Collision Efficiency of Drops in a Wide Range of Reynolds Numbers: Effects of Pressure on Spectrum Evolution

Pinsky, Mark; Хаин, А.; Shapiro, M.

doi:10.1175/1520-0469(2001)058<0742:ceodia>2.0.co;2

Cited by 163 publications

(115 citation statements)

References 36 publications

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“…Collisions are described by solving the stochastic collection equations for the corresponding size distributions using the Bott (1998) method. Heightdependent, gravitational collision kernels for drop-drop and drop-graupel interactions are taken from Pinsky et al (2001) and Khain et al (2001); those for collisions between ice crystals are taken from Khain and Sednev (1995) and Khain et al (2004). The latter studies include the dependence of particle mass on the ice crystal cross section.…”

Section: Model Descriptionmentioning

confidence: 99%

Application of a new scheme of cloud base droplet nucleation in a spectral (bin) microphysics cloud model: sensitivity to aerosol size distribution

Ilotoviz

Хаин

2016

Atmos. Chem. Phys.

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Abstract. A new scheme of droplet nucleation at cloud base is implemented into the Hebrew University Cloud Model (HUCM) with spectral (bin) microphysics. In this scheme, supersaturation maximum S max near cloud base is calculated using theoretical results according to which, where w is the vertical velocity at cloud base and N d is droplet concentration. Microphysical cloud structure obtained in the simulations of a midlatitude hail storm using the new scheme is compared with that obtained in the standard approach, in which droplet nucleation is calculated using supersaturation calculated in grid points. The simulations were performed with different concentrations of cloud condensational nuclei (CCN) and with different shapes of CCN size spectra. It is shown that the new nucleation scheme substantially improves the vertical profile of droplet concentration shifting the concentration maximum to cloud base. It is shown that the effect of the CCN size distribution shape on cloud microphysics is not less important than the effect of the total CCN concentration. It is shown that the smallest CCN with diameters less than about 0.015 µm have a substantial effect on mixed-phase and ice microphysics of deep convective clouds. Such CCN are not measured by standard CCN probes, which hinders understanding of cold microphysical processes.

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Section: Model Descriptionmentioning

confidence: 99%

Application of a new scheme of cloud base droplet nucleation in a spectral (bin) microphysics cloud model: sensitivity to aerosol size distribution

Ilotoviz

Хаин

2016

Atmos. Chem. Phys.

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“…The raindrop-particle collection efficiency E(d p ,D p ) has been investigated extensively in a series of previous studies (e.g., Wang and Pruppacher, 1977;Grover and Pruppacher, 1985;Slinn, 1983;Pruppacher and Klett, 1997;Pinsky and Khain, 2001). Both experimental and theoretical results have shown that E(d p ,D p ) is the result of the net action of various forces influencing the relative motion of aerosol particles and hydrometeors.…”

Section: Raindrop-particle Collection Efficiency E(d P D P )mentioning

confidence: 99%

Uncertainty assessment of current size-resolved parameterizations for below-cloud particle scavenging by rain

Wang¹,

2010

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Abstract. Current theoretical and empirical size-resolved parameterizations of the scavenging coefficient ( ), a parameter commonly used in aerosol transport models to describe below-cloud particle scavenging by rain, have been reviewed in detail and compared with available field and laboratory measurements. Use of different formulations for raindropparticle collection efficiency can cause uncertainties in sizeresolved values of one to two orders of magnitude for particles in the 0.01-3 µm diameter range. Use of different formulations of raindrop number size distribution can cause values to vary by a factor of 3 to 5 for all particle sizes. The uncertainty in caused by the use of different droplet terminal velocity formulations is generally small than a factor of 2. The combined uncertainty due to the use of different formulations of raindrop-particle collection efficiency, raindrop size spectrum, and raindrop terminal velocity in the current theoretical framework is not sufficient to explain the one to two order of magnitude under-prediction of for the theoretical calculations relative to the majority of field measurements. These large discrepancies are likely caused by additional known physical processes (i.e, turbulent transport and mixing, cloud and aerosol microphysics) that influence field data but that are not considered in current theoretical parameterizations. The predicted size-resolved particle concentrations using different theoretical parameterization can differ by up to a factor of 2 for particles smaller than 0.01 µm and by a factor of >10 for particles larger than 3 µm after 2-5 mm of rain. The predicted bulk mass and number concentrations (integrated over the particle size distribution) can differ by a factor of 2 between theoretical and empirical parameterizations after 2-5 mm of moderate intensity rainfall.

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“…We use u g = gτ for a < 40 µm and take u g (a) from the measurements [38] for a > 50 µm with a smooth interpolation for 40 µm < a < 50 µm. Hydrodynamic interaction between approaching droplets is accounted in K g by the collision efficiency E, which values we take from [39] at the 750 mbar altitude.…”

Section: Turbulent Diffusion and Collision Ratementioning

confidence: 99%

Evolution of non-uniformly seeded warm clouds in idealized turbulent conditions

2008

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Abstract. We present a mean-field model of cloud evolution that describes droplet growth due to condensation and collisions and droplet loss due to fallout. The model accounts for the effects of cloud turbulence both in a large-scale turbulent mixing and in a microphysical enhancement of condensation and collisions. The model allows for an effective numerical simulation by a scheme that is conservative in water mass and keeps accurate count of the number of droplets. We first study the homogeneous situation and determine how the rain-initiation time depends on the concentration of cloud condensation nuclei (CCN) and turbulence level. We then consider clouds with an inhomogeneous concentration of CCN and evaluate how the rain initiation time and the effective optical depth vary in space and time. We argue that over-seeding even a part of a cloud by small hygroscopic nuclei, one can substantially delay the onset and increase the amount of precipitation.

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Collision Efficiency of Drops in a Wide Range of Reynolds Numbers: Effects of Pressure on Spectrum Evolution

Cited by 163 publications

References 36 publications

Application of a new scheme of cloud base droplet nucleation in a spectral (bin) microphysics cloud model: sensitivity to aerosol size distribution

Application of a new scheme of cloud base droplet nucleation in a spectral (bin) microphysics cloud model: sensitivity to aerosol size distribution

Uncertainty assessment of current size-resolved parameterizations for below-cloud particle scavenging by rain

Evolution of non-uniformly seeded warm clouds in idealized turbulent conditions

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