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.

A formal approach is presented to couple small-scale processes associated with atmospheric moist convection with the large-scale dynamics. The approach involves applying a two-dimensional cloud-resolving model in each column of a three-dimensional large-scale model. In the spirit of classical convection parameterization, which assumes scale separation between convection and the large-scale flow, the cloud-resolving models from neighboring columns interact only through the large-scale dynamics. This approach is referred to as Cloud-Resolving Convection Parameterization (CRCP). In short, CRCP involves many two-dimensional cloud-resolving models interacting in a manner consistent with the large-scale dynamics. The approach is first applied to the idealized problem of a convective-radiative equilibrium of a two-dimensional nonrotating atmosphere in the presence of SST gradients. This simple dynamical setup allows comparison of CRCP simulations with the cloud-resolving model results. In these tests, the large-scale model has various horizontal grid spacings, from 20 to 500 km, and the CRCP domains change correspondingly. Comparison between CRCP and cloud-resolving simulations shows that the large-scale features, such as the mean temperature and moisture profiles and the large-scale flow, are reasonably well represented in CRCP simulations. However, the interaction between ascending and descending branches through the gravity wave mechanism, as well as organization of convection into mesoscale convective systems, are poorly captured. These results illustrate the limitations of not only CRCP, but also convection parameterization in general. The CRCP approach is also applied to the idealized problem of a rotating constant-SST aquaplanet in convective-radiative equilibrium. The global CRCP simulation features pronounced large-scale organization of convection within the equatorial waveguide. A prominent solitary equatorial ''super cloud cluster'' develops toward the end of the 80-day long simulation, which bears a strong resemblance to the Madden-Julian oscillation observed in the terrestrial Tropics.

Motivated by the need to resolve the condensation-coalescence bottleneck in warm rain formation, a significant number of studies have emerged in the past 15 years concerning the growth of cloud droplets by water-vapor diffusion and by collision-coalescence in a turbulent environment. With regard to condensation, recent studies suggest that small-scale turbulence alone does not produce a significant broadening of the cloud-droplet spectrum because of the smearing of droplet-scale fluctuations by rapid turbulent and gravitational mixing. However, different diffusional-growth histories associated with large-eddy hopping could lead to a significant spectral broadening. In contrast, small-scale turbulence in cumulus clouds makes a significant contribution to the collision-coalescence of droplets, enhancing the collection kernel up to a factor of 5, especially for droplet pairs with a low gravitational collision rate. This moderate level of enhancement has a significant impact on warm rain initiation. The multiscale nature of turbulent cloud microphysical processes and open research issues are delineated throughout. 293Annu. Rev. Fluid Mech. 2013.45:293-324. Downloaded from www.annualreviews.org by University of Delaware on 02/13/13. For personal use only.

In this survey we consider the impact of turbulence on cloud formation from the cloud scale to the droplet scale. We assess progress in understanding the effect of turbulence on the condensational and collisional growth of droplets and the effect of entrainment and mixing on the droplet spectrum. The increasing power of computers and better experimental and observational techniques allow for a much more detailed study of these processes than was hitherto possible. However, much of the research necessarily remains idealized and we argue that it is those studies which include such fundamental characteristics of clouds as droplet sedimentation and latent heating that are most relevant to clouds. Nevertheless, the large body of research over the last decade is beginning to allow tentative conclusions to be made. For example, it is unlikely that small-scale turbulent eddies (i.e. not the energy-containing eddies) alone are responsible for broadening the droplet size spectrum during the initial stage of droplet growth due to condensation. It is likely, though, that small-scale turbulence plays a significant role in the growth of droplets through collisions and coalescence. Moreover, it has been possible through detailed numerical simulations to assess the relative importance of different processes to the turbulent collision kernel and how this varies in the parameter space that is important to clouds. The focus of research on the role of turbulence in condensational and collisional growth has tended to ignore the effect of entrainment and mixing and it is arguable that they play at least as important a role in the evolution of the droplet spectrum. We consider the role of turbulence in the mixing of dry and cloudy air, methods of quantifying this mixing and the effect that it has on the droplet spectrum. Copyright

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SUMMARYAn idealized case-study has been designed to investigate the modelling of the diurnal cycle of deep precipitating convection over land. A simulation of this case was performed by seven single-column models (SCMs) and three cloud-resolving models (CRMs). Within this framework, a quick onset of convective rainfall is found in most SCMs, consistent with the results from general-circulation models. In contrast, CRMs do not predict rainfall before noon. A joint analysis of the results provided by both types of model indicates that convection occurs too early in most SCMs, due to crude triggering criteria and quick onsets of convective precipitation. In the CRMs, the first clouds appear before noon, but surface rainfall is delayed by a few hours to several hours. This intermediate stage, missing in all SCMs except for one, is characterized by a gradual moistening of the free troposphere and an increase of cloud-top height. Later on, convective downdraughts efficiently cool and dry the boundary layer (BL) in the CRMs. This feature is also absent in most SCMs, which tend to adjust towards more unstable states, with moister (and often more cloudy) low levels and a drier free atmosphere. This common behaviour of most SCMs with respect to deep moist convective processes occurs even though each SCM simulates a different diurnal cycle of the BL and atmospheric stability. The scatter among the SCMs results from the wide variety of representations of BL turbulence and moist convection in these models. Greater consistency is found among the CRMs, despite some differences in their representation of the daytime BL growth, which are linked to their parametrizations of BL turbulence and/or resolution.

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SUMMARYThis paper investigates daytime convective development over land and its representation in single-column models (SCMs) and cloud-resolving models (CRMs). A model intercomparison case is developed based on observations of the diurnal cycle and convection during the rainy season in Amazonia. The focus is on the 6 h period between sunrise and early afternoon which was identified in previous studies as critical for the diurnal cycle over summertime continents in numerical weather prediction and climate models. This period is characterized by the formation and growth of a well-mixed convective boundary layer from the early morning temperature and moisture profiles as the surface sensible-and latent-heat fluxes increase after sunrise. It proceeds with the formation of shallow convective clouds as the convective boundary layer deepens, and leads to the eventual transition from shallow to deep precipitating convection around local noon. To provide a benchmark for other models, a custom-designed set of simulations, applying increasing in time computational domain and decreasing spatial resolution, was executed. The SCMs reproduced the previously identified problem with premature development of deep convection, less than two hours after sunrise. The benchmark simulations suggest a possible route to improve SCMs by considering a time-evolving cumulus entrainment rate as convection evolves from shallow to deep and the cloud width increases up to an order of magnitude. The CRMs featuring horizontal grid length around 500 m are capable of capturing the qualitative aspects of the benchmark simulations, but there are significant differences among the models. Two-dimensional CRMs tend to simulate too rapid a transition from shallow to deep convection and too high a cloud cover.