The current version of the Dutch Atmospheric Large-Eddy Simulation (DALES) is presented. DALES is a large-eddy simulation code designed for studies of the physics of the atmospheric boundary layer, including convective and stable boundary layers as well as cloudy boundary layers. In addition, DALES can be used for studies of more specific cases, such as flow over sloping or heterogeneous terrain, and dispersion of inert and chemically active species. This paper contains an extensive description of the physical and numerical formulation of the code, and gives an overview of its applications and accomplishments in recent years.

In this study large-eddy simulations (LES) are used to gain more knowledge on the shell of subsiding air that is frequently observed around cumulus clouds. First, a detailed comparison between observational and numerical results is presented to better validate LES as a tool for studies of microscale phenomena. It is found that horizontal cloud profiles of vertical velocity, humidity, and temperature are in good agreement with observations. They show features similar to the observations, including the presence of the shell of descending air around the cloud. Second, the availability of the complete 3D dataset in LES has been exploited to examine the role of lateral mixing in the exchange of cloud and environmental air. The origin of the subsiding shell is examined by analyzing the individual terms of the vertical momentum equation. Buoyancy is found to be the driving force for this shell, and it is counteracted by the pressure-gradient force. This shows that evaporative cooling at the cloud edge, induced by lateral mixing of cloudy and environmental air, is the responsible mechanism behind the descending shell. For all clouds, and especially the smaller ones, the negative mass flux generated by the subsiding shell is significant. This suggests an important role for lateral mixing throughout the entire cloud layer. The role of the shell in these processes is further explored and described in a conceptual three-layer model of the cloud.

Trade wind cumulus clouds often organize in along-wind cloud streets and across-wind mesoscale arcs. We present a benchmark large-eddy simulation which resolves the individual clouds as well as the mesoscale organization on scales of O(10 km). Different methods to quantify organization of cloud fields are applied and discussed. Using perturbed physics large-eddy simulation experiments, the processes leading to the formation of cloud clusters and the mesoscale arcs are revealed. We find that both cold pools as well as the sub-cloud layer moisture field are crucial to understand the organization of precipitating shallow convection. Further sensitivity studies show that microphysical assumptions can have a pronounced impact on the onset of cloud organization.

Subtropical marine low cloud sensitivity to an idealized climate change is compared in six large‐eddy simulation (LES) models as part of CGILS. July cloud cover is simulated at three locations over the subtropical northeast Pacific Ocean, which are typified by cold sea surface temperatures (SSTs) under well‐mixed stratocumulus, cool SSTs under decoupled stratocumulus, and shallow cumulus clouds overlying warmer SSTs. The idealized climate change includes a uniform 2 K SST increase with corresponding moist‐adiabatic warming aloft and subsidence changes, but no change in free‐tropospheric relative humidity, surface wind speed, or CO₂. For each case, realistic advective forcings and boundary conditions are generated for the control and perturbed states which each LES runs for 10 days into a quasi‐steady state. For the control climate, the LESs correctly produce the expected cloud type at all three locations. With the perturbed forcings, all models simulate boundary‐layer deepening due to reduced subsidence in the warmer climate, with less deepening at the warm‐SST location due to regulation by precipitation. The models do not show a consistent response of liquid water path and albedo in the perturbed climate, though the majority predict cloud thickening (negative cloud feedback) at the cold‐SST location and slight cloud thinning (positive cloud feedback) at the cool‐SST and warm‐SST locations. In perturbed climate simulations at the cold‐SST location without the subsidence decrease, cloud albedo consistently decreases across the models. Thus, boundary‐layer cloud feedback on climate change involves compensating thermodynamic and dynamic effects of warming and may interact with patterns of subsidence change.

CGILS—the CFMIP‐GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)—investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, cumulus under stratocumulus, and well‐mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus alone regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well‐mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: in a warmer climate, the moistening rate of the cloudy layer associated with the surface‐based turbulence parameterization is enhanced; together with weaker large‐scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as the “NESTS” negative cloud feedback and the “SCOPE” positive cloud feedback (Negative feedback from Surface Turbulence under weaker Subsidence—Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations.

This paper describes MicroHH 1.0, a new and open-source (www.microhh.org) computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is primarily made for direct numerical simulation but also supports large-eddy simulation (LES). The paper covers the description of the governing equations, their numerical implementation, and the parameterizations included in the code. Furthermore, the paper presents the validation of the dynamical core in the form of convergence and conservation tests, and comparison of simulations of channel flows and slope flows against well-established test cases. The full numerical model, including the associated parameterizations for LES, has been tested for a set of cases under stable and unstable conditions, under the Boussinesq and anelastic approximations, and with dry and moist convection under stationary and time-varying boundary conditions. The paper presents performance tests showing good scaling from 256 to 32 768 processes. The graphical processing unit (GPU)-enabled version of the code can reach a speedup of more than an order of magnitude for simulations that fit in the memory of a single GPU.