The Max Planck Institute Grand Ensemble (MPI-GE) is the largest ensemble of a single comprehensive climate model currently available, with 100 members for the historical simulations and four forcing scenarios. It is currently the only large ensemble available that includes scenario representative concentration pathway (RCP) 2.6 and a 1% CO 2 scenario. These advantages make MPI-GE a powerful tool. We present an overview of MPI-GE, its components, and detail the experiments completed. We demonstrate how to separate the forced response from internal variability in a large ensemble. This separation allows the quantification of both the forced signal under climate change and the internal variability to unprecedented precision. We then demonstrate multiple ways to evaluate MPI-GE and put observations in the context of a large ensemble, including a novel approach for comparing model internal variability with estimated observed variability. Finally, we present four novel analyses, which can only be completed using a large ensemble. First, we address whether temperature and precipitation have a pathway dependence using the forcing scenarios. Second, the forced signal of the highly noisy atmospheric circulation is computed, and different drivers are identified to be important for the North Pacific and North Atlantic regions. Third, we use the ensemble dimension to investigate the time dependency of Atlantic Meridional Overturning Circulation variability changes under global warming. Last, sea level pressure is used as an example to demonstrate how MPI-GE can be utilized to estimate the ensemble size needed for a given scientific problem and provide insights for future ensemble projects.Large-ensemble projects of comprehensive coupled climate models are gaining traction as methods to robustly estimate internal variability in transient simulations and to quantify the forced signal (e.g., Kay

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together with an initialization procedure and a model evaluation system. This paper 31 summarizes the lessons learned from MiKlip so far; some are purely scientific, others concern 32 strategies and structures of research that targets future operational use. 33Three prediction-system generations have been constructed, characterized by 34 alternative initialization strategies; the later generations show a marked improvement in 35 hindcast skill for surface temperature. Hindcast skill is also identified for multi-year-mean 36European summer surface temperatures, extra-tropical cyclone tracks, the Quasi-Biennial 37Oscillation, and ocean carbon uptake, among others. Regionalization maintains or slightly 38 enhances the skill in European surface temperature inherited from the global model and also 39 displays hindcast skill for wind-energy output. A new volcano code package permits rapid 40 modification of the predictions in response to a future eruption. 41MiKlip has demonstrated the efficacy of subjecting a single global prediction system 42 to a major research effort. The benefits of this strategy include the rapid cycling through the 43 prediction-system generations, the development of a sophisticated evaluation package usable 44 by all MiKlip researchers, and regional applications of the global predictions. Open research 45 questions include the optimal balance between model resolution and ensemble size, the 46 appropriate method for constructing a prediction ensemble, and the decision between full-47 field and anomaly initialization. 48

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