Effects Of Cloud Condensation Nuclei Research Articles

Development of a cloud microphysical model and parameterizations to describe the effect of CCN on warm cloud

Abstract. First, a hybrid cloud microphysical model was developed that incorporates both Lagrangian and Eulerian frameworks to study quantitatively the effect of cloud condensation nuclei (CCN) on the precipitation of warm clouds. A parcel model and a grid model comprise the cloud model. The condensation growth of CCN in each parcel is estimated in a Lagrangian framework. Changes in cloud droplet size distribution arising from condensation and coalescence are calculated on grid points using a two-moment bin method in a semi-Lagrangian framework. Sedimentation and advection are estimated in the Eulerian framework between grid points. Results from the cloud model show that an increase in the number of CCN affects both the amount and the area of precipitation. Additionally, results from the hybrid microphysical model and Kessler's parameterization were compared. Second, new parameterizations were developed that estimate the number and size distribution of cloud droplets given the updraft velocity and the number of CCN. The parameterizations were derived from the results of numerous numerical experiments that used the cloud microphysical parcel model. The input information of CCN for these parameterizations is only several values of CCN spectrum (they are given by CCN counter for example). It is more convenient than conventional parameterizations those need values concerned with CCN spectrum, C and k in the equation of N=CSk, or, breadth, total number and median radius, for example. The new parameterizations' predictions of initial cloud droplet size distribution for the bin method were verified by using the aforesaid hybrid microphysical model. The newly developed parameterizations will save computing time, and can effectively approximate components of cloud microphysics in a non-hydrostatic cloud model. The parameterizations are useful not only in the bin method in the regional cloud-resolving model but also both for a two-moment bulk microphysical model and for a global model. The effects of sea salt, sulfate, and organic carbon particles were also studied with these parameterizations and global model.

A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 2: Maritime vs. continental deep convective storms

A systematic modeling study investigates the effects of cloud condensation nuclei (CCNs) on the evolution of mixed-phase deep convective storms. Following previous studies the environmental conditions like buoyancy and vertical wind shear are varied to simulate different storm types like ordinary single cells, multicells and supercells. In addition, the CCN characteristics are changed from maritime to continental conditions. The results reveal very different effects of continentality on the cloud microphysics and dynamics of the different storms. While a negative feedback on total precipitation and maximum updraft velocity is found for ordinary single cells and supercell storms, a positive feedback exists for multicell cloud systems. The most important link between CCN properties, microphysics and dynamics is the release of latent heat of freezing.

Wintertime/summertime contrasts of cloud condensation nuclei and cloud microphysics over the Southern Ocean

Wintertime/summertime contrasts of cloud condensation nuclei (CCN) and cloud microphysics observed in clean maritime environments off the west coast of Tasmania, Australia in the Southern Ocean Cloud Experiment, are presented. The average wintertime CCN concentration (NCCN) was 32 cm−3 at 1% supersaturation (S), but it was 19 cm−3 when only baseline (maritime airflow with minimal anthropogenic influences) flights were considered. In contrast, the average summertime NCCN were more than a factor of 5 higher than wintertime for all S ranges. The seasonal contrast was larger when only baseline flights were considered, especially at lower S: summertime more than an order of magnitude higher than wintertime at S below 0.1%. Corresponding cloud droplet concentrations (Nc) showed similar contrasts but to a smaller extent. Summertime average cloud droplet concentrations [Nc(ave)] were only 2.5 times higher than wintertime concentrations (70 cm−3 versus 28 cm−3). This difference was nearly a factor of 3 when only baseline flights were considered (57 cm−3 versus 20 cm−3). Flight‐average NCCN and various representations of adiabatic cloud droplet concentrations (Na) generally showed good correlations, indicating that the original effects of CCN are somehow retained in the Nc(ave). The average mean diameter (MD) of the cloud droplets was 13.9 and 17.1 μm for the summer and winter clouds, respectively. For baseline only, average MDs were 15.4 and 18.2 μm, respectively. Average MD was thus above or close to the 15‐μm threshold for drizzle production, except for the summertime nonbaseline clouds, which had an average MD smaller than 10 μm. Because of the larger droplet sizes, conversion to drizzle was more efficient in the winter clouds, where the average drizzle liquid water content (Ld) of 0.12 g m−3 was twice that of the summer Ld. The Ld for the summer nonbaseline clouds was negligible. Average Ld was also highly dependent on cloud depth. Winter baseline clouds were sometimes too thin to produce significant drizzle even though they contained very low Nc and very large MDs. The thickest clouds contained the highest Ld although their MD was not always the largest.

