A Bayesian Hierarchical Model for Heterogeneous RCM-GCM Multimodel Ensembles

摘要: AbstractA Bayesian hierarchical model for heterogeneous multimodel ensembles of global and regional climate models is presented. By applying the methodology herein to seasonal temperature averages from ENSEMBLES project, probabilistic projections future are derived. Intermodel correlations that particularly strong between their driving explicitly accounted for. Instead working with time slices, a data archive investigated in transient setting. This enables coherent treatment internal variability on multidecadal scales. Results presented four European regions highlight feasibility approach. In particular, able objectively identify patterns changes, ways previously required subjective expert knowledge. Furthermore, this study underlines assumptions about bias changes have an effect projected warming. It also shown valid...