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This paper describes climate simulations of the Community Atmosphere Model, version 5 (CAM5), coupled with a higher-order turbulence closure known as Cloud Layers Unified by Binormals (CLUBB). CLUBB is a unified parameterization of the planetary boundary layer (PBL) and shallow convection that is centered around a trivariate probability density function (PDF) and replaces the conventional PBL, shallow convection, and cloud macrophysics schemes in CAM5. CAM–CLUBB improves many aspects of the base state climate compared to CAM5. Chief among them is the transition of stratocumulus to trade wind cumulus regions in the subtropical oceans. In these regions, CAM–CLUBB provides a much more gradual transition that is in better agreement with observational analysis compared to CAM5, which is too abrupt. The improvement seen in CAM–CLUBB can be largely attributed to the gradual evolution of the simulated turbulence, which is in part a result of the unified nature of the parameterization, and to the general improved representation of shallow cumulus clouds compared to CAM5. In addition, there are large differences in the representation and structure of marine boundary layer clouds between CAM–CLUBB and CAM5. CAM–CLUBB is also shown to be more robust, in terms of boundary layer clouds, to changes in vertical resolution for global simulations in a preliminary test.

In global atmospheric models, resolving stratocumulus (Sc) in the vertical is computationally expensive. However, Sc appear only under special meteorological conditions. Therefore, there is motivation to refine the vertical grid levels adaptively. In order to facilitate the possibility of parallelization on graphical processing units, our grid adaptation method prescribes the number of vertical levels a priori. Then grid levels are relocated toward altitude ranges in need of refinement. Because the method relocates existing grid levels, rather than adding extra levels, there is a risk of creating regions with overly coarse grid spacing, that is, voids in the grid mesh. To prevent such voids from forming, a simple method is developed to impose a maximum grid spacing. To decide where to place enhanced resolution, the authors develop an empirical mesh refinement criterion. It refines grid spacing near the ground, near strong temperature gradients, and within clouds. Our grid adaptation method is implemented in a single‐column model and evaluated on four test cases: decaying stratocumulus, developing shallow cumulus, a quasi‐stationary stratocumulus deck, and the diurnal cycle of a dry boundary layer. In the stratocumulus cases, mesh refinement leads to improvements in both the time evolution of fields and their time averages. The other two cases show smaller differences. Plain Language Summary Stratocumuli are thin, turbulent, overcast clouds. They contain fine‐scale vertical variations of length 10 m or less. In principle, a global atmospheric model could simulate such fine features by blanketing the globe with fine resolution, but such an approach is not affordable on today's supercomputers. However, stratocumulus clouds cover a relatively small portion of the globe, and other layers—for example, clear, non‐turbulent layers—do not require such fine grid spacing. Therefore, it is of interest to explore the possibility of moving grid levels away from layers without fine scales and toward layers with fine scales. The automatic movement of grid levels in the vertical brings up a number of questions, such as when it is worthwhile to move grid levels and where they should be moved. A simple method that addresses these questions is presented here. Key Points Adaptive mesh refinement is implemented in a single‐column model of clouds and turbulence Grid levels are relocated, not added, and a method is developed to enforce a maximum grid spacing A grid refinement criterion refines the grid near ground, in temperature gradients, and in cloud