Parameterization of the Effect of Cloud Condensation Nuclei on Optical Properties of a Non-precipitating Water Layer Cloud

A new method is proposed to predict the optical thickness, effective radius, and concentration of cloud droplets in water layer clouds by using the spectrum of cloud condensation nuclei (CCN), ascent velocity at cloud base, and liquid water path (LWP). A retrieval method is also proposed to predict CCN number concentration by using independent observational data of ascent velocity at the cloud base, the optical thickness and LWP of clouds. For this purpose, a newly developed cloud microphysical model that relates cloud droplet size distributions to the updraft velocity, and to CCN constituents and size distribution is used. Cloud droplet growth is calculated, with special care being taken to avoid non-physical numerical diffusion of the droplet spectrum. Near the cloud base, CCN activation and subsequent cloud droplet growth are calculated in a Lagrangian framework to model the effect of CCN on growth by condensation more accurately. In the middle and upper parts of the cloud, an Eulerian framework is used to estimate growth by coalescence for cloud droplet size distributions. Simulated vertical profiles of droplet size distributions, and a solu-tion to the radiative transfer equation using the discrete ordinate method, with no parameterizations, yield the optical properties of the cloud for short-wavelength radiation. Using the approximation equation proposed in this study, the maximum value of supersaturation in a cloud (Smax) is predicted by observing cumulative activated CCN number concentration at 0.075% supersaturation Nc(075%)), and the ascent velocity at the cloud base. Using this Smax, we can estimate Nc(Smax), which is the cumulative number concentration of CCN, whose critical supersaturations are lower than Smax. Nc(Smax) is used to predict the concentration of cloud droplets at the middle altitude of layer cloud (Nd). Conventionally Nd is assumed to be Nc(Smax). However, our parameterization can show that Nd is smaller than Nc(Smax), when Nc(Smax) is large. For the fixed liquid water path, optical thickness and effective radius can be expressed as a function of Nd, unless drizzle is falling from the cloud. The parameterizations developed in this paper are based on the U.S. Standard Atmosphere 1976. If necessary, the parameterizations for the extremely different atmosphere from that used here can be developed in the same way.

Revised Parameterization to Predict Cloud Droplet Concentration and a Retrieval Method to Predict CCN Concentration-Supplement-

In our recent paper “Parameterization of the effect of cloud condensation nuclei on optical properties of a non-precipitating water layer cloud” (Kuba et al. 2003), we developed an approximation to predict the cloud droplet concentration as a function of the CCN concentration and the updraft velocity at the cloud base. This study improves on the approximation for convenience. In addition, this study proposes an approximation for higher updraft velocities than those in the previous paper.

Field measurements of the effects of cloud condensation nuclei on cloud microphysics in various environments

Field measurements of the effects of cloud condensation nuclei on cloud microphysics in various environments

Bistability of CCN concentrations and thermodynamics in the cloud-topped boundary layer

RECENT discussions of the effect of cloud condensation nuclei (CCN) in controlling the albedo of marine stratus cloud and hence global climate1–3have raised questions concerning the factors that control CCN populations and how (or whether) such factors should be included in climate models4. The observed near-constancy5 of CCN concentrations in remote marine air is remarkable in view of the wide variety of possible conditions, the range over which they might be expected to vary, and the considerable difference between marine and continental CCN concentrations. Here we explain this relative lack of variability, thought to be due to a balance of source and sink processes6,7, in a simple model of the marine cloud-topped boundary layer. Solutions to this model give two stable CCN concentration regimes—one corresponding to the low concentration observed over the ocean, the other corresponding to the higher concentration observed over land—each dominated by a different sink mechanism. The two regimes have very different optical properties, and thus may be of climatic significance.

