Title
Significance of model credibility in estimating climate projection distributions for regional hydroclimatological risk assessments
Document Type
Article
Publication Date
9-2008
Publisher
Springer Netherlands
Abstract
Ensembles of historical climate simulations and climate projections from the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset were investigated to determine how model credibility affects apparent relative scenario likelihoods in regional risk assessments. Methods were developed and applied in a Northern California case study. An ensemble of 59 twentieth century climate simulations from 17 WCRP CMIP3 models was analyzed to evaluate relative model credibility associated with a 75-member projection ensemble from the same 17 models. Credibility was assessed based on how models realistically reproduced selected statistics of historical climate relevant to California climatology. Metrics of this credibility were used to derive relative model weights leading to weight-threshold culling of models contributing to the projection ensemble. Density functions were then estimated for two projected quantities (temperature and precipitation), with and without considering credibility-based ensemble reductions. An analysis for Northern California showed that, while some models seem more capable at recreating limited aspects twentieth century climate, the overall tendency is for comparable model performance when several credibility measures are combined. Use of these metrics to decide which models to include in density function development led to local adjustments to function shapes, but led to limited affect on breadth and central tendency, which were found to be more influenced by “completeness” of the original ensemble in terms of models and emissions pathways.
Recommended Citation
Brekke, L.D., M.D. Dettinger, E.P. Maurer, and M. Anderson, 2008, Significance of Model Credibility in estimating Climate Projection Distributions for Regional Hydroclimatological Risk Assessments, Climatic Change Vol. 89 No. 3-4, 371-394, doi: 10.1007/s10584-007-9388-3.
