• Christensen, J. H., , and O. B. Christensen, 2007: A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Climatic Change, 81 , (Suppl. 1). 730.

    • Search Google Scholar
    • Export Citation
  • Christensen, J. H., , J. Räisänen, , T. Iversen, , D. Bjørge, , O. B. Christensen, , and M. Rummukainen, 2001: A synthesis of regional climate change simulations—A Scandinavian perspective. Geophys. Res. Lett., 28 , 10031006.

    • Search Google Scholar
    • Export Citation
  • Collins, M., , B. B. B. Booth, , B. Bhaskaran, , G. R. Harris, , J. M. Murphy, , D. M. H. Sexton, , and M. J. Webb, 2010: Climate model errors, feedbacks and forcings: A comparison of perturbed physics and multi-model ensembles. Climate Dyn., in press, doi:10.1007/s00382-010-0808-0.

    • Search Google Scholar
    • Export Citation
  • Déqué, M., and Coauthors, 2007: An intercomparison of regional climate simulations for Europe: Assessing uncertainties in model projections. Climatic Change, 81 , (Suppl. 1). 5370.

    • Search Google Scholar
    • Export Citation
  • Harris, G. R., , D. M. H. Sexton, , B. B. B. Booth, , M. Collins, , J. M. Murphy, , and M. J. Webb, 2006: Frequency distributions of transient regional climate change from perturbed physics ensembles of general circulation model simulations. Climate Dyn., 27 , 357375. doi:10.1007/s00382-006-0142-8.

    • Search Google Scholar
    • Export Citation
  • Hewitt, C. D., , and D. J. Griggs, 2004: Ensembles-based predictions of climate changes and their impacts. Eos, Trans. Amer. Geophys. Union, 85 .doi:10.1029/2004EO520005.

    • Search Google Scholar
    • Export Citation
  • Jacob, D., and Coauthors, 2001: A comprehensive model intercomparison study investigating the water budget during the BALTEX-PIDCAP period. Meteor. Atmos. Phys., 77 , 1943.

    • Search Google Scholar
    • Export Citation
  • Jacob, D., , O. B. Christensen, , F. J. Doblas-Reyes, , C. Goodess, , A. Klein Tank, , P. Lorenz, , and E. Roeckner, 2008: Information on observations, global and regional modelling data availability and statistical downscaling. ENSEMBLES Tech. Rep. 4, 10 pp. [Available online at http://ensembles-eu.metoffice.com/tech_reports/ETR_4_vn1.pdf].

    • Search Google Scholar
    • Export Citation
  • Jungclaus, J. H., and Coauthors, 2006: Ocean circulation and tropical variability in the coupled ECHAM5/MPI-OM. J. Climate, 19 , 39523972.

    • Search Google Scholar
    • Export Citation
  • Kendon, E. J., , D. P. Rowell, , R. G. Jones, , and E. Buonomo, 2008: Robustness of future changes in local precipitation extremes. J. Climate, 21 , 42804297.

    • Search Google Scholar
    • Export Citation
  • Kendon, E. J., , D. P. Rowell, , and R. G. Jones, 2010: Mechanisms and reliability of future projected changes in daily precipitation. Climate Dyn., 35 , 489509. doi:10.1007/s00382-009-0639-z.

    • Search Google Scholar
    • Export Citation
  • Kjellström, E., , G. Nikulin, , U. Hansson, , G. Strandberg, , and A. Ullerstig, 2010: 21st century changes in the European climate: Uncertainties derived from an ensemble of regional climate model simulations. Tellus, doi:10.1111/j.1600-0870.2010.00475.x.

    • Search Google Scholar
    • Export Citation
  • Lenderink, G., , B. van den Hurk, , E. van Meijgaard, , A. van Ulden, , and J. Cuijpers, 2003: Simulation of present-day climate in RACMO2: First results and model developments. KNMI Tech. Rep. 252, 24 pp. [Available online at http://www.knmi.nl/publications/fulltexts/trracmo2.pdf].

    • Search Google Scholar
    • Export Citation
  • Lind, P., , and E. Kjellström, 2008: Temperature and precipitation changes in Sweden: A wide range of model-based projections for the 21st century. SMHI Meteorology and Climatology Rep. 113, 66 pp. [Available online at http://www.smhi.se/polopoly_fs/1.3297!RMK113_rapport_090421.pdf].

    • Search Google Scholar
    • Export Citation
  • Mearns, L. O., , W. Gutowski, , R. Jones, , R. Leung, , S. McGinnis, , A. Nunes, , and Y. Qian, 2009: A Regional Climate Change Assessment Program for North America. Eos, Trans. Amer. Geophys. Union, 90 , 311. doi:10.1029/2009EO360002.

    • Search Google Scholar
    • Export Citation
  • Mitchell, J. F. B., , T. C. Johns, , M. Eagles, , W. J. Ingram, , and R. A. Davis, 1999: Towards the construction of climate change scenarios. Climatic Change, 41 , 547581.

    • Search Google Scholar
    • Export Citation
  • Mitchell, T. D., 2003: Pattern scaling: An examination of the accuracy of the technique for describing future climates. Climatic Change, 60 , 217242.

    • Search Google Scholar
    • Export Citation
  • Nakićenović, N., and Coauthors, 2000: Emission Scenarios. Cambridge University Press, 599 pp.

