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Ann M. Fridlind and Andrew S. Ackerman

Abstract

A proposed objective of the planned Aerosol–Cloud–Ecosystem (ACE) satellite mission is to provide constraints on climate model representation of aerosol effects on clouds by retrieving profiles of aerosol number concentration, effective variance, and effective radius over the 0.1–1-μm radius range under humidified ambient conditions with 500-m vertical resolution and uncertainties of 100%, 50%, and 10%, respectively. Shallow, broken marine clouds provide an example of conditions where boundary layer aerosol properties would be retrieved in clear-sky gaps. To quantify the degree of constraint that proposed retrievals might provide on cloud radiative forcing (CRF) simulated by climate models under such conditions, dry aerosol size distribution parameters are independently varied here in large-eddy simulations of three well-established modeling case studies. Using the rudimentary available aerosol specifications, it is found that relative changes of total dry aerosol properties in simulations can be used as a proxy for relative changes of ambient aerosol properties targeted by ACE retrievals. The sensitivity of simulated daytime shortwave CRF to the proposed uncertainty in retrieved aerosol number concentration is −15 W m−2 in the overcast limit, roughly a factor of 2 smaller than a simple analytic estimate owing primarily to aerosol-induced reductions in simulated liquid water path across this particular set of case studies. The CRF sensitivity to proposed uncertainties in retrieved aerosol effective variance and effective radius is typically far smaller, with no corresponding analytic estimate. Generalization of the results obtained here using only three case studies would require statistical analysis of relevant meteorological and aerosol observations and quantification of observational and model uncertainties and biases.

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Ann M. Fridlind and Andrew S. Ackerman
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David E. Stevens, Andrew S. Ackerman, and Christopher S. Bretherton

Abstract

The authors present three-dimensional numerical simulations of oceanic trade cumulus clouds underlying stratocumulus clouds. The case studied is a Global Energy and Water Experiment (GEWEX) Cloud System Study (GCSS) model intercomparison that is loosely based on observed conditions during the Atlantic Trade Cumulus Experiment (ATEX). It is motivated by the importance of this cloud type to global cloud radiative forcing, and their role as a feeder system for deep convection in the Tropics. This study focuses on the sensitivity of the modeled cloud field to the domain size and the grid spacing. Domain widths from 6.5 to 20 km and horizontal grid spacings ranging from 10 to 80 m, with corresponding vertical grid spacing ranging from 5 to 40 m, are studied, involving massively parallel computations on up to 2.5 billion grid cells. The combination of large domain size and small grid resolution provides an unprecedented perspective on this type of convection.

The mean stratocumulus cloud fraction, optical depth, and vertical fluxes of heat, moisture, and momentum are found to be quite sensitive to both the domain size and the resolution. The sensitivities are associated with a strong feedback between cloud fraction, cloud-top radiative cooling, and entrainment. The properties of individual cumulus clouds rising into the stratocumulus are less affected than the stratocumulus clouds. The simulations with 80-m horizontal by 40-m vertical resolution are clearly under-resolved, with distinctly different distributions of liquid water within the clouds. Increasing the resolution to finer than 40 m horizontal/20 m vertical affects the inversion structure and entrainment processes somewhat, but has less impact on the structure of individual clouds. Large-domain simulations exhibit mesoscale structure in the cloud organization and liquid water path. This mesoscale variability feeds back on the domain-mean properties through the cloud-radiative feedback. These simulations suggest that very large computations are required to obtain meaningful cloud statistics for this case.

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Andrew S. Ackerman, Peter V. Hobbs, and Owen B. Toon

Abstract

A detailed 1D model of the stratocumulus-topped marine boundary layer is described. The model has three coupled components: a microphysics module that resolves the size distributions of aerosols and cloud droplets, a turbulence module that treats vertical mixing between layers, and a multiple wavelength radiative transfer module that calculates radiative heating rates and cloud optical properties.

The results of a 12-h model simulation reproduce reasonably well the bulk thermodynamics, microphysical properties, and radiative fluxes measured in an ∼500-m thick, summertime marine stratocumulus cloud layer by Nicholls. However, in this case, the model predictions of turbulent fluxes between the cloud and subcloud layers exceed the measurements. Results of model simulations are also compared to measurements of a marine stratus layer made under gale conditions and with measurements of a high, thin marine stratocumulus layer. The variations in cloud properties are generally reproduced by the model, although it underpredicts the entrainment of overlying air at cloud top under gale conditions.

Sensitivities of the model results are explored. The vertical profile of cloud droplet concentration is sensitive to the lower size cutoff of the droplet size distribution due to the presence of unactivated haze particles in the lower region of the modeled cloud. Increases in total droplet concentrations do not always produce less drizzle and more cloud water in the model. The radius of the mean droplet volume does not correlate consistently with drizzle, but the effective droplet radius does. The greatest impacts on cloud properties predicted by the model are produced by halving the width of the size distribution of input condensation nuclei and by omitting the effect of cloud-top radiative cooling on the condensational growth of cloud droplets. The omission of infrared scattering produces noticeable changes in cloud properties. The collection efficiencies for droplets <30-µm radius, and the value of the accommodation coefficient for condensational droplet growth, have noticeable effects on cloud properties. The divergence of the horizontal wind also has a significant effect on a 12-h model simulation of cloud structure.

