*Result*: Coupled Climate Simulations With E3SM‐MMF.

*Simulations of the recent historical period from 1950 to 2014 are conducted with E3SM‐MMF, which uses an embedded 2D cloud resolving model that runs efficiently on GPUs in place of traditional parameterizations for cloud and turbulence. Analysis of the climate and variability reveal several aspects where E3SM‐MMF produces smaller biases compared to E3SMv2, including better agreement with the observed evolution of global mean surface temperature, although the representation of ENSO is too weak and fast. Three idealized abrupt CO2 experiments were also conducted to assess climate sensitivity and feedbacks. These yield three estimates of effective climate sensitivity (4.38, 5.21, and 6.06 K), with a corresponding spread in the shortwave cloud feedbacks. These estimates are on the higher end of sensitivity estimates from CMIP ensembles, and the spread indicates substantial state‐dependent feedbacks. These results demonstrate how multiscale modeling framework (MMF) models can be used for climate relevant experiments and projections by leveraging modern GPU enabled computational platforms. The unique qualities of E3SM‐MMF shown in previous literature are largely still present, but various instances of reduced biases suggest that MMF models have utility in improving future projections. Plain Language Summary: One of the largest source of uncertainty in climate projections comes from clouds, which are often represented with relatively crude parameterizations that fail to capture the rich complexity and scale interactions in the real atmosphere. The multiscale modeling framework (MMF) was designed to address the need for a model that could be used for climate scale experiments while explicitly representing clouds in a computationally efficient way. Here we present results from an Earth system model that uses this approach, along with active ocean and sea‐ice components to simulate the recent historical period and assess the biases relative to its traditionally parameterized counterpart. Many biases are improved with the MMF despite significantly less effort spent on tuning uncertain parameters, but there are also some aspects of the variability that are worse. Additional simulations with varying levels of CO2 are used to calculate effective climate sensitivity, which is higher than most traditional models. Key Points: E3SM‐MMF performs well over the historical period of 1950–2014 with active ocean and sea‐ice components despite minimal tuningThe representation of ENSO variability is generally too weak and too fast compared to both E3SMv2 and observationsAbrupt CO2 experiments yield a wide range of effective climate sensitivity (4.38–6.06 K) indicating substantial state‐dependent feedbacks [ABSTRACT FROM AUTHOR]

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