Hongli Jiang

Evaluation of Large-Eddy Simulations via Observations of Nocturnal Marine Stratocumulus

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 wa s5ma t thecloud-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.

Controls on precipitation and cloudiness in simulations of trade-wind cumulus as observed during RICO

Twelve large-eddy simulations, with a wide range of microphysical representations, are compared to each other and to independent measurements. The measurements and the initial and forcing data for the simulations are taken from the undisturbed period of the Rain in Cumulus over the Ocean (RICO) field study. A regional downscaling of meteorological analyses is performed so as to provide forcing data consistent with the measurements. The ensemble average of the simulations plausibly reproduces many features of the observed clouds, including the vertical structure of cloud fraction, profiles of cloud and rain water, and to a lesser degree the population density of rain drops. The simulations do show considerable departures from one another in the representation of the cloud microphysical structure and the ensuant surface precipitation rates, increasingly so for the more simplified microphysical models. There is a robust tendency for simulations that develop rain to produce a shallower, somewhat more stable cloud layer. Relations between cloud cover and precipitation are ambiguous.

Large-Eddy Simulations of a Drizzling, Stratocumulus-Topped Marine Boundary Layer

Cloud water sedimentation and drizzle in a stratocumulus-topped boundary layer are the focus of an intercomparison of large-eddy simulations. The context is an idealized case study of nocturnal stratocumulus under a dry inversion, with embedded pockets of heavily drizzling open cellular convection. Results from 11 groups are used. Two models resolve the size distributions of cloud particles, and the others parameterize cloud water sedimentation and drizzle. For the ensemble of simulations with drizzle and cloud water sedimentation, the mean liquid water path (LWP) is remarkably steady and consistent with the measurements, the mean entrainment rate is at the low end of the measured range, and the ensemble-average maximum vertical wind variance is roughly half that measured. On average, precipitation at the surface and at cloud base is smaller, and the rate of precipitation evaporation greater, than measured. Including drizzle in the simulations reduces convective intensity, increases boundary layer stratification, and decreases LWP for nearly all models. Including cloud water sedimentation substantially decreases entrainment, decreases convective intensity, and increases LWP for most models. In nearly all cases, LWP responds more strongly to cloud water sedimentation than to drizzle. The omission of cloud water sedimentation in simulations is strongly discouraged, regardless of whether or not precipitation is present below cloud base.

Cloud Resolving Simulations of Mixed-Phase Arctic Stratus Observed during BASE: Sensitivity to Concentration of Ice Crystals and Large-Scale Heat and Moisture Advection

The authors’ previous idealized, two-dimensional cloud resolving model (CRM) simulations of Arctic stratus revealed a surprising sensitivity to the concentrations of ice crystals. In this paper, simulations of an actual case study observed during the Beaufort and Arctic Seas Experiment are performed and the results are compared to the observed data. It is again found in the CRM simulations that the simulated stratus cloud is very sensitive to the concentration of ice crystals. Using midlatitude estimates of the availability of ice forming nuclei (IFN) in the model, the authors find that the concentrations of ice crystals are large enough to result in the almost complete dissipation of otherwise solid, optically thick stratus layers. A tenuous stratus can be maintained in the simulation when the continuous input of moisture through the imposed large-scale advection is strong enough to balance the ice production. However, in association with the large-scale moisture and warm advection, only by reducing the concentration of IFN to 0.3 of the midlatitude estimate values can a persistent, optically thick stratus layer be maintained. The results obtained from the reduced IFN simulation compare reasonably well with observations. The longwave radiative fluxes at the surface are significantly different between the solid stratus and liquidwater-depleted higher ice crystal concentration experiments. This work suggests that transition-season Arctic stratus can be very vulnerable to anthropogenic sources of IFN, which can alter cloud structure sufficiently to affect the rates of melting and freezing of the Arctic Ocean. The authors find that the Hallett‐Mossop riming splintering mechanism is not activated in the simulations because the cloud droplets are very small and cloud temperatures are outside the range supporting efficient rime splintering. Thus, the conclusions drawn from the results presented in this paper may be applicable to only a limited class of Arctic stratus.

