The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5°C) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatures. In this study, we examine the role of cloud parameterizations in simulating the LGM cooling in CESM2. Through substituting different versions of cloud schemes in the atmosphere model, we attribute the excessive LGM cooling to the new CESM2 schemes of cloud microphysics and ice nucleation. Further exploration suggests that removing an inappropriate limiter on cloud ice number (NoNimax) and decreasing the time‐step size (substepping) in cloud microphysics largely eliminate the excessive LGM cooling. NoNimax produces a more physically consistent treatment of mixed‐phase clouds, which leads to an increase in cloud ice content and a weaker shortwave cloud feedback over mid‐to‐high latitudes and the Southern Hemisphere subtropics. Microphysical substepping further weakens the shortwave cloud feedback. Based on NoNimax and microphysical substepping, we have developed a paleoclimate‐calibrated CESM2 (PaleoCalibr), which simulates well the observed twentieth century warming and spatial characteristics of key cloud and climate variables. PaleoCalibr has a lower ECS (∼4°C) and a 20% weaker aerosol‐cloud interaction than CESM2. PaleoCalibr represents a physically more consistent treatment of cloud microphysics than CESM2 and is a valuable tool in climate change studies, especially when a large climate forcing is involved. Our study highlights the unique value of paleoclimate constraints in informing the cloud parameterizations and ultimately the future climate projection.

Uncertainties in cloud and aerosol radiative effects are a principal contributor to climate model uncertainty, and remain so despite decades of model development (Boucher et al., 2013). These uncertainties arise from the difficulty of representing aerosol-cloud interactions and other key physical processes at the typical resolutions of global climate models (GCMs). Evaluations of available models from the Coupled Model Intercomparison Project Phase 6 (CMIP6; Eyring et al., 2016) indicate that changes in climate sensitivity relative to CMIP5 (Taylor et al., 2012) are mostly due to changes in cloud representation, specifically for extratropical low-level clouds (Zelinka et al., 2020). Using observations to reevaluate the representation of these clouds in the latest generation of GCMs is a vital part of testing the validity of these new predictions.In the Arctic, clouds mediate climate change through interactions with land and sea ice, and impacts on surface radiative fluxes (H. Morrison et al., 2012). As the thermodynamic phase of Arctic clouds shifts from ice to liquid in response to warming, the radiative effect they exert on the surface changes (Mitchell et al., 1989). This cloud phase feedback depends on cloud optical thickness and lifetime changes. In the Arctic, observations indicate that liquid and ice clouds exert very different radiative forcings on the surface

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