A framework for developing high‐resolution multi‐model climate projections: 21st century scenarios for the UK

This article proposes a framework for building climate projections from an ensemble of global circulation models (GCMs) at the local scale required for impact studies. The proposed method relies on a fine-scale gridded baseline climatology and consists of the following steps: (1) building appropriate precipitation and temperature time series from land areas covered by GCM sea cells; (2) correction of GCM outputs inherent biases through ‘quantile-based mapping’; and (3) disaggregation of bias-corrected outputs with monthly spatial anomalies between GCM-specific and observed spatial scales. The overall framework is applied to derive 21st century seasonal climate projections and inter-annual variability for the UK based on an ensemble of six GCMs run under two different emissions scenarios. Results show a large dispersion of changes within the multi-GCM ensemble, along with a good comparison between scenarios from individual ensemble members and from previous UK and European studies using dynamically downscaled outputs from corresponding GCMs. The framework presented in this article provides appropriate outputs to take account of the uncertainty in global model configuration within impacts studies that are influencing current decisions on major investments in flood risk management and water resources. Copyright © 2007 Royal Meteorological Society

[1]  Deliang L. Chen,et al.  Statistical downscaling based on dynamically downscaled predictors: Application to monthly precipitation in Sweden , 2003 .

[2]  J. Houghton,et al.  Climate change 2001 : the scientific basis , 2001 .

[3]  S. Min,et al.  Future Projections of East Asian Climate Change from Multi-AOGCM Ensembles of IPCC SRES Scenario Simulations , 2004 .

[4]  J. Corte-Real,et al.  European winter precipitation extremes and large-scale circulation: a coupled model and its scenarios , 2007 .

[5]  K. Taylor.  Summarizing multiple aspects of model performance in a single diagram , 2001 .

[6]  M. Noguer,et al.  Climate change 2001: The scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change , 2002 .

[7]  GCM and downscaling uncertainty in modelling of current river flow: why is it important for future impacts? , 2006 .

[8]  Mike Hulme,et al.  Representing uncertainty in climate change scenarios: a Monte-Carlo approach , 2000 .

[9]  R. Wilby,et al.  A framework for assessing uncertainties in climate change impacts: Low‐flow scenarios for the River Thames, UK , 2006 .

[10]  David P. Rowell,et al.  A Demonstration of the Uncertainty in Projections of UK Climate Change Resulting from Regional Model Formulation , 2006 .

[11]  C. Bretherton,et al.  Statistical Precipitation Downscaling over the Northwestern United States Using Numerically Simulated Precipitation as a Predictor , 2003 .

[12]  S. O’Farrell,et al.  Transient Climate Change in the CSIRO Coupled Model with Dynamic Sea Ice , 1997 .

[13]  Eric P. Salathe,et al.  Comparison of various precipitation downscaling methods for the simulation of streamflow in a rainshadow river basin , 2003 .

[14]  Richard L. Smith,et al.  Quantifying Uncertainty in Projections of Regional Climate Change: A Bayesian Approach to the Analysis of Multimodel Ensembles , 2005 .

[15]  T. Huntington.  Evidence for intensification of the global water cycle: Review and synthesis , 2006 .

[16]  B. Hewitson,et al.  Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa , 2006 .

[17]  F. Giorgi,et al.  PRUDENCE employs new methods to assess European climate change , 2002 .

[18]  Jeremy S. Pal,et al.  Simulation of regional‐scale water and energy budgets: Representation of subgrid cloud and precipitation processes within RegCM , 2000 .

[19]  K. Taylor,et al.  An overview of results from the Coupled Model Intercomparison Project , 2003 .

[20]  John F. B. Mitchell,et al.  Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios , 2003 .

[21]  Clare M. Goodess,et al.  Interannual variability of European extreme winter rainfall and links with mean large‐scale circulation , 2004 .

[22]  F. Giorgi,et al.  Climate Change Prediction , 2005 .

[23]  Christian W. Dawson,et al.  SDSM - a decision support tool for the assessment of regional climate change impacts , 2002, Environ. Model. Softw..

[24]  U. Willén,et al.  European climate in the late twenty-first century: regional simulations with two driving global models and two forcing scenarios , 2004 .

[25]  Richard G. Jones,et al.  Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results , 2005 .

[26]  U. Willén,et al.  The development of the regional coupled ocean-atmosphere model RCAO , 2002 .

[27]  Upmanu Lall,et al.  Probabilistic multimodel regional temperature change projections , 2006 .

[28]  Roger Jones,et al.  Managing Uncertainty in Climate Change Projections – Issues for Impact Assessment , 2000 .

[29]  Peter J. Gleckler,et al.  Evaluation of continental precipitation in 20th century climate simulations: The utility of multimodel statistics , 2006 .

[30]  David P. Rowell,et al.  Causes and uncertainty of future summer drying over Europe , 2006 .

[31]  S. Emori,et al.  Coupled Ocean-Atmosphere Model Experiments of Future Climate Change with an Explicit Representation , 1999 .

[32]  F. Massey.  The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .

[33]  R. Benestad.  Tentative probabilistic temperature scenarios for northern Europe , 2004 .

[34]  D. Lettenmaier,et al.  Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs , 2004 .

[35]  M. Webb,et al.  Quantification of modelling uncertainties in a large ensemble of climate change simulations , 2004, Nature.

[36]  Alexei G. Sankovski,et al.  Special report on emissions scenarios , 2000 .

[37]  M. Perry.  National Climate Information Centre Climate Memorandum No 21 A spatial analysis of trends in the UK climate since 1914 using gridded datasets , 2008 .

[38]  G. Boer,et al.  Warming asymmetry in climate change simulations , 2001 .

[39]  David Lister,et al.  The development of monthly temperature series for Scotland and Northern Ireland , 2004 .

[40]  M. Perry,et al.  The generation of monthly gridded datasets for a range of climatic variables over the UK , 2005 .

[41]  Ann Henderson-Sellers,et al.  GRID BOX OR GRID POINT: WHAT TYPE OF DATA DO GCMs DELIVER TO CLIMATE IMPACTS RESEARCHERS? , 1996 .

[42]  F. Giorgi,et al.  Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the reliability ensemble averaging (REA) method , 2002 .

[43]  Zong-ci Zhao,et al.  Climate change 2001, the scientific basis, chap. 8: model evaluation. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change IPCC , 2001 .

[44]  David P. Rowell,et al.  A scenario of European climate change for the late twenty-first century: seasonal means and interannual variability , 2005 .

[45]  T. Osborn.  Areal and point precipitation intensity changes: Implications for the application of climate models , 1997 .

[46]  Jeremy S. Pal,et al.  Mean, interannual variability and trends in a regional climate change experiment over Europe. II: climate change scenarios (2071–2100) , 2004 .