Effect of aerosol on warm convective clouds: Aerosol-cloud-surface flux feedbacks in a new coupled large eddy model

Received 27 April 2005; revised 25 October 2005; accepted 8 November 2005; published 5 January 2006. [1] We present a new large eddy simulation model that comprises coupled components representing size-resolved aerosol and cloud microphysics, radiative properties of aerosol and clouds, dynamics, and a surface soil and vegetation model. The model is used to investigate the effect of increases in aerosol on liquid water path LWP, cloud fraction, optical depth, and precipitation formation in warm, continental cumulus clouds. Sets of simulations that either neglect, or include the radiative properties of a partially absorbing aerosol are performed. In the absence of aerosol radiative effects, an increase in aerosol loading results in a reduction in precipitation. However, the clouds do not experience significant changes in LWP, cloud fraction and cloud depth; aerosol effects on LWP and cloud fraction are small compared to the dynamical variability of the clouds at any given aerosol concentration. Reasons for this response are discussed. When aerosol radiative effects are included, the modification in atmospheric heating profiles, and the reduction in surface latent and sensible heat fluxes resulting from the presence of these particles, have a significant effect on cloud parameters and boundary layer evolution. For the case considered, there is a significant reduction in the strength of convection, LWP, cloud fraction and cloud depth. Cloud optical depth responds non-monotonically to the increase in aerosol. These results indicate that in continental regions surface processes must be included in calculations of aerosol-cloud-precipitation interactions. Neglect of these surface processes may result in an overestimate of the second aerosol indirect effect.

Simulations of aerosol‐cloud‐dynamical feedbacks resulting from entrainment of aerosol into the marine boundary layer during the Atlantic Stratocumulus Transition Experiment

dynamics, and radiative properties. The initial CCN concentration is 100 cm � 3 in one simulation, while in the second simulation it varies from 100 cm � 3 below the cloud top to a peak of 1200 cm � 3 at the inversion. In the clean case, cooling from evaporating drizzle destabilizes the layer just below cloud base (not the entire subcloud layer) with respect to the surface, and promotes stronger penetrating cumulus. In the case with the elevated pollution layer, reduced drizzle at the cloud base results in weaker penetrating cumulus and a less effective supply of surface moisture to the cloud. This results in a much lower liquid water path (LWP) relative to the clean case that offsets the cloud albedo enhancement due to higher drop concentrations. Thus, although entrained CCN enhance the droplet concentration, the net effect on the cloud albedo is small. Additional simulations were performed to study the sensitivity of the MBL to varying levels of largescale subsidence. The change in large-scale subsidence has a large effect on boundary layer dynamics, cloud microphysics, and the radiative budget. The simulations are used to separate the effects of enhanced albedo due to enhanced drop concentrations at constant LWP and those where LWP is modified due to dynamical feedbacks. For this case study, weaker subsidence results in a cloud with higher LWP and a cloud albedo that is enhanced over and above that due to enhanced droplet concentration. The simulations point to the complex dynamical-microphysical-radiative feedbacks in the MBL and how elevated polluted layers can change cloud radiative forcing in ways that would not be easily predicted by large-scale models. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0320 Atmospheric Composition and Structure: Cloud physics and chemistry; 3307 Meteorology and Atmospheric Dynamics: Boundary layer processes; 3337 Meteorology and Atmospheric Dynamics: Numerical modeling and data assimilation; KEYWORDS: aerosol-cloud-dynamic feedbacks, entrainment, ASTEX, marine boundary layer, LES Citation: Jiang, H., G. Feingold, and W. R. Cotton, Simulations of aerosol-cloud-dynamical feedbacks resulting from entrainment of aerosol into the marine boundary layer during the Atlantic Stratocumulus Transition Experiment, J. Geophys. Res., 107(D24), 4813, doi:10.1029/2001JD001502, 2002.

The Influence of Entrainment and Mixing Assumption on Aerosol–Cloud Interactions in Marine Stratocumulus

Abstract This study uses large-eddy simulation with bin microphysics to investigate the influence of entrainment and mixing on aerosol–cloud interactions in the context of idealized, nocturnal, nondrizzling marine stratocumulus (Sc). Of particular interest are (i) an evaporation–entrainment effect and a sedimentation–entrainment effect that result from increasing aerosol concentrations and (ii) the nature of mixing between clear and cloudy air, where homogeneous and extreme inhomogeneous mixing represent the bounding mixing types. Simulations are performed at low resolution (Δz = 20 m; Δx, y = 40 m) and high resolution (Δz = 10 m; Δx, y = 20 m). It is demonstrated that an increase in aerosol from clean conditions (100 cm−3) to polluted conditions (1000 cm−3) produces both an evaporation–entrainment and a sedimentation–entrainment effect, which couple to cause about a 10% decrease in liquid water path (LWP) when all warm microphysical processes are included. These dynamical effects are insensitive to both ...