Conclusions drawn from the model are tentative because of the limitations of the 1D model framework. A principal simplification is that the model assumes horizontal homogeneity, and, therefore, does not resolve updrafts and downdrafts. Likely consequences of this simplification include overprediction of the growth of droplets by condensation in the upper region of the cloud, underprediction of droplet condensational growth in the lower region of the cloud, and underprediction of peak supersaturations.

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Mikhail D. Alexandrov, Alexander Marshak, and Andrew S. Ackerman

Abstract

A new analytical statistical model describing the structure of broken cloud fields is presented. It depends on two parameters (cell size and occupancy probability) and provides chord distributions of clouds and gaps between them by length, as well as the cloud fraction distribution. This approach is based on the assumption that the structure of a cloud field is determined by a semiregular grid of cells (an abstraction of the atmospheric convective cells), which are filled with cloud with some probability. First, a simple discrete model is introduced, where clouds and gaps can occupy an integer number of cells, and then a continuous analog is developed, allowing for arbitrary cloud and gap sizes. The influence of a finite sample size on the retrieved statistics is also described.

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Bastiaan van Diedenhoven, Ann M. Fridlind, and Andrew S. Ackerman

Abstract

Lidar measurements obtained during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment under a mixed-phase stratus cloud that was lightly precipitating ice show a range of surprisingly low depolarization ratios (4%–23%), despite an absence of cloud droplets there. These depolarization ratios are much lower than the range of theoretical values obtained for various ice habits. The depolarization ratios correlate well with radar reflectivity, suggesting that the variation in depolarization ratios results from variations in ice water content, rather than variation in ice habits or orientation. By calculating lidar depolarization based on (i) large-eddy simulations and (ii) in situ ice size distribution measurements, it is shown that the presence of humidified aerosol particles in addition to the ice precipitation can explain the distribution and vertical profile of the observed depolarization ratios, although uncertainties related to the aerosol size distributions are substantial. These calculations show that humidified aerosol must be taken into account when interpreting lidar depolarization measurements for cloud and precipitation phase discrimination or ice habit classification, at least under conditions similar to those observed during SHEBA.

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Xiaoli Zhou, Andrew S. Ackerman, Ann M. Fridlind, and Pavlos Kollias

Abstract

This study uses eddy-permitting simulations to investigate the mechanisms that promote mesoscale variability of moisture in drizzling stratocumulus-topped marine boundary layers. Simulations show that precipitation tends to increase horizontal scales. Analysis of terms in the prognostic equation for total water mixing ratio variance indicates that moisture stratification plays a leading role in setting horizontal scales. This result is supported by simulations in which horizontal mean thermodynamic profiles are strongly nudged to their initial well-mixed state, which limits cloud scales. It is found that the spatial variability of subcloud moist cold pools surprisingly tends to respond to, rather than determine, the mesoscale variability, which may distinguish them from dry cold pools associated with deeper convection. Simulations also indicate that moisture stratification increases cloud scales specifically by increasing latent heating within updrafts, which increases updraft buoyancy and favors greater horizontal scales.

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Mikhail D. Alexandrov, Andrew S. Ackerman, and Alexander Marshak

Abstract

Cellular statistical models are designed to provide a simple two-parameter characterization of the structure of broken cloud fields described through distributions of cloud fraction and of chord lengths for clouds and clear gaps. In these analytical models cloud fields are assumed to occur on a semiregular grid of cells (which can be vaguely interpreted as atmospheric convective cells). In a simple, discrete cell model, cell size is fixed and each cell can either be completely filled with cloud with some probability or remain empty. Extending the discrete model to a continuous case provides more realism by allowing arbitrary cloud and gap sizes. Here the continuous cellular model is tested by comparing its statistics with those from large-eddy simulations (LES) of marine boundary layer clouds based on case studies from three trade-cumulus field projects. The statistics largely agree with some differences in small sizes approaching the LES model grid spacing. Exponential chord-length distributions follow from the assumption that the probability of any cell being cloudy is constant, appropriate for a given meteorological state (narrow sampling). Relaxing that assumption, and instead allowing this probability to have its own distribution, leads to a power-law distribution of chord lengths, appropriate to a broader sample of meteorological states (diverse sampling).

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Xiaoli Zhou, Andrew S. Ackerman, Ann M. Fridlind, and Pavlos Kollias
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Hyunho Lee, Ann M. Fridlind, and Andrew S. Ackerman

Abstract

This study evaluates some available schemes designed to solve the stochastic collection equation (SCE) for collision–coalescence of hydrometeors using a size-resolved (bin) microphysics approach and documents their numerical properties within the framework of a box model. Comparing three widely used SCE schemes, we find that all converge to almost identical solutions at sufficiently fine mass grids. However, one scheme converges far slower than the other two and shows pronounced numerical diffusion at the large-drop tail of the size distribution. One of the remaining two schemes is recommended on the basis that it is well converged on a relatively coarse mass grid, stable for large time steps, strictly mass conservative, and computationally efficient. To examine the effects of SCE scheme choice on simulating clouds and precipitation, two of the three schemes are compared in large-eddy simulations of a drizzling stratocumulus field. A forward simulator that produces Doppler spectra from the large-eddy simulation results is used to compare the model output directly with radar observations. The scheme with pronounced numerical diffusion predicts excessively large mean Doppler velocities and overly broad and negatively skewed spectra compared with observations, consistent with numerical diffusion demonstrated in the box model. Statistics obtained using the recommended scheme are closer to observations, but notable differences remain, indicating that factors other than SCE scheme accuracy are limiting simulation fidelity.

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