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We describe the model performance of a new global coupled climate model configuration, CM4‐MG2. Beginning with the Geophysical Fluid Dynamics Laboratory's fourth‐generation physical climate model (CM4.0), we incorporate a two‐moment Morrison‐Gettelman bulk stratiform microphysics scheme with prognostic precipitation (MG2), and a mineral dust and temperature‐dependent cloud ice nucleation scheme. We then conduct and analyze a set of fully coupled atmosphere‐ocean‐land‐sea ice simulations, following Coupled Model Intercomparison Project Phase 6 protocols. CM4‐MG2 generally captures CM4.0's baseline simulation characteristics, but with several improvements, including better marine stratocumulus clouds off the west coasts of Africa and North and South America, a reduced bias toward "double" Intertropical Convergence Zones south of the equator, and a stronger Madden‐Julian Oscillation (MJO). Some degraded features are also identified, including excessive Arctic sea ice extent and a stronger‐than‐observed El Nin∼ $\tilde{\mathrm{n}}$o‐Southern Oscillation. Compared to CM4.0, the climate sensitivity is reduced by about 10% in CM4‐MG2. Plain Language Summary: A sophisticated cloud microphysical scheme, along with a mineral dust and temperature‐dependent ice nucleation scheme, have been implemented in a new configuration of the Geophysical Fluid Dynamics Laboratory's most recent climate model (CM4.0). This microphysical scheme predicts both mass and number concentrations of cloud drops, ice crystals, rain, and snow, and treats aerosol‐cloud interactions more consistently. The ice nucleation on mineral dust aerosol in large‐scale clouds is represented more realistically. Centennial‐scale global coupled atmosphere‐ocean‐land‐sea ice simulations from this new configuration compare favorably with observations—with improved subtropical stratocumulus clouds and better tropical intraseasonal variability (i.e., the 30‐ to 90‐day Madden‐Julian Oscillation). The new configuration also reduces the magnitude of future global warming in response to anthropogenic emissions. Key Points: The performance of two‐moment microphysics with prognostic precipitation and an ice nucleation scheme in CM4.0: CM4‐MG2, is documentedThe overall performance of CM4‐MG2 is comparable to or better than CM4.0, based on a set of Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima and historical simulationsNotable improvements include enhanced coastal stratocumulus and a stronger Madden‐Julian Oscillation. CM4‐MG2 has a lower climate sensitivity than CM4.0 [ABSTRACT FROM AUTHOR]

The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July-August-September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications for highly vulnerable nations in the region. [ABSTRACT FROM AUTHOR]