Climatic Change

, Volume 76, Issue 1–2, pp 149–168

A Component-Resampling Approach for Estimating Probability Distributions from Small Forecast Ensembles



In many meteorological and climatological modeling applications, the availability of ensembles of predictions containing very large numbers of members would substantially ease statistical analyses and validations. This study describes and demonstrates an objective approach for generating large ensembles of “additional” realizations from smaller ensembles, where the additional ensemble members share important first-and second-order statistical characteristics and some dynamic relations within the original ensemble. By decomposing the original ensemble members into assuredly independent time-series components (using a form of principal component decomposition) that can then be resampled randomly and recombined, the component-resampling procedure generates additional time series that follow the large and small scale structures in the original ensemble members, without requiring any tuning by the user. The method is demonstrated by applications to operational medium-range weather forecast ensembles from a single NCEP weather model and application to a multi-model, multi-emission-scenarios ensemble of 21st Century climate-change projections.


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  1. Allen, M. R. and Ingram, W. J.: 2002, ‘Constraints on future changes in climate and the hydrologic cycle’, Nature 419, 224–232.CrossRefGoogle Scholar
  2. Blyth, T. S. and Robertson, E. F.: 2002, Basic Linear Algebra, Springer, New York, 232 p.Google Scholar
  3. Dai, A., Wigley, T. M. L., Boville, B. A., Kiehl, J. T., and Buja, L. E.: 2001, ‘Climates of the twentieth and twenty-first centuries simulated by the ncar climate system model’, J. Clim. 14, 485– 519.CrossRefGoogle Scholar
  4. Dettinger, M. D., Battisti, D. S., Garreaud, R. D., McCabe, G. J., and Bitz, C. M.: 2001, ‘Interhemispheric Effects of Interannual and Decadal ENSO-like Climate Variations on the Americas’, in V. Markgraf (ed.), Interhemispheric Climate Linkages, Academic Press, San Diego, pp. 1–16.Google Scholar
  5. Ghil, M., Allen, M. R., Dettinger, M. D., Ide, K., Kondrashov, D., Mann, M. E., Robertson, A. W., Saunders, A., Tian, Y., Varadi, F., and Yiou, P.: 2002, ‘Advanced spectral methods for climatic time series’, Reviews of Geophysics 40, doi:10.1029/2000RG000092, pp. 1–41.CrossRefGoogle Scholar
  6. Ghil, M. and Childress, S.: 1987, Topics In Geophysical Fluid Dynamics – Atmospheric Dynamics, Dynamo Theory, and Climate Dynamics, Springer-Verlag, New York, 485 p.Google Scholar
  7. Ghil, M. and Vautard, R.: 1991, ‘Interdecadal oscillations and the warming trend in global temperature time series’, Nature 350, 324–327.CrossRefGoogle Scholar
  8. Hayhoe, K., Cayan, D., Field, C., Frumhoff, P., Maurer, E., Miller, N., Moser, S., Schneider, S., Cahill, K., Cleland, E., Dale, L., Drapek, R., Hanneman, R. M., Kalkstein, L., Lenihan, L., Lunch, C., Neilson, R., Sheridan, S., and Verville, J.: 2004, ‘Emissions pathways, climate change, and impacts on California’, Proc., National Academy of Sciences 101, 12422–12427.Google Scholar
  9. Houghton and others (eds.): 2001, Climate Change 2001 – The Scientific Basis, Cambridge University Press, 525–582.Google Scholar
  10. Jeton, A. E., Dettinger, M. D., and Smith, J. L.: 1996, Potential Effects of Climate Change on Streamflow, Eastern and Western Slopes of the Sierra Nevada, California and Nevada, U.S. Geological Survey Water Resources Investigations Report 95 – 4260, 44 p.Google Scholar
  11. Krishnamurti, T. N., Kishtawal, C. M., LaRow, T., Bachiochi, D., Zhang, Z., Williford, C. E., Gadgil, S., and Surendran, S.: 2000, ‘Multimodel superensemble forecasts for weather and seasonal climate’, J. Clim. 13, 4196–4216.CrossRefGoogle Scholar
  12. Richardson, D. S.: 2001, ‘Measures of skill and value of ensemble prediction systems, their interrelationship and the effect of ensemble size’, Q. J. Royal Met. Soc. 127, 2473–2489.CrossRefGoogle Scholar
  13. Stewart, I., Cayan, D. R., and Dettinger, M. D.: 2004, ‘Changes in snowmelt runoff timing in western north america under a ‘Business As Usual’ climate change scenario’, Climatic Change, 15 p.Google Scholar
  14. Toth, Z., and Kalnay, E.: 1993, ‘Ensemble forecasting at NMC: The generation of perturbations’, Bull. Amer. Meteor. Soc. 74, 2317–2330.CrossRefGoogle Scholar
  15. Toth, Z., Talagrand, O., Candille, G., and Zhu, Y.: 2003, ‘Probability and ensemble forecasts’, in I. T. Jolliffe and D. B. Stephenson (eds.), Forecast Verification – A Practitioner's Guide in Atmospheric Science John Wiley & Sons, San Francisco, pp. 137–164.Google Scholar
  16. Traction, M. S. and Kalnay, E.: 1993, ‘Ensemble forecasting at NMC: Operation implementation’, Weather and Forecasting 8, 379–398.CrossRefGoogle Scholar
  17. Von Storch, H. and Zwiers, F. W.: 2002, Statistical Analysis in Climate Research, Cambridge University} Press, New York, 494 p.Google Scholar
  18. Weare, B. C., and Nasstrom, J. S.: 1982, ‘Examples of extended empirical orthogonal function analysis}’, Mon. Wea. Rev. 110, 481–485.CrossRefGoogle Scholar
  19. Zhu, Y., Toth, Z., Wobus, R., Richardson, D., and Mylne, K.: 2002, ‘The economic value of ensemble-based weather forecasts’, Bull. Amer. Met. Soc. 83, 73–83.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  1. 1.U.S. Geological SurveyScripps Institution of Oceanography, Dept. 0224La JollaUSA

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