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Abstract

Earth System Models (ESMs) are a key tool for studying the climate under changing conditions. Over recent decades, it has been established to not only rely on projections of a single model but to combine various ESMs in multi-model ensembles (MMEs) to improve robustness and quantify the uncertainty of the projections. The data access for MME studies has been fundamentally facilitated by the World Climate Research Programme's Coupled Model Intercomparison Project (CMIP) – a collaborative effort bringing together ESMs from modelling communities all over the world. Despite the CMIP standardization processes, addressing specific research questions using MMEs requires unique ensemble design, analysis, and interpretation choices. Based on the collective expertise within the Fresh Eyes on CMIP initiative, mainly composed of early-career researchers engaged in CMIP, we have identified common issues and questions encountered while working with climate MMEs. Here, we provide a comprehensive literature review addressing these questions. We provide statistics tracing the development of the climate MMEs analysis field throughout the last decades, and, synthesizing existing studies, we outline guidelines regarding model evaluation, model dependence, weighting methods, and uncertainty treatment. We summarize a collection of useful resources for MME studies, we review common questions and strategies, and finally, we outline emerging scientific trends, such as the integration of machine learning (ML) techniques, single model initial-condition large ensembles (SMILEs), and computational resource considerations. We thereby aim to support researchers working with climate MMEs, particularly in the upcoming 7th phase of CMIP.