Numerical Study of the Effect of CCN on the Size Distribution of Cloud Droplets

Takeda, Takeshi; Kuba, Naomi

doi:10.2151/jmsj1965.60.4_978

Cited by 34 publications

(26 citation statements)

References 14 publications

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“…equation 6), if the aerosol particles consist primarily of two components (e.g., submicrometer particles and supermicrometer mineral dust particles) and if the variabilities in d a,coarse and d a,fine were small. It is also important to investigate the dependence of the d a value of dust particles on their internal mixing state (whether they are coated with solution or not) because the mixing state critically affects its direct radiative effect [Ackerman and Toon, 1981] as well as its cloud microphysical properties; they would activate as cloud condensation nuclei at lower supersaturations [e.g., Takeda and Kuba, 1982] and as ice forming nuclei in the immersion-freezing mode at lower supersaturations and warmer temperatures [Zuberi et al, 2002] when they were coated with solution.…”

Section: Total Aerosol Linear Depolarization Ratiomentioning

confidence: 99%

Raman lidar and aircraft measurements of tropospheric aerosol particles during the Asian dust event over central Japan: Case study on 23 April 1996

et al. 2003

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[1] The vertical distributions of tropospheric aerosol properties were measured during the Asian dust event over central Japan (35°-36°N, 136°-137°E), using a ground-based Raman lidar and aircraft-based instruments on 23 April 1996. The lidar measured enhancements of aerosol backscattering below an altitude of 4 km and between 5 and 8 km where the total aerosol linear depolarization ratio showed peaks of 12-15% and the relative humidities were $30%. The aircraft measurements showed that the aerosol particles consisted primarily of irregularly shaped mineral dusts and sea salts with a mode radius (r m ) of $1 mm and sulfates with r m $ 0.1 mm over the measured height range of 0.6-5.5 km. Electron microscopic analyses suggest that $77% of the mineral particles were coated with a solution at 1.8 km and that the fraction of coated particles decreased with height. The aerosol backscattering coefficients (b a ), calculated from the airborne optical particle counter (OPC) data, were smaller than the lidar-derived values by $30% above 3.1 km and by $44% below that altitude. The difference was attributable to the horizontal and temporal inhomogeneities of the aerosol properties between the measurement sites and to the uncertainty in b a , particularly for the coarse particles calculated from the OPC data. The aerosol depolarization ratios (d a ) estimated from the OPC data showed the same increase as those obtained with the lidar above 4.1 km. This suggests that the proportion of backscattering by coarse particles to total particles primarily controlled the d a measured with the lidar in that region.

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Section: Total Aerosol Linear Depolarization Ratiomentioning

confidence: 99%

Raman lidar and aircraft measurements of tropospheric aerosol particles during the Asian dust event over central Japan: Case study on 23 April 1996

et al. 2003

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“…However we note that there are other parameters used in this study that can lead to the uncertainties in the results. For example, Takeda and Kuba (1982) found that using an insufficient number of model grids will lead to the narrow CDSD reported by Mordy (1959). Kreidenweis et al (2003) found that both the spectral discretization and the uncertainty in the value of the mass accommodation coefficient can lead to uncertainty in the results.…”

Section: Discussionmentioning

confidence: 99%

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

et al. 2018

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Abstract. Cloud droplet size distributions (CDSDs), which are related to cloud albedo and rain formation, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a moving-size-grid cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, submicrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with early work. The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by numerous smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are as follows: (1) droplets form on aerosols of different sizes, and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in situ measurements and 3-D dynamic models.

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“…Takeda and Kuba (1982) noted that the discretizations of Mordy (1959) and Fitzgerald (1974) were too broad to allow an accurate estimation of cloud droplet concentration. In our model, the number of nuclei included in one class is less than 1% of the number of activated cloud droplets.…”

Section: Cloud Modelmentioning

confidence: 99%

“…The equations governing the growth rate of droplets by condensation are those in Takeda and Kuba (1982). The potential temperature tendency of an air parcel is calculated.…”

Section: Governing Equationsmentioning

confidence: 99%

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

Kuba

Iwabuchi

Maruyama

et al. 2003

Journal of the Meteorological Society of Japan

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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 soluCorresponding author: Naomi Kuba, Frontier Research System for Global Change, 3173-25 Showamachi, Kanazawa-ku, Yokohama 236-0001, Japan. E-mail: kuba@jamstec.go.jp ( 2003, Meteorological Society of Japan 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 ðS max Þ is predicted by observing cumulative activated CCN number concentration at 0.075% supersaturation ðN c ð0:075%ÞÞ, and the ascent velocity at the cloud base. Using this S max , we can estimate N c ðS max Þ, which is the cumulative number concentration of CCN, whose critical supersaturations are lower than S max . N c ðS max Þ is used to predict the concentration of cloud droplets at the middle altitude of layer cloud ðN d Þ. Conventionally N d is assumed to be N c ðS max Þ. However, our parameterization can show that N d is smaller than N c ðS max Þ, when N c ðS max Þ is large. For the fixed liquid water path, optical thickness and effective radius can be expressed as a function of N d , 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.

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Numerical Study of the Effect of CCN on the Size Distribution of Cloud Droplets

Cited by 34 publications

References 14 publications

Raman lidar and aircraft measurements of tropospheric aerosol particles during the Asian dust event over central Japan: Case study on 23 April 1996

Raman lidar and aircraft measurements of tropospheric aerosol particles during the Asian dust event over central Japan: Case study on 23 April 1996

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

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

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