biostudies-literatureThao SUniversity of LausanneEuropean Research CouncilJoint Programming Initiative Climate and European Union2345-2361https://www.ebi.ac.uk/biostudies/studies/S-EPMC9463255biostudies-literatureUnknown59(7-8)Global Climate Models are the main tools for climate projections. Since many models exist, it is common to use Multi-Model Ensembles to reduce biases and assess uncertainties in climate projections. Several approaches have been proposed to combine individual models and extract a robust signal from an ensemble. Among them, the Multi-Model Mean (MMM) is the most commonly used. Based on the assumption that the models are centered around the truth, it consists in averaging the ensemble, with the possibility of using equal weights for all models or to adjust weights to favor some models. In this paper, we propose a new alternative to reconstruct multi-decadal means of climate variables from a Multi-Model Ensemble, where the local performance of the models is taken into account. This is in contrClimate dynamicsCombining global climate models using graph cuts.PMC9463255338965Grant 690462Grant no.565338965-A2C2Garvik MMariethoz GThao SVrac MfalseCombining global climate models using graph cuts.Global Climate Models are the main tools for climate projections. Since many models exist, it is common to use Multi-Model Ensembles to reduce biases and assess uncertainties in climate projections. Several approaches have been proposed to combine individual models and extract a robust signal from an ensemble. Among them, the Multi-Model Mean (MMM) is the most commonly used. Based on the assumption that the models are centered around the truth, it consists in averaging the ensemble, with the possibility of using equal weights for all models or to adjust weights to favor some models. In this paper, we propose a new alternative to reconstruct multi-decadal means of climate variables from a Multi-Model Ensemble, where the local performance of the models is taken into account. This is in contr2022-01-01T00:00:00Z20222025-04-04T13:46:46.248Z2025-04-04T13:46:46.248ZS-EPMC94632553610167410.1007/s00382-022-06213-4