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Marine low clouds have a large impact on Earth's energy and hydrologic cycle. They strongly reflect incoming solar radiation, with little compensating impact on outgoing longwave radiation resulting in a [...]

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement Program and output from the University of California, Los Angeles/Colorado State University cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties analyzed by applying the SCM's assumptions about cloud vertical overlap and horizontal homogeneity to its profiles of cloud water/ice mixing ratio, cloud fraction, and snow flux differed from the cloud radar observations while the CRM simulation reproduced most of the observed cirrus properties. The present study evaluates, through a comparison with the CRM, the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. This study finds that, although the SCM's detrainment rate profile averaged over the entire simulation period is comparable to the CRM's, detrainment in the SCM is comparatively sporadic and vertically localized. Too much detrained ice is sublimated when first detrained. Snow formed from detrained cloud ice falls through too deep of a layer. These aspects of the SCM's parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM), and suggest several possible improvements for the SCM: 1) allowing multiple coexisting cumulus cloud types as in the original Arakawa-Schubert scheme, 2) prognostically determining the stratiform cloud fraction, and 3) explicitly predicting the snow mixing ratio. These would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow flux.

This study describes and demonstrates a new method for identifying deficiencies in how cloud processes are represented in large-scale models. Kilometer-scale-resolving cloud radar observations and cloud-resolving model (CRM) simulations were used to evaluate the representation of cirrus clouds in the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model for a 29-day period during June and July 1997 at the Atmospheric Radiation Measurement Program site in Oklahoma. To produce kilometer-scale cirrus statistics from the SCM results, synthetic subgrid-scale (SGS) cloud fields were generated using the SCM's cloud fraction and hydrometeor content profiles, and the SCM's cloud overlap and horizontal inhomogeneity assumptions. Three sets of SCM synthetic SGS cloud fields were analyzed. Two NOSNOW sets were produced in which clouds did not include snow; one set used random overlap, the other, maximum/random. In the SNOW set, clouds included snow and random overlap was used. The three sets were sampled in the same way as the cloud-radar-detected cloud fields and the CRM-simulated cloud fields. The mean cirrus cloud occurrence frequency for the SCM NOSNOW cloud fields agrees with the observed value as well as the CRM's does, while that for SCM SNOW cloud fields is only half that observed. In most aspects, the SCM's cirrus properties differ significantly from the cloud radar's and the CRM's, which generally agree. In comparison, there are too many physically thin SCM NOSNOW cirrus layers (most occupy only a single model layer) and too many physically thick SCM SNOW cirrus layers (most are thicker than 4 km). For the optically thin subset of cirrus layers, 1) the mean, mode, and median ice water path, and layer-mean ice water content (IWC) values for the SCM are significantly larger than the observed and CRM values; 2) the SCM layer-mean IWCs decrease with cloud physical thickness, opposite to the observations and CRM results; and 3) the range of layer-mean effective radii in the SCM thin cirrus is too narrow.

The Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was organized to promote the development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. GCSS uses models to analyze and understand observations of the behavior of cloud systems. Cloud-system-resolving models (CSRMs) have sufficient spatial and temporal resolution to represent individual cloud elements, but cover a wide enough range of time and space scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the column physics components of atmospheric general circulation models (GCMs). SCMs are used to test cloud parameterizations in an uncoupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data are collected in various field programs and provided to the CSRM community, which first uses the data to 'certify' the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM community. Results of a rethinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data, are reported on herein. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, an explicit recognition of the importance of data integration, and an increasing use of observed cloud-scale statistics for model evaluations.