雲核が雲粒粒径分布に与える影響に関する数値実験

The effect of cloud condensation nuclei (CCN) on the production of large cloud droplets in a shallow cumulus cloud was studied by numerical modeling. Dynamical processes were treated in an Eulerian framework in an axially symmetric model. Microphysical processes in the layer near cloud base were treated in a Lagrangian framework using air-parcels which ascend successively, in order to avoid the influence of artificial broadening of droplet size distribution on the formation of large cloud droplets. Following conclusions were reached. When the concentration of nuclei in the range of Aitken size (radius_??_0.lμm) is low, large droplets are produced mainly by coalescence which occurs between droplets formed on nuclei smaller than 1μm in radius (large nuclei). In this case droplets formed on giant nuclei (radius>1μm) do not contribute to the concentration of large cloud droplets. When the concentration of nuclei in the range of Aitken size is high, droplets formed on giant nuclei contribute largely to the concentration of large droplets and most of large droplets are produced by coalescence between droplets formed on giant nuclei.

Effects of Cloud Condensation Nuclei Due to Fires and Surface Sources During South Florida Droughts

Cloud condensation nuclei (CCN) at cloud base strongly affect the droplet concentration at cloud base, which in turn influences the life history of a cloud. There are usually more nuclei over land than over water because of surface sources of nuclei, and vegetation fires produce large numbers of nuclei which may keep much of a cloud's water in small droplets that fail to reach raindrop size. Smoke particles from drought fires are thought to result from the burning of four major vegetation types in South Florida. Samples of these were burned in the laboratory and produced (at 0.75% supersaturation) between 109 and 1010 nuclei per gram burned. A simple calculation, assuming reasonable burn rates for these materials, resulted in 4600 CCN cm−2 when mixed uniformly to cloud base over a large area. The drought between 1 April and 15 May of 1967 over Florida was found to be related predominantly to synoptic-scale dryness and subsiding northerly winds aloft. There was no significant large-scale lag in rainfall caused by lingering CCN from fires and the dry surface, since dynamic changes explain the onset of normal rainfall. Individual cloud rainfall may have been affected by high CCN counts as indicated by cumulus model calculations. Liquid water fallout from small clouds is affected to a greater degree than from tall clouds.

南極昭和基地における雲核の観測

Observation of cloud condensation nuclei was carried out at Syowa Station (69°00'S, 39°35'E), Antarctica from the beginning of February to the end of December, 1968 using a chemical diffusion chamber. Supersaturation adopted were in five grades of 0, 0.05, 0.1, 0.5 and 1% at the same time. As a result the mean number concentrations of 0 and 1% supersaturations at the station were 3×102 and 8×102 particles per cm3, respectively. The maximum concentrations of 0 and 1% were 3×103 and 4×103, and in only one case 9×103 particles per cm3 at 1% was seen. The minimum concentrations of both supersaturations were nil, but in general they were approximately in an order of 1×102 particles at 1% supersaturation. The high concentrations were observed in the range of the wind direction from ESE to S and they were related to the wind direction rather than wind velocity. The spectra of the number concentration in the range from 0 to 1% supersaturations showed two distinct patterns. One showed nearly flat spectra, namely 2-3×103 and the other showed steep gradients of 1-5×102 and 2-4×103 particles per cm3 at 0 and 1% supersaturations, respectively. The nuclei spectra showing steep gradients were considered to be from a man-made source judging from the shapes of the spectra and by the wind directions at the station. The nuclei showing a flat pattern were surmized to be of an oceanic source. An examination of the washout effect of cloud condensation nuclei in "before", "during" and "after" solid precipitation was carried out. As a result, the value of the number concentration of cloud condensation nuclei in "during" precipitation was less approximately 30% than that of "before" precipitation, and the value of the concentration in "after" precipitation was greater 200% than that of "during" precipitation in both 0 and 1% supersaturations.