: The Elements of Statistical Learning, Data Mining, Inference and Prediction. Springer Series in Statistics, Springer, 533 pp.
Hibon, M., , and T. Evgeniou, 2005: To combine or not to combine: Selecting among forecasts and their combinations. Int. J. Forecasting, 21 , 15–24.
Hoeting, J. A., , D. Madigan, , A. E. Raftery, , and C. T. Volinsky, 1999: Bayesian model averaging: A tutorial (with discussion). Stat. Sci., 14 , 382–417.
Kim, Y. O., , D. Jeong, , and I. H. Ko, 2006: Combining rainfall-runoff model outputs for improving ensemble streamflow prediction. J. Hydrol. Eng., 11 , 578–588.
Kondrashov, D., , S. Kravtsov, , A. W. Robertson, , and M. Ghil, 2005: A hierarchy of data-based ENSO models. J. Climate, 18 , 4425–4444.
Lall, U., , Y-I. Moon, , H-H. Kwon, , and K. Bosworth, 2006: Locally weighted polynomial regression: Parameter choice and application to forecasts of the Great Salt Lake. Water Resour. Res., 42 , W05422. doi:10.1029/2004WR003782.
Larrick, R. P., , and J. B. Soll, 2006: Intuitions about combining opinions: Misappreciation of the averaging principle. Manage. Sci., 52 , 111–127.
Lundberg, S., , T. Terasvirta, , and D. van Dijk, 2003: Time-varying smooth transition autoregressive models. J. Business Econ. Stat., 21 , 104–112.
Marshall, L. A., 2006: Bayesian analysis of rainfall-runoff models: Insights to parameter estimation, model comparison and hierarchical model development. Ph.D. thesis, School of Civil and Environmental Engineering, University of New South Wales, 222 pp.
Marshall, L. A., , D. Nott, , and A. Sharma, 2007: Towards dynamic catchment modelling: A Bayesian hierarchical modelling framework. Hydrol. Processes, 21 , 847–861.
McLeod, A. I., , D. J. Noakes, , K. W. Hipel, , and R. M. Thompstone, 1987: Combining hydrologic forecast. J. Water Resour. Plann. Manage., 113 , 29–41.
Mehrotra, R., , and A. Sharma, 2006: Conditional resampling of hydrologic time series using multiple predictor variables: A K-nearest neighbour approach. Adv. Water Resour., 29 , 987–999.
Palmer, T. N., and Coauthors, 2004: Development of a European multimodel ensemble system for seasonal-to-interannual prediction (DEMETER). Bull. Amer. Meteor. Soc., 85 , 853–872.
Pavan, V., , and F. J. Doblas-Reyes, 2000: Multi-model seasonal hindcasts over the Euro-Atlantic: Skill scores and dynamic features. Climate Dyn., 16 , 611–625.
Peng, P., , A. Kumar, , H. Van den Dool, , and A. G. Barnston, 2002: An analysis of multimodel ensemble predictions for seasonal climate anomalies. J. Geophys. Res., 107 , 4710. doi:10.1029/2002JD002712.
Phillips-Wren, G. E., , E. D. Hahn, , and G. A. Forgionne, 2004: A multiple-criteria framework for evaluation of decision support systems. Omega, 32 , 323.
Raftery, A. E., , T. Geneiting, , F. Balabdaoui, , and M. Polakowski, 2005: Using Bayesian model averaging to calibrate forecast ensembles. Mon. Wea. Rev., 133 , 1155–1174.
Ragonda, S. K., , B. Rajagopalan, , M. Clark, , and E. Zagona, 2006: A multimodel ensemble forecast framework: Application to spring seasonal flows in the Gunnison River Basin. Water Resour. Res., 42 , W09404. doi:10.1029/2005WR004653.
Rajagopalan, B., , U. Lall, , and S. E. Zebiak, 2002: Categorical climate forecasts through regularization and optimal combination of multiple GCM ensembles. Mon. Wea. Rev., 130 , 1792–1811.
Robertson, A. W., , U. Lall, , S. E. Zebiak, , and L. Goddard, 2004: Improved combination of multiple atmospheric GCM ensembles for seasonal prediction. Mon. Wea. Rev., 132 , 2732–2744.
Shamseldin, A. Y., , K. M. O’Connor, , and G. C. Liang, 1997: Methods for combining the outputs of different rainfall-runoff models. J. Hydrol., 197 , 203–229.
Sharma, A., 2000: Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 1—A strategy for system predictor identification. J. Hydrol., 239 , 232–239.
Sharma, A., , and U. Lall, 2004: Model averaging and its use in probabilistic forecasting of hydrologic variables. Hydrology, Science and Practice for the 21st Century, Imperial College, London, British Hydrological Society, 372–378.
Shephard, N., 1995: Generalized linear autoregressions. Economics working paper 8, Nuffield College, University of Oxford, 13 pp.
Smith, T. M., , and R. W. Reynolds, 2003: Extended reconstruction of global sea surface temperatures based on COADS data (1854–1997). J. Climate, 16 , 1495–1510.
Terui, N., , and H. K. van Dijk, 2002: Combined forecasts from linear and nonlinear time series models. Int. J. Forecasting, 18 , 421–438.
Van den Dool, H., 2000: Constructed analogue prediction of the east central tropical Pacific SST and the entire world ocean for 2001. Exp. Long-Lead Forecast Bull., 9 , 38–41.
Xiong, L., , A. Y. Shamseldin, , and K. M. O’Connor, 2001: A non-linear combination of the forecasts of rainfall-runoff models by the first-order Takagi-Sugeno fuzzy system. J. Hydrol., 245 , 196–217.
Yang, C., , R. E. Chandler, , V. S. Isham, , and H. S. Wheater, 2005: Spatial-temporal rainfall simulation using generalized linear models. Water Resour. Res., 41 , W11415. doi:10.1029/2004WR003739.
Yu, L., , S. Wang, , and K. K. Lai, 2005: A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates. Comput. Oper. Res., 32 , 2523–2541.