Cloud radar data collected at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains site were used to evaluate the properties of cirrus clouds that occurred in a cloud-resolving model (CRM) simulation of the 29-day summer 1997 intensive observation period (IOP). The simulation was 'forced' by the large-scale advective temperature and water vapor tendencies, horizontal wind velocity, and turbulent surface fluxes observed at the Southern Great Plains site. The large-scale advective condensate tendency was not observed. The correlation of CRM cirrus amount with Geostationary Operational Environmental Satellite (GOES) high cloud amount was 0.70 for the subperiods during which cirrus formation and decay occurred primarily locally, but only 0.30 for the entire IOP. This suggests that neglecting condensate advection has a detrimental impact on the ability of a model (CRM or single-column model) to properly simulate cirrus cloud occurrence. The occurrence, vertical location, and thickness of cirrus cloud layers, as well as the bulk microphysical properties of thin cirrus cloud layers, were determined from the cloud radar measurements for June, July, and August 1997. The composite characteristics of cirrus clouds derived from this dataset are well suited for evaluating CRMs because of the close correspondence between the timescales and space scales resolved by the cloud radar measurements and by CRMs. The CRM results were sampled at eight grid columns spaced 64 km apart using the same definitions of cirrus and thin cirrus as the cloud radar dataset. The composite characteristics of cirrus clouds obtained from the CRM were then compared to those obtained from the cloud radar. Compared with the cloud radar observations, the CRM cirrus clouds occur at lower heights and with larger physical thicknesses. The ice water paths in the CRM's thin cirrus clouds are similar to those observed. However, the corresponding cloud-layer-mean ice water contents are significantly less than observed due to the CRM's larger cloud-layer thicknesses. The strong dependence of cirrus microphysical properties on layer-mean temperature and layer thickness as revealed by the observations is reproduced by the CRM. In addition, both the CRM and the observations show that the thin cirrus ice water path during large-scale ascent is only slightly greater than during no ascent or descent.

A model used to study entrainment and mixing of thermodynamic properties in the stratus-topped boundary layer has been extended to represent these processes in cumulus clouds. The new model, called the 'explicit mixing parcel model' (EMPM), depicts finescale internal structure of a rising thermal in a cumulus cloud using a ID domain. The EMPM links the conventional parcel model, which has no internal structure, and multidimensional cloud models, which resolve cloud-scale structure produced by large eddies. In the EMPM, the internal structure evolves as a consequence of a sequence of discrete entrainment events and an explicit representation of turbulent mixing based on Kerstein's linear eddy model. In this version of the EMPM, subgrid-scale (eddy) diffusion is found to be adequate for representing the effects of the smallest turbulent eddies. In addition, a simple parameterization is used to determine the local condensation or evaporation rates. If the grid size is reduced so that the Kolmogorov scale is resolved and a droplet growth model is incorporated, the EMPM can predict the local microphysical environments of individual cloud droplets. To evaluate its entrainment parameterization, the EMPM was used to predict the bulk properties of Hawaiian cumulus cloud main turrets observed by aircraft. All of the quantities required by the EMPM except for the entrained blob size were obtained from the observations. Profiles of in-cloud means and variances of thermodynamic properties calculated by the EMPM for entrained blob sizes of 50 m, 100 m, and 200 m and by a parcel model with instantaneous mixing were compared to those observed. The observed mean conserved scalar profiles are reproduced by both mixing representations, but the observed mean liquid water mixing ratio and buoyancy profiles, all of the observed variance profiles, and the observed nonbuoyancy level are better reproduced by the EMPM. For entrained blob sizes of 100 m and 200 m, undiluted cloud base air reaches the inversion base in the EMPM, as was observed. These results indicate that the EMPM's entrainment parameterization is adequate for these cloud turrets, and that the characteristic entrained blob size is about 100 m. The model results also demonstrate that the finescale structure represented by the EMPM's 1D domain can be directly compared to high-frequency aircraft measurements.

The authors present the objectives of the working group on precipitating convective cloud systems. These center on developing physically based parameterizations for global models in which basic research into the large-scale role of cloud systems is an important part. The approach calls on a range of expertise: cloud-resolving modeling and contributing research, observational evaluation of the model results, and tests of parameterizations in single-column models. Ongoing studies focus on oceanic cloud systems in Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Research Experiment (TOGA COARE). First, cloud-resolving modeling of organized convection on a timescale of a few hours concentrates on momentum transport and surface fluxes. Results are evaluated against data obtained during the 22 February 1993 Intensive Observation Period, which include airborne Doppler radar measurements of a squall line. Second, multiday simulations focus on the environmental effects of cloud systems as they respond to changes in specified (observed) large-scale tendencies and sea surface temperature. In this case, observational data on the scale of the entire TOGA COARE Intensive Flux Array are used in model evaluations. Results and recommendations from the first model intercomparison workshop, as well as the next steps in the intercomparison, are summarized. In the longer term, cloud system research in Working Group 4 will contribute to the Climate Variability and Predictability-Global Ocean-Atmosphere-Land System program, as regards the large-scale effects of cloud systems up to intraseasonal timescales. Another contribution will be to space-borne measurements; for example, cloud-profiling capability will provide data critical to the comprehensive evaluation of upper-tropospheric moisture distribution in cloud-resolving models. Besides additional studies in tropical cloud systems, convection in cold air outbreaks and convection over continents have a high priority.

