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Numerical convergence of the collision–coalescence algorithm used in Lagrangian particle-based microphysics is studied in 2D simulations of an isolated cumulus congestus (CC) and in box and multi-box simulations of collision–coalescence. Parameters studied are the time step for coalescence and the number of super-droplets (SDs) per cell. A time step of 0.1 s gives converged droplet size distribution (DSD) in box simulations and converged mean precipitation in CC. Variances of the DSD and of precipitation are not sensitive to the time step. In box simulations, mean DSD converges for 103 SDs per cell, but variance of the DSD does not converge as it decreases with an increasing number of SDs. Fewer SDs per cell are required for convergence of the mean DSD in multi-box simulations, probably thanks to mixing of SDs between cells. In CC simulations, more SDs are needed for convergence than in box or multi-box simulations. Mean precipitation converges for 5×103 SDs, but only in a strongly precipitating cloud. In cases with little precipitation, mean precipitation does not converge even for 105 SDs per cell. Variance in precipitation between independent CC runs is more sensitive to the resolved flow field than to the stochasticity in collision–coalescence of SDs, even when using as few as 50 SDs per cell. [ABSTRACT FROM AUTHOR]

Numerical convergence of the collision-coalescence algorithm used in Lagrangian particle-based microphysics is studied in 2D simulations of an isolated Cumulus Congestus (CC) and in box simulations of collision-coalescence. Parameters studied are the time step for coalescence and the number of super-droplets per cell. Time step of 0.1s gives converged droplet size distribution (DSD) in box simulations and converged mean precipitation in CC. Variances of the DSD and of precipitation are not sensitive to time step. In box simulations mean DSD converges for 103 super-droplets per cell, but variance of the DSD does not converge. In CC simulations mean precipitation converges for 5×103, but only in a strongly precipitating case. In cases with less precipitation, mean precipitation does not converge even for 105 super-droplet per cell. The result that more super-droplets are needed in CC simulations than in box simulations indicates that too large differences in the DSD between cells can reduce precipitation in cloud simulations. Variance in precipitation between independent CC runs is not affected by the number of super-droplets. This study suggests that parameters typically used in large-eddy simulations (LES) with particle microphysics can lead to underestimation of rain in lightly precipitating clouds. [ABSTRACT FROM AUTHOR]

This paper discusses an extension of the approach proposed previously to represent the delay of cloud water evaporation and buoyancy reversal due to the cloud-environment mixing in bulk microphysics large-eddy simulation of clouds. In the original approach, an additional equation for the mean spatial scale of cloudy filaments was introduced to represent the progress toward microscale homogenization of a volume undergoing turbulent cloud-environment mixing, with the evaporation of cloud water allowed only when the filament scale approached the Kolmogorov microscale. Here, it is shown through a posteriori analysis of model simulations that one should also predict the volume fraction of the cloudy air that was diagnosed in the original approach. The resulting model of turbulent mixing and homogenization, referred to as the [lambda]-[beta] model, is applied in a series of shallow convection simulations using various spatial resolutions and compared to the traditional bulk model. This work represents an intermediate step in the development of a modeling framework to simulate characteristics of microphysical transformations during entrainment and subgrid-scale turbulent mixing.

The impact of giant sea salt aerosols released from breaking waves on rain formation in marine boundary layer clouds is studied using large-eddy simulations (LES). We perform simulations of marine cumuli and stratocumuli for various concentrations of cloud condensation nuclei (CCN) and giant CCN (GCCN). Cloud microphysics are modeled with a Lagrangian method that provides key improvements in comparison to previous LES of GCCN that used Eulerian bin microphysics. We find that GCCN significantly increase precipitation in stratocumuli. This effect is strongest for low and moderate CCN concentrations. GCCN are found to have a smaller impact on precipitation formation in cumuli. These conclusions are in agreement with field measurements. We develop a simple parameterization of the effect of GCCN on precipitation, accretion, and autoconversion rates in marine stratocumuli. Significance Statement: Breaking sea waves release salt particles into the atmosphere. Cloud droplets formed on these salt particles can grow larger than droplets formed on other smaller particles. Therefore, sea salt particles can be important for rain formation over oceans. To investigate this effect, we performed idealized computer simulations of stratocumulus and cumulus clouds. Sea salt particles were modeled with an unprecedented precision thanks to the use of an emerging modeling method. In our simulations sea salt particles significantly enhance rain formation in stratocumuli, but not in cumuli. Our study has implications for climate models, because stratocumuli are important for Earth's energy budget and for rain enhancement experiments. [ABSTRACT FROM AUTHOR]

