biostudies-literatureMendlik TAustrian Science Fund FWF381-393https://www.ebi.ac.uk/biostudies/studies/S-EPMC4922546biostudies-literatureUnknown135In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input foClimatic changeSelecting climate simulations for impact studies based on multivariate patterns of climate change.PMC4922546I 1295-N29I 1295Mendlik TGobiet AfalseSelecting climate simulations for impact studies based on multivariate patterns of climate change.In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input fo2016-01-01T00:00:00Z20162025-04-04T14:05:52.925Z2019-03-27T02:17:01ZS-EPMC49225462742949910.1007/s10584-015-1582-0