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Abstract Wave breaking induced bubbles contribute a significant part of air‐sea gas fluxes. Recent modeling of the sea state dependent CO₂flux found that bubbles contribute up to ∼40% of the total CO₂air‐sea fluxes (Reichl & Deike, 2020,https://doi.org/10.1029/2020gl087267). In this study, we implement the sea state dependent bubble gas transfer formulation of Deike and Melville (2018,https://doi.org/10.1029/2018gl078758) into a spectral wave model (WAVEWATCH III) incorporating the spectral modeling of the wave breaking distribution from Romero (2019,https://doi.org/10.1029/2019gl083408). We evaluate the accuracy of the sea state dependent gas transfer parameterization against available measurements of CO₂gas transfer velocity from 9 data sets (11 research cruises, see Yang et al. (2022,https://doi.org/10.3389/fmars.2022.826421)). The sea state dependent parameterization for CO₂gas transfer velocity is consistent with observations, while the traditional wind‐only parameterization used in most global models slightly underestimates the observations of gas transfer velocity. We produce a climatology of the sea state dependent gas transfer velocity using reanalysis wind and wave data spanning 1980–2017. The climatology shows that the enhanced gas transfer velocity occurs frequently in regions with developed sea states (with strong wave breaking and high significant wave height). The present study provides a general sea state dependent parameterization for gas transfer, which can be implemented in global coupled models. 

Abstract This paper is Part II of a two‐part paper that documents the Climate Model version 4X (CM4X) hierarchy of coupled climate models developed at the Geophysical Fluid Dynamics Laboratory. Part I of this paper is presented in Griffies et al. (2025a,https://doi.org/10.1029/2024MS004861). Here we present a suite of case studies that examine ocean and sea ice features that are targeted for further research, which include sea level, eastern boundary upwelling, Arctic and Southern Ocean sea ice, Southern Ocean circulation, and North Atlantic circulation. The case studies are based on experiments that follow the protocol of version 6 from the Coupled Model Intercomparison Project. The analysis reveals a systematic improvement in the simulation fidelity of CM4X relative to its CM4.0 predecessor, as well as an improvement when refining the ocean/sea ice horizontal grid spacing from the of CM4X‐p25 to the of CM4X‐p125. Even so, there remain many outstanding biases, thus pointing to the need for further grid refinements, enhancements to numerical methods, and/or advances in parameterizations, each of which target long‐standing model biases and limitations. 

Abstract We present the GFDL‐CM4X (Geophysical Fluid Dynamics Laboratory Climate Model version 4X) coupled climate model hierarchy. The primary application for CM4X is to investigate ocean and sea ice physics as part of a realistic coupled Earth climate model. CM4X utilizes an updated MOM6 (Modular Ocean Model version 6) ocean physics package relative to CM4.0, and there are two members of the hierarchy: one that uses a horizontal grid spacing of (referred to as CM4X‐p25) and the other that uses a grid (CM4X‐p125). CM4X also refines its atmospheric grid from the nominally 100 km (cubed sphere C96) of CM4.0–50 km (C192). Finally, CM4X simplifies the land model to allow for a more focused study of the role of ocean changes to global mean climate. CM4X‐p125 reaches a global ocean area mean heat flux imbalance of within years in a pre‐industrial simulation, and retains that thermally equilibrated state over the subsequent centuries. This 1850 thermal equilibrium is characterized by roughly less ocean heat than present‐day, which corresponds to estimates for anthropogenic ocean heat uptake between 1870 and present‐day. CM4X‐p25 approaches its thermal equilibrium only after more than 1000 years, at which time its ocean has roughlymoreheat than its early 21st century ocean initial state. Furthermore, the root‐mean‐square sea surface temperature bias for historical simulations is roughly 20% smaller in CM4X‐p125 relative to CM4X‐p25 (and CM4.0). We offer themesoscale dominance hypothesisfor why CM4X‐p125 shows such favorable thermal equilibration properties. 

Abstract The drag coefficient under tropical cyclones and its dependence on sea states are investigated by combining upper-ocean current observations [using electromagnetic autonomous profiling explorer (EM-APEX) floats deployed under five tropical cyclones] and a coupled ocean–wave (Modular Ocean Model 6–WAVEWATCH III) model. The estimated drag coefficient averaged over all storms is around 2–3 × 10⁻³for wind speeds of 25–55 m s⁻¹. While the drag coefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is significantly reduced when the misalignment angle between the dominant wave direction and the wind direction exceeds about 45°, a feature that is underestimated by current models of sea state–dependent drag coefficient. Since the misaligned swell is more common in the far front and in the left-front quadrant of the storm (in the Northern Hemisphere), the drag coefficient also tends to be lower in these areas and shows a distinct spatial distribution. Our results therefore support ongoing efforts to develop and implement sea state–dependent parameterizations of the drag coefficient in tropical cyclone conditions. 

This study utilizes a large-eddy simulation (LES) approach to systematically assess the directional variability of wave-driven Langmuir turbulence (LT) in the ocean surface boundary layer (OSBL) under tropical cyclones (TCs). The Stokes drift vector, which drives LT through the Craik–Leibovich vortex force, is obtained through spectral wave simulations. LT’s direction is identified by horizontally elongated turbulent structures and objectively determined from horizontal autocorrelations of vertical velocities. In spite of a TC’s complex forcing with great wind and wave misalignments, this study finds that LT is approximately aligned with the wind. This is because the Reynolds stress and the depth-averaged Lagrangian shear (Eulerian plus Stokes drift shear) that are key in determining the LT intensity (determined by normalized depth-averaged vertical velocity variances) and direction are also approximately aligned with the wind relatively close to the surface. A scaling analysis of the momentum budget suggests that the Reynolds stress is approximately constant over a near-surface layer with predominant production of turbulent kinetic energy by Stokes drift shear, which is confirmed from the LES results. In this layer, Stokes drift shear, which dominates the Lagrangian shear, is aligned with the wind because of relatively short, wind-driven waves. On the contrary, Stokes drift exhibits considerable amount of misalignments with the wind. This wind–wave misalignment reduces LT intensity, consistent with a simple turbulent kinetic energy model. Our analysis shows that both the Reynolds stress and LT are aligned with the wind for different reasons: the former is dictated by the momentum budget, while the latter is controlled by wind-forced waves.