A stratus-to-cumulus transition (SCT) that resembles observations occurred in Lagrangian numerical simulations of the subtropical marine boundary layer over the northeastern Pacific Ocean southwest of California. The Lagrangian approach involves translating the domain along the climatological boundary-layer trajectory at a rate equal to the observed surface wind speed. The SST is increased at a corresponding rate. The simulations did not include drizzle, the diurnal cycle, divergence changes, or mesoscale circulations and thus demonstrate that these processes are not essential for an SCT. A 2D numerical cloud model that can explicitly represent large convective eddies is used. Turbulence at scales smaller than the large eddies is parameterized using a third-moment turbulence closure. This type of model requires no cloud-regime-specific input and is computationally economical for multiday simulations. The results suggest that there are four stages in the transition from the stratus-topped boundary layer (STBL) to the trade cumulus boundary layer (TCBL). The simulated transition involves two intermediate stages: the deep stratus-topped boundary layer (DSTBL) and the 'cumulus-under-stratocumulus' boundary layer (CUSBL). The DSTBL, like the STBL, is well mixed. The CUSBL has a two-layer structure, like the TCBL, with a well-mixed subcloud layer and a stratified (partly mixed) cloud layer. The transition to a typical TCBL structure preceded the transition to a typical TCBL cloud fraction by about two days. Sensitivity tests indicate that by using diurnally averaged solar radiation with the daytime-averaged solar zenith angle, the model is able to reproduce the diurnally averaged cloud-top height. Tests also suggest that the boundary-layer structure is sensitive to the above-inversion thermodynamic structure.

The progression from the stratus-topped boundary layer (STBL) to the trade cumulus boundary layer (TCBL) during a simulated stratus-to-cumulus transition (SCT) involves two intermediate stages: the deep stratus-topped boundary layer (DSTBL) and the 'cumulus-under-stratocumulus' boundary layer (CUSBL). The DSTBL, like the STBL, has an active circulation that extends from the surface to the cloud top. The CUSBL, like the TCBL, has an active subcloud-layer circulation that is linked to the cloud layer by narrow cumulus updrafts. It is called a 'cumulus-coupled' boundary layer. A generally applicable convective updraft/downdraft partitioning scheme based on trajectory analysis was developed and used to analyze the boundary-layer circulation changes during the simulated SCT. The circulation analysis revealed that as the SST increased and the boundary layer changed from an STBL to a TCBL the updraft fraction in the cloud layer decreased, the convective updrafts strengthened, and the convective downdrafts weakened. The convective mass flux in the cloud layer decreased significantly as SST increased, while in the subcloud layer it changed little. The differences between updraft and downdraft properties and cloud-base levels gradually increased as SST increased. An analysis of the vertical acceleration components of the convective updrafts and downdrafts suggests that there are three steps in the transition from an STBL circulation to a TCBL circulation. First, the STBL deepens due to increased surface buoyancy fluxes as it moves over increasing SST but remains well mixed. Next, the DSTBL gradually changes into the two-layer CUSBL. During this step, negative buoyancy in downdrafts originating near cloud top becomes less important, while positive buoyancy in (cumulus) updrafts becomes more important. This indicates that cloud-top entrainment instability does not play a significant role in the SCT. Finally, the overlying stratocumulus deck gradually dissipates and only the underlying cumulus clouds of a typical TCBL remain. This general sequence of events is supported by recent observational evidence.

Modification of a commonly employed bulk ice-phase microphysics parameterization improves the simulation of few microphysical processes occurring in tropical anvil clouds. The modification includes the revision of the cloud ice growth by the Bergeron process and the associated formation of snow. Application of the modified procedure for numerical simulation of a tropical squall line reveals that these two changes increase the amount of cloud ice and the extent of anvil clouds to more realistic values.