The parameterization of subgrid‐scale processes such as boundary layer (PBL) turbulence introduces uncertainty in Earth System Model (ESM) results. This uncertainty can contribute to or exacerbate existing biases in representing key physical processes. This study analyzes the influence of tunable parameters in an experimental version of the Cloud Layers Unified by Binormals (CLUBBX) scheme. CLUBB is the operational PBL parameterization in the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community ESM version 2 (CESM2). We perform the Morris one‐at‐a‐time (MOAT) parameter sensitivity analysis using short‐term (3‐day), initialized hindcasts of CAM6‐CLUBBX with 24 unique initial conditions. Several input parameters modulating vertical momentum flux appear most influential for various regionally‐averaged quantities, namely surface stress and shortwave cloud forcing (SWCF). These parameter sensitivities have a spatial dependence, with parameters governing momentum flux most influential in regions of high vertical wind shear (e.g., the mid‐latitude storm tracks). We next evaluate several experimental 20‐year simulations of CAM6‐CLUBBX with targeted parameter perturbations. We find that parameter perturbations produce similar physical mechanisms in both short‐term and long‐term simulations, but these physical responses can be muted due to nonlinear feedbacks manifesting over time scales longer than 3 days, thus causing differences in how output metrics respond in the long‐term simulations. Analysis of turbulent fluxes in CLUBBX indicates that the influential parameters affect vertical fluxes of heat, moisture, and momentum, providing physical pathways for the sensitivities identified in this study. Plain Language Summary Models struggle with certain aspects of predicting the Earth's current and future climate. To achieve better predictions in the future, it is important to understand which parts of the model need to be improved. This study explores how changing certain model characteristics influences what the model outputs. We find that changing how the model estimates small‐scale motions in the atmosphere improves the model's accuracy. Furthermore, these changes affect both short‐term (several days) and long‐term (several decades) model simulations. The results of this study can help scientists understand the physical behavior of climate models and help inform future improvements to enhance model accuracy. Key Points A computationally‐efficient sensitivity analysis identifies key parameters and physical mechanisms for global climate properties Certain parameter sensitivities in short‐term, initialized hindcasts are consistent with those seen in multidecadal climate simulations Parameters governing the degree of turbulent mixing in the presence of vertical wind shear are influential for surface stress representation

One of the challenges in representing warm rain processes in global climate models (GCMs) is related to the representation of the subgrid variability of cloud properties, such as cloud water and cloud droplet number concentration (CDNC), and the effect thereof on individual precipitation processes such as autoconversion. This effect is conventionally treated by multiplying the resolved-scale warm rain process rates by an enhancement factor (Eq) which is derived from integrating over an assumed subgrid cloud water distribution. The assumed subgrid cloud distribution remains highly uncertain. In this study, we derive the subgrid variations of liquid-phase cloud properties over the tropical ocean using the satellite remote sensing products from Moderate Resolution Imaging Spectroradiometer (MODIS) and investigate the corresponding enhancement factors for the GCM parameterization of autoconversion rate. We find that the conventional approach of using only subgrid variability of cloud water is insufficient and that the subgrid variability of CDNC, as well as the correlation between the two, is also important for correctly simulating the autoconversion process in GCMs. Using the MODIS data which have near-global data coverage, we find that Eq shows a strong dependence on cloud regimes due to the fact that the subgrid variability of cloud water and CDNC is regime dependent. Our analysis shows a significant increase of Eq from the stratocumulus (Sc) to cumulus (Cu) regions. Furthermore, the enhancement factor EN due to the subgrid variation of CDNC is derived from satellite observation for the first time, and results reveal several regions downwind of biomass burning aerosols (e.g., Gulf of Guinea, east coast of South Africa), air pollution (i.e., East China Sea), and active volcanos (e.g., Kilauea, Hawaii, and Ambae, Vanuatu), where the EN is comparable to or even larger than Eq, suggesting an important role of aerosol in influencing the EN. MODIS observations suggest that the subgrid variations of cloud liquid water path (LWP) and CDNC are generally positively correlated. As a result, the combined enhancement factor, including the effect of LWP and CDNC correlation, is significantly smaller than the simple product of Eq⋅EN. Given the importance of warm rain processes in understanding the Earth's system dynamics and water cycle, we conclude that more observational studies are needed to provide a better constraint on the warm rain processes in GCMs.

