The spatial organization of deep moist convection in radiative-convective equilibrium over a constant sea surface temperature is studied. A 100-day simulation is performed with a three-dimensional cloud-resolving model over a (576 km) 2 domain with no ambient rotation and no mean wind. The convection self-aggregates within 10 days into quasi-stationary mesoscale patches of dry, subsiding and moist, rainy air columns. The patches ultimately merge into a single intensely convecting moist patch surrounded by a broad region of very dry subsiding air.The self-aggregation is analyzed as an instability of a horizontally homogeneous convecting atmosphere driven by convection-water vapor-radiation feedbacks that systematically dry the drier air columns and moisten the moister air columns. Column-integrated heat, water, and moist static energy budgets over (72 km) 2 horizontal blocks show that this instability is primarily initiated by the reduced radiative cooling of air columns in which there is extensive anvil cirrus, augmented by enhanced surface latent and sensible heat fluxes under convectively active regions due to storm-induced gustiness. Mesoscale circulations intensify the later stages of self-aggregation by fluxing moist static energy from the dry to the moist regions. A simple mathematical model of the initial phase of self-aggregation is proposed based on the simulations.In accordance with this model, the self-aggregation can be suppressed by horizontally homogenizing the radiative cooling or surface fluxes. Lower-tropospheric wind shear leads to slightly slower and less pronounced self-aggregation into bands aligned along the shear vector. Self-aggregation is sensitive to the ice microphysical parameterization, which affects the location and extent of cirrus clouds and their radiative forcing. Self-aggregation is also sensitive to ambient Coriolis parameter f, and can induce spontaneous tropical cyclogenesis for large f. Inclusion of an interactive mixed-layer ocean slows but does not prevent self-aggregation.

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This paper reports an intercomparison study on undisturbed trade wind cumulus convection under steadystate conditions as observed during the Barbados Oceanographic and Meteorological Experiment (BOMEX) with 10 large eddy simulation (LES) models. A main objective of this study is to obtain a quantitative assessment of the quality of the turbulent dynamics for this type of boundary layer clouds as produced by the different LES codes. A 6-h simulation shows excellent model-to-model agreement of the observed vertical thermodynamical structure, reasonable agreement of variances and turbulent fluxes, and good agreement of quantities conditionally sampled within the model clouds, such as cloud cover, liquid water, and cloud updraft strength. In the second part of this paper the LES dataset is used to evaluate simple models that are used in parameterizations of current general circulation models (GCMs). Finally, the relation of this work to subsequent LES studies of more complicated regimes is discussed, and guidance is given for the design of future observational studies of shallow cumulus boundary layers.

Data from the first research flight (RF01) of the second Dynamics and Chemistry of Marine Stratocumulus (DYCOMS-II) field study are used to evaluate the fidelity with which large-eddy simulations (LESs) can represent the turbulent structure of stratocumulus-topped boundary layers. The initial data and forcings for this case placed it in an interesting part of parameter space, near the boundary where cloud-top mixing is thought to render the cloud layer unstable on the one hand, or tending toward a decoupled structure on the other hand. The basis of this evaluation consists of sixteen 4-h simulations from 10 modeling centers over grids whose vertical spacing was 5 m at the cloud-top interface and whose horizontal spacing was 35 m. Extensive sensitivity studies of both the configuration of the case and the numerical setup also enhanced the analysis. Overall it was found that (i) if efforts are made to reduce spurious mixing at cloud top, either by refining the vertical grid or limiting the effects of the subgrid model in this region, then the observed turbulent and thermodynamic structure of the layer can be reproduced with some fidelity; (ii) the base, or native configuration of most simulations greatly overestimated mixing at cloud top, tending toward a decoupled layer in which cloud liquid water path and turbulent intensities were grossly underestimated; (iii) the sensitivity of the simulations to the representation of mixing at cloud top is, to a certain extent, amplified by particulars of this case. Overall the results suggest that the use of LESs to map out the behavior of the stratocumulus-topped boundary layer in this interesting region of parameter space requires a more compelling representation of processes at cloud top. In the absence of significant leaps in the understanding of subgrid-scale (SGS) physics, such a representation can only be achieved by a significant refinement in resolution-a refinement that, while conceivable given existing resources, is probably still beyond the reach of most centers.