Mixing of entrained air in stratus clouds is an important but poorly understood process. It is a crucial ingredient of cloud-top entrainment instability (CEI). CEI has been proposed as a breakup mechanism for stratus clouds. A recently developed model called the linear eddy model was used to simulate mixing of air entrained into stratus clouds. The linear eddy approach involves stochastic simulation on a one-dimensional domain with sufficient resolution to include all physically relevant length scales. In each realization, molecular diffusion is implemented explicitly, while a sequence of statistically independent 'rearrangement events' represents the effect of turbulent eddies. Inertial range scaling is incorporated. The linear eddy model was used to simulate the mixing of one or more wisps of entrained air with a specified volume of cloud-topped boundary layer (CTBL) air. The volume was idealized to be a horizontal slab of fluid that travels from the top of the CTBL down to the surface in the descending branch of a large convective eddy. The probability density function of the mixing fraction of entrained air was determined from linear eddy model simulations as a function of time for a mean mixing fraction of 0.05 and three wisp sizes. The effect of the mixing on the mean buoyancy of the downdraft could then be calculated given a specification of the buoyancy as a function of mixing fraction. In the simulations, the entrained air did not completely mix with cloudy air just below the CTBL top, nor was uniform saturation maintained. Furthermore, when buoyancy functions typical of observed CTBLs were used, the mean downdraft buoyancy due to entrainment and mixing integrated over the cloud layer remained positive. This suggests that CEI is unlikely in stratocumulus. An additional conclusion is that using reduced spatial resolutions typical of published large-eddy simulations (LES) of CTBLs in mixing simulations significantly underestimates the buoyancy in the cloud layer near cloud top. This may explain why low-resolution LES simulations have exhibited CEI under conditions for which CEI is not observed in the atmosphere.

The two-dimensional UCLA cumulus ensemble model (CEM), which covers a large horizontal area with a sufficiently small horizontal grid size, is used in this study. A number of simulation experiments are performed with the CEM to study the macroscopic behavior of cumulus convection under a variety of different large-scale and underlying surface conditions. Specifically, the modulation of cumulus activity by the imposed large-scale processes and the eddy kinetic energy (EKE) budget are investigated in detail. In all simulations, cumulus convection is rather strongly modulated by large-scale advective processes in spite of the existence of some nonmodulated high-frequency fluctuations. The modulation exhibits some phase delays, however, when the basic wind shear is strong. This is presumably associated with the existence of mesoscale convective organization. The EKE budget analysis shows that the net eddy buoyancy generation rate is nearly zero for a wide range of cumulus ensembles.

A global TRMM database of tropical cloud system precipitation features (PFs), which provides useful observational constraints on cloud system properties, is used to evaluate the bulk microphysics schemes in a cloud-resolving model (CRM). The simulation of the Mesoscale Convective System (MCS) of 11–12 August 1999 during the Kwajalein Experiment (KWAJEX) is executed using the 3D University of Utah CRM, which employs a one-moment bulk, three-ice category microphysical parameterization. The simulated precipitation features are compared with climatological “norms” for Kwajalein locations from the TRMM PF database to evaluate the precipitation microphysics of the cloud model simulation. The model-simulated reflectivities are also compared with vertical profiles of radar reflectivity obtained from a ground-based precipitation radar. Comparison of simulation results with the TRMM observation statistics indicates that the model tends to underestimate microwave brightness temperatures at ice-scattering frequencies and overestimate radar reflectivities, especially for those associated with larger ice particles. The differences between the statistics of KWAJEX simulation and available ground-based precipitation radar observations are relatively small at the levels below 5 km. Above 6 km, the differences increase with height and reach a maximum near 9 km. The simulated radar reflectivities are statistically 5–13 dBZ higher than those from radar observations at levels between 7 and 10.5 km, where graupel is the dominant simulated ice species. The largest graupel mixing ratios, as high as 8 g kg-1, are the most likely reason for the unrealistically high simulated radar reflectivity. Comparison of model-simulated graupel mixing ratio with available microphysics data from the Citation aircraft indicates that the model overestimates graupel content at the level the Citation flew (about 6.4 km). [ABSTRACT FROM AUTHOR]

Presents the objectives of the Global Energy and Water-Cycle Experiment (GEWEX) Cloud Study (GCSS), which centers on developing physically based parameterizations for global models into the role of cloud systems. What the approach call for; Details on ongoing studies in Tropical Ocean Global Atmosphere Coupled Ocean--Atmosphere Research Experiment (TOGA COARE); Cloud-resolving models to develop physically based parameterizations.