Effect of Aerosol on the Susceptibility and Efficiency of Precipitation in Warm Trade Cumulus Clouds

Abstract Large-eddy simulations of warm, trade wind cumulus clouds are conducted for a range of aerosol conditions with a focus on precipitating clouds. Individual clouds are tracked over the course of their lifetimes. Precipitation rate decreases progressively as aerosol increases. For larger, precipitating clouds, the polluted clouds have longer lifetimes because of precipitation suppression. For clean aerosol conditions, there is good agreement between the average model precipitation rate and that calculated based on observed radar reflectivity Z and precipitation rate R relationships. Precipitation rate can be expressed as a power-law function of liquid water path (LWP) and Nd, to reasonable accuracy. The respective powers for LWP and Nd are of similar magnitude compared to those based on observational studies of stratocumulus clouds. The time-integrated precipitation rate represented by a power-law function of LWP, Nd, and cloud lifetime is much more reliably predicted than is R expressed in terms of...

Soil moisture estimation using an artificial neural network: a feasibility study

An artificial neural network (ANN) based algorithm is implemented and tested for soil moisture estimation. The ANN model is calibrated (trained) and validated (tested) with data including National Centers for Environmental Protection (NCEP) daily precipitation; normalized difference vegetation index (NDVI) data processed by the US Geological Survey Earth Resources Observations Systems (USGS EROS) data center; Geostationary Operational Environmental Satellite (GOES) based, cloud-masked infrared (IR) skin temperature produced by the University of Maryland; and soil moisture profiles measured over the Oklahoma (OK) Mesonet. The performance of the ANN model is evaluated by direct comparison between the soil moisture estimated by the ANN model and the Mesonet measurements and by examining the correlation between them. Strong correlation is demonstrated between the ANN estimates and Mesonet measurements for spatially averaged data. This work suggests that the ANN model is a promising alternative to soil moisture estimation. The advantage of the ANN approach to soil moisture estimation is that it can provide estimates having resolution commenmmensurate with remotely sensed IR data and has the potential for worldwide coverage.

Supplying Local Microphysics Parameterizations with Information about Subgrid Variability: Latin Hypercube Sampling

One problem in computing cloud microphysical processes in coarse-resolution numerical models is that many microphysical processes are nonlinear and small in scale. Consequently, there are inaccuracies if microphysics parameterizations are forced with grid box averages of model fields, such as liquid water content. Rather, the model needs to determine information about subgrid variability and input it into the microphysics parameterization. One possible solution is to assume the shape of the family of probability density functions (PDFs) associated with a grid box and sample it using the Monte Carlo method. In this method, the microphysics subroutine is called repeatedly, once with each sample point. In this way, the Monte Carlo method acts as an interface between the host model’s dynamics and the microphysical parameterization. This avoids the need to rewrite the microphysics subroutines. A difficulty with the Monte Carlo method is that it introduces into the simulation statistical noise or variance, associated with the finite sample size. If the family of PDFs is tractable, one can sample solely from cloud, thereby improving estimates of in-cloud processes. If one wishes to mitigate the noise further, one needs a method for reduction of variance. One such method is Latin hypercube sampling, which reduces noise by spreading out the sample points in a quasi-random fashion. This paper formulates a sampling interface based on the Latin hypercube method. The associated family of PDFs is assumed to be a joint normal/lognormal (i.e., Gaussian/lognormal) mixture. This method of variance reduction has a couple of advantages. First, the method is general: the same interface can be used with a wide variety of microphysical parameterizations for various processes. Second, the method is flexible: one can arbitrarily specify the number of hydrometeor categories and the number of calls to the microphysics parameterization per grid box per time step. This paper performs a preliminary test of Latin hypercube sampling. As a prototypical microphysical formula, this paper uses the Kessler autoconversion formula. The PDFs that are sampled are extracted diagnostically from large-eddy simulations (LES). Both stratocumulus and cumulus boundary layer cases are tested. In this diagnostic test, the Latin hypercube can produce somewhat less noisy time-averaged estimates of Kessler autoconversion than a traditional Monte Carlo estimate, with no additional calls to the microphysics parameterization. However, the instantaneous estimates are no less noisy. This paper leaves unanswered the question of whether the Latin hypercube method will work well in a prognostic, interactive cloud model, but this question will be addressed in a future manuscript.