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The higher‐order turbulence scheme, Cloud Layers Unified by Binormals (CLUBB), is known for effectively simulating the transition from cumulus to stratocumulus clouds within leading atmospheric climate models. This study investigates an underexplored aspect of CLUBB: its capacity to simulate near‐surface winds and the Planetary Boundary Layer (PBL), with a particular focus on its coupling with surface momentum flux. Using the GFDL atmospheric climate model (AM4), we examine two distinct coupling strategies, distinguished by their handling of surface momentum flux during the CLUBB's stability‐driven substepping performed at each atmospheric time step. The static coupling maintains a constant surface momentum flux, while the dynamic coupling adjusts the surface momentum flux at each CLUBB substep based on the CLUBB‐computed zonal and meridional wind speed tendencies. Our 30‐year present‐day climate simulations (1980–2010) show that static coupling overestimates 10‐m wind speeds compared to both control AM4 simulations and reanalysis, particularly over the Southern Ocean (SO) and other midlatitude ocean regions. Conversely, dynamic coupling corrects the static coupling 10‐m winds biases in the midlatitude regions, resulting in CLUBB simulations achieving there an excellent agreement with AM4 simulations. Furthermore, analysis of PBL vertical profiles over the SO reveals that dynamic coupling reduces downward momentum transport, consistent with the found wind‐speed reductions. Instead, near the tropics, dynamic coupling results in minimal changes in near‐surface wind speeds and associated turbulent momentum transport structure. Notably, the wind turning angle serves as a valuable qualitative metric for assessing the impact of changes in surface momentum flux representation on global circulation patterns. 

Abstract We extend the locking technique to separate the poleward shift of the atmospheric circulation in response to quadrupled CO₂into contributions from (1) CO₂increase, (2) cloud radiative effects, and (3) wind and surface humidity‐induced surface heat exchange. In aquaplanet simulations, wind and surface humidity‐induced surface heat exchange accounts for 30–60% of the Hadley cell edge and midlatitude eddy‐driven jet shift. The increase of surface specific humidity dominates and mostly follows global mean warming. Consistent with previous work the remaining shift is attributed to cloud radiative effects. Across CMIP5 models the intermodel variance in the austral winter circulation shift in response to quadrupled CO₂is significantly correlated with the response of the subtropical‐subpolar difference of surface heat exchange. The results highlight the dominant role of surface heat exchange for future circulation changes. 

Abstract Advances in high‐performance computing have enabled large‐eddy simulations (LES) of turbulence, convection, and clouds. However, their potential to improve parameterizations in global climate models (GCMs) is only beginning to be harnessed, with relatively few canonical LES available so far. The purpose of this paper is to begin creating a public LES library that expands the training data available for calibrating and evaluating GCM parameterizations. To do so, we use an experimental setup in which LES are driven by large‐scale forcings from GCMs, which in principle can be used at any location, any time of year, and in any climate state. We use this setup to create a library of LES of clouds across the tropics and subtropics, in the present and in a warmer climate, with a focus on the transition from stratocumulus to shallow cumulus over the East Pacific. The LES results are relatively insensitive to the choice of host GCM driving the LES. Driven with large‐scale forcing under global warming, the LES simulate a positive but weak shortwave cloud feedback, adding to the accumulating evidence that low clouds amplify global warming. 

Abstract Climate models project tropical warming is amplified aloft relative to the surface in response to increased CO₂. Here we show moist adiabatic adjustment overpredicts the multimodel mean 300 hPa temperature response by 16.6–25.3% across the CMIP5 model hierarchy. We show three mechanisms influence overprediction: climatological large‐scale circulation, direct effect of increased CO₂, and convective entrainment. Accounting for the presence of a climatological large‐scale circulation and the direct effect of CO₂reduces the CMIP5 multimodel mean overprediction by 0.7–7.2% and 2.8–3.9%, respectively, but does not eliminate it. To quantify the influence of entrainment, we vary the Tokioka parameter in aquaplanet simulations. When entrainment is decreased by decreasing the Tokioka parameter from 0.1 to 0, overprediction decreases by 9.6% and 10.4% with and without a large‐scale circulation, respectively. The sensitivity of overprediction to climatological entrainment rate in the aquaplanet mostly follows the predictions of zero‐buoyancy bulk‐plume and spectral‐plume models.