  • Roeckner, E., and Coauthors, 2006: Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model. J. Climate, 19 , 37713791.

    • Search Google Scholar
    • Export Citation
  • Rowell, D. P., , and R. G. Jones, 2006: Causes and uncertainty of future summer drying over Europe. Climate Dyn., 27 , 281299.

  • Rummukainen, M., and Coauthors, 2003: Regional climate scenarios for use in Nordic water resources studies. Nord. Hydrol., 34 , 399412.

    • Search Google Scholar
    • Export Citation
  • Ruosteenoja, K., , H. Tuomenvirta, , and K. Jylhä, 2007: GCM-based regional temperature and precipitation change estimates for Europe under four SRES scenarios applying a super-ensemble pattern-scaling method. Climatic Change, 81 , (Suppl. 1). 193208.

    • Search Google Scholar
    • Export Citation
  • Samuelsson, P., and Coauthors, 2010: The Rossby Centre regional climate model RCA3: Model description and performance. Tellus, doi:10.1111/j.1600-0870.2010.00478.x.

    • Search Google Scholar
    • Export Citation
  • Sapiano, M. R. P., , D. B. Stephenson, , H. J. Grubb, , and P. A. Arkin, 2006: Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model. J. Climate, 19 , 41544166.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., 1999: Conceptual framework for changes of extremes of the hydrological cycle with climate change. Climatic Change, 42 , 327339.

    • Search Google Scholar
    • Export Citation
  • Widmann, M., , C. S. Bretherton, , and E. P. Salathe, 2003: Statistical precipitation downscaling over the northwestern United States using numerically simulated precipitation as a predictor. J. Climate, 16 , 799816.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 286 286 70
PDF Downloads 269 269 79

Using and Designing GCM–RCM Ensemble Regional Climate Projections

View More View Less
  • 1 Met Office Hadley Centre, Exeter, United Kingdom
  • | 2 Met Office Hadley Centre (Reading Unit), University of Reading, Reading, United Kingdom
  • | 3 Rossby Centre, SMHI, Norrköping, Sweden
  • | 4 Met Office Hadley Centre, Exeter, United Kingdom
© Get Permissions
Restricted access

Abstract

Multimodel ensembles, whereby different global climate models (GCMs) and regional climate models (RCMs) are combined, have been widely used to explore uncertainties in regional climate projections. In this study, the extent to which information can be enhanced from sparsely filled GCM–RCM ensemble matrices and the way in which simulations should be prioritized to sample uncertainties most effectively are examined.

A simple scaling technique, whereby the local climate response in an RCM is predicted from the large-scale change in the GCM, is found to often show skill in estimating local changes for missing GCM–RCM combinations. In particular, scaling shows skill for precipitation indices (including mean, variance, and extremes) across Europe in winter and mean and extreme temperature in summer and winter, except for hot extremes over central/northern Europe in summer. However, internal variability significantly impacts the ability to determine scaling skill for precipitation indices, with a three-member ensemble found to be insufficient for identifying robust local scaling relationships in many cases.

This study suggests that, given limited computer resources, ensembles should be designed to prioritize the sampling of GCM uncertainty, using a reduced set of RCMs. Exceptions are found over the Alps and northeastern Europe in winter and central Europe in summer, where sampling multiple RCMs may be equally or more important for capturing uncertainty in local temperature or precipitation change. This reflects the significant role of local processes in these regions. Also, to determine the ensemble strategy in some cases, notably precipitation extremes in summer, better sampling of internal variability is needed.

Corresponding author address: Elizabeth Kendon, Fitzroy Road, Met Office Hadley Centre, Exeter EX1 3PB, United Kingdom. Email: elizabeth.kendon@metoffice.gov.uk

Abstract

Multimodel ensembles, whereby different global climate models (GCMs) and regional climate models (RCMs) are combined, have been widely used to explore uncertainties in regional climate projections. In this study, the extent to which information can be enhanced from sparsely filled GCM–RCM ensemble matrices and the way in which simulations should be prioritized to sample uncertainties most effectively are examined.

A simple scaling technique, whereby the local climate response in an RCM is predicted from the large-scale change in the GCM, is found to often show skill in estimating local changes for missing GCM–RCM combinations. In particular, scaling shows skill for precipitation indices (including mean, variance, and extremes) across Europe in winter and mean and extreme temperature in summer and winter, except for hot extremes over central/northern Europe in summer. However, internal variability significantly impacts the ability to determine scaling skill for precipitation indices, with a three-member ensemble found to be insufficient for identifying robust local scaling relationships in many cases.

This study suggests that, given limited computer resources, ensembles should be designed to prioritize the sampling of GCM uncertainty, using a reduced set of RCMs. Exceptions are found over the Alps and northeastern Europe in winter and central Europe in summer, where sampling multiple RCMs may be equally or more important for capturing uncertainty in local temperature or precipitation change. This reflects the significant role of local processes in these regions. Also, to determine the ensemble strategy in some cases, notably precipitation extremes in summer, better sampling of internal variability is needed.

Corresponding author address: Elizabeth Kendon, Fitzroy Road, Met Office Hadley Centre, Exeter EX1 3PB, United Kingdom. Email: elizabeth.kendon@metoffice.gov.uk

Save