This study provides comprehensive insight into the notable differences in clouds and precipitation simulated by the Energy Exascale Earth System Model Atmosphere Model version 0 and version 1 (EAMv1). Several sensitivity experiments are conducted to isolate the impact of changes in model physics, resolution, and parameter choices on these differences. The overall improvement in EAMv1 clouds and precipitation is primarily attributed to the introduction of a simplified third‐order turbulence parameterization Cloud Layers Unified By Binormals (along with the companion changes) for a unified treatment of boundary layer turbulence, shallow convection, and cloud macrophysics, though it also leads to a reduction in subtropical coastal stratocumulus clouds. This lack of stratocumulus clouds is considerably improved by increasing vertical resolution from 30 to 72 layers, but the gain is unfortunately subsequently offset by other retuning to reach the top‐of‐atmosphere energy balance. Increasing vertical resolution also results in a considerable underestimation of high clouds over the tropical warm pool, primarily due to the selection for numerical stability of a higher air parcel launch level in the deep convection scheme. Increasing horizontal resolution from 1° to 0.25° without retuning leads to considerable degradation in cloud and precipitation fields, with much weaker tropical and subtropical short‐ and longwave cloud radiative forcing and much stronger precipitation in the intertropical convergence zone, indicating poor scale awareness of the cloud parameterizations. To avoid this degradation, significantly different parameter settings for the low‐resolution (1°) and high‐resolution (0.25°) were required to achieve optimal performance in EAMv1. Plain Language Summary The Energy Exascale Earth System Model (E3SM) is a new and ongoing U.S. Department of Energy (DOE) climate modeling effort to develop a high‐resolution Earth system model specifically targeting next‐generation DOE supercomputers to meet the science needs of the nation and the mission needs of DOE. The increase of model resolution along with improvements in representing cloud and convective processes in the E3SM atmosphere model version 1 has led to quite significant model behavior changes from its earlier version, particularly in simulated clouds and precipitation. To understand what causes the model behavior changes, this study conducts sensitivity experiments to isolate the impact of changes in model physics, resolution, and parameter choices on these changes. Results from these sensitivity tests and discussions on the underlying physical processes provide substantial insight into the model errors and guidance for future E3SM development. Key Points CLUBB along with the companion changes in EAMv1 primarily account for the overall improvements in clouds and precipitation simulation Underestimate of coastal Sc in EAMv1 is due to CLUBB and model tuning; increased vertical resolution partially offsets this degradation The poor scale awareness of EAMv1 requires retuning as resolution increases, which has a large impact on model cloud behavior

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. Plain Language Summary The Cloud Layers Unified by Binormals (CLUBB) scheme offers a promising way to model the complexities of cloud behavior, but its impact on winds and global circulation has been less explored. In our study, we investigate how different ways of representing the complex coupling between surface drag and the lowest kilometer of the Earth's atmosphere affect global wind speeds and circulation. We specifically examine two distinct approaches: a static approach, which feeds a constant surface drag to CLUBB, and a dynamic approach, which adjusts the surface drag based on the winds updates computed by CLUBB. Over a present‐day climate, we find that static coupling tends to produce excessively large wind speeds in certain regions, like the Southern Ocean and parts of the North Atlantic and North Pacific. Instead, dynamic coupling produces excellent near‐surface wind speeds in these regions, and also over the rest of the globe. Moreover, we discover that dynamic coupling reduces the downward turbulent transport of momentum, highlighting the enhancements in near‐surface wind speeds found with this approach are physically consistent. Lastly, we use the change in wind direction with height to qualitatively evaluate how the two coupling methods affect global circulation patterns. Key Points Dynamic coupling between Cloud Layers Unified by Binormals (CLUBB) and surface momentum flux enhances global winds climate simulations bringing CLUBB in line with control atmospheric climate model In midlatitude regions, the dynamic coupling enhances the boundary‐layer momentum transport compared to the static coupling The wind turning angle turns out a useful qualitative metric, linking changes in surface momentum flux to the changes in global circulation

It is challenging to parameterize subgrid vertical momentum fluxes in marine shallow cumulus layers that contain a jet in the profile of horizontal wind. In a large‐eddy simulation of such a layer, it is found that the momentum flux in the direction of strongest wind magnitude has a three‐layer structure. The lowest layer, from the ocean surface up to the jet maximum, has downgradient momentum flux. The middle layer, from the jet maximum up to an altitude several hundred meters above, has upgradient (i.e., countergradient) momentum flux because of transport of low‐magnitude momentum upward through the jet maximum. In the upper layer, the layer‐average momentum flux is weak. The budget of momentum flux shows that in the middle and upper layers, both the buoyancy production term and turbulent advection (i.e., third‐order flux‐of‐flux) terms are important. To parameterize the profile of momentum flux in a single‐column model, the momentum flux is prognosed in this study. The buoyancy production and flux‐of‐flux terms are parameterized by integrating them over a subgrid probability density function with an assumed normal‐mixture shape. The resulting parameterized fluxes and mean‐wind profiles are demonstrated to be comparable to those produced in large‐eddy simulations, both for two marine shallow cumulus cases with upgradient fluxes and for a continental cumulus case and two stratocumulus cases with downgradient fluxes. In the two marine shallow cumulus cases, the parameterization is able to capture the upgradient momentum flux above the jet maximum and the weak momentum fluxes aloft. Plain Language Summary A fine‐scale simulation of a shallow cumulus cloud layer has been performed, and it exhibits a three‐layer structure of turbulent momentum flux in the vertical. This structure is difficult to approximate in coarse‐resolution global atmospheric models, but a method for doing so is proposed and tested. Key Points A simulation of shallow cumuli exhibits three layers, with different behavior of momentum flux in each The middle layer exhibits upgradient momentum flux, and the upper layer has weak momentum flux This three‐layer structure is parameterized by a higher‐order model closed with an assumed PDF