A model of the dynamically inactive parts of cumulus cloud (i.e., void of bulk, organized vertical drafts) is proposed. It is assumed that such parts of clouds consist of coarse filaments of saturated, droplet-containing air mixed with filaments of air free of liquid water and perhaps even unsaturated. During vertical motions saturated and unsaturated filaments change their buoyancy according to dry- and wet-adiabatic processes, respectively, but being entangled with each other, they cannot develop separate vertical drafts of reasonable scale; the latter can form only if bulk net buoyancy occurs. A preliminary study of evolution of such a mixture due to bulk vertical motion and internal homogenizing mixing (which both affect the latent sensible heat transition) is made by means of a one-dimensional model. Results of a number of runs of the model are presented, confirming the supposition that cloud with such a structure can persist fairly long even in conditionally unstable stratification. Some generalizations of these results and applications to real clouds are briefly discussed.

The use of the Paluch mixing diagram in examinations related to cumulus entrainment is reviewed. Paluch technique is applied to numerically simulated entrainment into a rising thermal to demonstrate the theoretical aspects. Paluch diagram must be used prudently for clouds that precipitate and for observation levels which lack precipitation-size particles.

The plane-parallel model for the parameterization of clouds in global climate models is examined in order to estimate the effects of the vertical profile of the microphysical parameters on radiative transfer calculations for extended boundary layer clouds. The vertically uniform model is thus compared to the adiabatic stratified one. The validation of the adiabatic model is based on simultaneous measurements of cloud microphysical parameters in situ and cloud radiative properties from above the cloud layer with a multispectral radiometer. In particular, the observations demonstrate that the dependency of cloud optical thickness on cloud geometrical thickness is larger than predicted with the vertically uniform model and that it is in agreement with the prediction of the adiabatic one. Numerical simulations of the radiative transfer have been performed to establish the equivalence between the two models in terms of the effective radius. They show that the equivalent effective radius of a vertically uniform model is between 80% and 100% of the effective radius at the top of an adiabatic stratified model. The relationship depends, in fact, upon the cloud geometrical thickness and droplet concentration. Remote sensing measurements of cloud radiances in the visible and near infrared are then examined at the scale of a cloud system for a marine case and the most polluted case sampled during the second Aerosol Characterization Experiment. The distributions of the measured values are significantly different between the two cases. This constitutes observational evidence of the aerosol indirect effect at the scale of a cloud system. Finally, the adiabatic stratified model is used to develop a procedure for the retrieval of cloud geometrical thickness and cloud droplet number concentration from the measurements of cloud radiances. It is applied to the marine and to the polluted cases. The retrieved values of droplet concentration are significantly underestimated with respect to the values measured in situ. Despite this discrepancy the procedure is efficient at distinguishing the difference between the two cases.

This paper introduces a new scheme available in the library of algorithms for representing cloud microphysics in numerical models named libcloudph++. The scheme extends the Lagrangian microphysics scheme available in libcloudph++ to the aqueous phase chemical processes occurring within cloud droplets. The representation of chemical processes focuses on the aqueous phase oxidation of the dissolved SO2 by O3 and H2O2. The Lagrangian Microphysics and Chemistry (LMC) scheme allows tracking the changes in the cloud condensation nuclei (CCN) distribution caused by both collisions between cloud droplets and aqueous phase oxidation. The scheme is implemented in C++ and equipped with bindings to Python which allow reusing the created scheme from models implemented in other programming languages. The scheme can be used on either CPU or GPU, and is distributed under the GPL3 license. Here, the LMC scheme is tested in a simple 0-dimensional adiabatic parcel model and then used in a 2-dimensional prescribed flow framework. The results are discussed with the focus on changes to the CCN sizes and compared with other model simulations discussed in the literature. [ABSTRACT FROM AUTHOR]