Addressing interdependency in a multi - model ensemble by 1 interpolation of model properties

6 The diverse set of Earth System Models used to conduct the CMIP5 ensemble partly sam7 ple the uncertainties in future climate projections. However, combining those projections 8 is complicated by the fact that models developed by different groups share ideas, code and 9 therefore biases. We propose a method for combining model results into single or multivari10 ate distributions which are more robust to the inclusion of models with a large degree of 11 interdependency. This study uses a multivariate metric of present-day climatology to assess 12 both model performance and similarity in two recent model inter-comparisons, CMIP3 and 13 CMIP5. Model characteristics can be interpolated and then resampled in a space defined 14 by independent climate properties. A form of weighting can be applied by sampling more 15 densely in the region of the space close to the projected observations thus taking into account 16 both model performance and interdependence. 17