A new three-dimensional cloud resolving model (CRM) has been developed to study the statistical properties of cumulus convection. The model was applied to simulate a 28-day evolution of clouds over the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains site during the summer 1997 Intensive Observation Period. The model was forced by the large-scale advective tendencies and surface fluxes derived from the observations. The sensitivity of the results to the domain dimensionality and size, horizontal grid resolution, and parameterization of microphysics has been tested. In addition, the sensitivity to perturbed initial conditions has also been tested using a 20-member ensemble of runs. The model captures rather well the observed temporal evolution of the precipitable water and precipitation rate, although it severely underestimates the shaded cloud fraction possibly because of an inability to account for the lateral advection of clouds over the ARM site. The ensemble runs reveal that the uncertainty of the simulated precipitable water due to the fundamental uncertainty of the initial conditions can be as large as 25% of the mean values. Even though the precipitation rates averaged over the whole simulation period were virtually identical among the ensemble members, the timing uncertainty of the onset and reaching the precipitation maximum can be as long as one full day. Despite the predictability limitations, the mean simulation statistics are found to be almost insensitive to the uncertainty of the initial conditions. The overall effects of the third spatial dimension are found to be minor for simulated mean fields and scalar fluxes but are quite considerable for velocity and scalar variances. Neither changes in a rather wide range of the domain size nor the horizontal grid resolution have any significant impact on the simulations. Although a rather strong sensitivity of the mean hydrometeor profiles and, consequently, cloud fraction to the microphysics parameters is found, the effects on the predicted mean temperature and humidity profiles are shown to be modest. It is found that the spread among the time series of the simulated cloud fraction, precipitable water, and surface precipitation rate due to changes in the microphysics parameters is within the uncertainty of the ensemble runs. This suggests that correlation of the CRM simulations to the observed long time series of the aforementioned parameters cannot be generally used to validate the microphysics scheme.

Abstract. Results are presented from the first intercomparison of Large-eddy simulation (LES) models for the stable boundary layer (SBL), as part of the GABLS (Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study) initiative. A moderately stable case is used, based on Arctic observations. All models produce successful simulations, inasmuch as they reflect many of the results from local scaling theory and observations. Simulations performed at 1 m and 2 m resolution show only small changes in the mean profiles compared to coarser resolutions. Also, sensitivity to sub-grid models for individual models highlights their importance in SBL simulation at moderate resolution (6.25 m). Stability functions are derived from the LES using typical mixing lengths used in Numerical Weather Prediction (NWP) and climate models. The functions have smaller values than those used in NWP. There is also support for the use of K-profile similarity in parametrizations. Thus, the results provide improved understanding and motivate future developments of the parametrization of the SBL.

Progress on the cloud parameterization problem has been too slow. The authors advocate a new approach that is very promising but also very expensive computationally.

Traditionally, the effects of clouds in GCMs have been represented by semiempirical parameterizations. Recently, a cloud-resolving model (CRM) was embedded into each grid column of a realistic GCM, the NCAR Community Atmosphere Model (CAM), to serve as a superparameterization (SP) of clouds. Results of the standard CAM and the SP-CAM are contrasted, both using T42 resolution (2.8° × 2.8° grid), 26 vertical levels, and up to a 500-day-long simulation. The SP was based on a two-dimensional (2D) CRM with 64 grid columns and 24 levels collocated with the 24 lowest levels of CAM. In terms of the mean state, the SP-CAM produces quite reasonable geographical distributions of precipitation, precipitable water, top-of-the-atmosphere radiative fluxes, cloud radiative forcing, and high-cloud fraction for both December–January–February and June–July–August. The most notable and persistent precipitation bias in the western Pacific, during the Northern Hemisphere summer of all the SP-CAM runs with 2D SP, seems to go away through the use of a small-domain three-dimensional (3D) SP with the same number of grid columns as the 2D SP, but arranged in an 8 × 8 square with identical horizontal resolution of 4 km. Two runs with the 3D SP have been carried out, with and without explicit large-scale momentum transport by convection. Interestingly, the double ITCZ feature seems to go away in the run that includes momentum transport. The SP improves the diurnal variability of nondrizzle precipitation frequency over the standard model by precipitating most frequently during late afternoon hours over the land, as observed, while the standard model maximizes its precipitation frequency around local solar noon. Over the ocean, both models precipitate most frequently in the early morning hours as observed. The SP model also reproduces the observed global distribution of the percentage of days with nondrizzle precipitation rather well. In contrast, the standard model tends to precipitate more frequently, on average by about 20%–30%. The SP model seems to improve the convective intraseasonal variability over the standard model. Preliminary results suggest that the SP produces more realistic variability of such fields as 200-mb wind and OLR, relative to the control, including the often poorly simulated Madden–Julian oscillation (MJO).