We describe and analyze the results of the third global energy and water cycle experiment atmospheric boundary layer Study intercomparison and evaluation study for single-column models. Each of the nineteen participating models was operated with its own physics package, including land-surface, radiation and turbulent mixing schemes, for a full diurnal cycle selected from the Cabauw observatory archive. By carefully prescribing the temporal evolution of the forcings on the vertical column, the models could be evaluated against observations. We focus on the gross features of the stable boundary layer (SBL), such as the onset of evening momentum decoupling, the 2-m minimum temperature, the evolution of the inertial oscillation and the morning transition. New process diagrams are introduced to interpret the variety of model results and the relative importance of processes in the SBL; the diagrams include the results of a number of sensitivity runs performed with one of the models. The models are characterized in terms of thermal coupling to the soil, longwave radiation and turbulent mixing. It is shown that differences in longwave radiation schemes among the models have only a small effect on the simulations; however, there are significant variations in downward radiation due to different boundary-layer profiles of temperature and humidity. The differences in modelled thermal coupling to the land surface are large and explain most of the variations in 2-m air temperature and longwave incoming radiation among models. Models with strong turbulent mixing overestimate the boundary-layer height, underestimate the wind speed at 200 m, and give a relatively large downward sensible heat flux. The result is that 2-m air temperature is relatively insensitive to turbulent mixing intensity. Evening transition times spread 1.5 h around the observed time of transition, with later transitions for models with coarse resolution. Time of onset in the morning transition spreads 2 h around the observed transition time. With this case, the morning transition appeared to be difficult to study, no relation could be found between the studied processes, and the variation in the time of the morning transition among the models.

The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs.

It is difficult for coarse‐resolution global models of the atmosphere to accurately simulate the observed distribution of low clouds. In particular, it is difficult for moist turbulence closure models to simulate sufficiently bright near‐coastal stratocumulus (Sc) without simulating overly bright marine shallow cumuli (Cu). To parameterize bright Sc, a turbulence parameterization must damp the turbulent fluxes of heat and moisture above cloud top in order to prevent excessive entrainment of dry air into cloud top. To parameterize dim shallow Cu, the subgrid variances of temperature and moisture must remain large, in order to permit partial cloudiness. However, damping the fluxes but not the variances just above cloud top is difficult if a parameterization uses a single “master” time scale to damp both. In nature, the above‐cloud fluxes are damped by pressure fluctuations, whereas scalar variances are damped by a different process, namely, turbulent dissipation. In a stably stratified inversion above cloud, pressure damping is large but turbulent dissipation is small. To avoid this problem, a multitime scale parameterization for damping has been developed. The damping parameterization has been implemented in a global model and evaluated. The parameterization is capable of dimming shallow Cu while producing adequately bright Sc. Plain Language Summary This paper describes an assumption in turbulence modeling that is known to be questionable but is still sometimes made. To avoid making this assumption, the formulation of a particular turbulence model is generalized. The generalized formulation, when implemented in a global model of the atmosphere, changes the pattern of low‐altitude clouds. Key Points Some turbulence parameterizations use a single master turbulence length/time scale even though this assumption is an oversimplification This paper parameterizes turbulence by use of multiple turbulent time scales, including one for dissipation and another for pressure Use of the new multiscale parameterization in a global model significantly alters the distribution of stratocumulus and shallow cumulus clouds