Sensitivity of a GCM climate simulation to differences in continental versus maritime cloud drop size

1994 ◽  
Vol 99 (D11) ◽  
pp. 23107 ◽  
Author(s):  
J. T. Kiehl
Keyword(s):  
Drop Size ◽  
Climate Simulation ◽  
Cloud Drop

Theoretical Aspccts of Cloud Drop Distributions

1949 ◽  
Vol 2 (3) ◽  
pp. 376 ◽  
Author(s):  
EB Kraus ◽  
B Smith
Keyword(s):  
Cooling Rate ◽  
Drop Size ◽  
Initial Temperature ◽  
Theoretical Study ◽  
Air Pressure ◽  
Size Spectrum ◽  
Condensation Nuclei ◽  
Cloud Drop ◽  
Rate Of Cooling

A theoretical study indicates that the number and size of the drops formed in a cloud vary with the rate of cooling, the initial temperature, and the air pressure. The faster the cooling rate, the lower the initial temperature, and the lower the altitude, the greater is the number of drops and the smaller their size. The drop size spectrum also depends, to a large extent, on the number of available condensation nuclei. Furthermore, it tends to be widened by sedimentation and turbulence.

scholarly journals Comparison of Observed and Simulated Drop Size Distributions from Large-Eddy Simulations with Bin Microphysics

2019 ◽  
Vol 147 (2) ◽  
pp. 477-493
Author(s):  
Mikael K. Witte ◽  
Patrick Y. Chuang ◽  
Orlando Ayala ◽  
Lian-Ping Wang ◽  
Graham Feingold
Keyword(s):  
Liquid Water ◽  
Drop Size ◽  
Potential Temperature ◽  
Liquid Water Content ◽  
Liquid Water Path ◽  
Cloud Drop ◽  
Large Eddy Simulation Model ◽  
Surface Precipitation ◽  
Large Eddy ◽  
Bin Microphysics

Abstract Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles also agree well insofar as the thermodynamic profiles match observations, but there are significant differences in DSD shape among simulations that cause discrepancies in higher-order moments such as sedimentation flux, especially as a function of bin resolution. Counterintuitively, high-bin-resolution simulations produce broader DSDs than standard resolution for both cases. Examination of several metrics of DSD width and percentile drop sizes shows that various discrepancies of model output with respect to the observations can be attributed to specific microphysical processes: condensation spuriously creates DSDs that are too wide as measured by standard deviation, which leads to collisional production of too many large drops. The turbulent kernel has the greatest impact on the low-bin-resolution simulation of the drizzling case, which exhibits greater surface precipitation accumulation and broader DSDs than the control (quiescent kernel) simulations. Turbulence effects on precipitation formation cannot be definitively evaluated using bin microphysics until the artificial condensation broadening issue has been addressed.

Dependence of accumulated precipitation on cloud drop size distribution

2010 ◽  
Vol 102 (3-4) ◽  
pp. 471-481 ◽  
Author(s):  
Mladjen Ćurić ◽  
Dejan Janc ◽  
Katarina Veljović
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Drop Size Distribution ◽  
Cloud Drop

scholarly journals Robust relations between CCN and the vertical evolution of cloud drop size distribution in deep convective clouds

2008 ◽  
Vol 8 (6) ◽  
pp. 1661-1675 ◽  
Author(s):  
E. Freud ◽  
D. Rosenfeld ◽  
M. O. Andreae ◽  
A. A. Costa ◽  
P. Artaxo
Keyword(s):  
Amazon Basin ◽  
Drop Size ◽  
Cloud Condensation Nuclei ◽  
Liquid Water Content ◽  
Cloud Drop ◽  
Cloud Droplets ◽  
Freezing Level ◽  
Convective Clouds ◽  
Warm Rain ◽  
Drop Size Distributions

Abstract. In-situ measurements in convective clouds (up to the freezing level) over the Amazon basin show that smoke from deforestation fires prevents clouds from precipitating until they acquire a vertical development of at least 4 km, compared to only 1–2 km in clean clouds. The average cloud depth required for the onset of warm rain increased by ~350 m for each additional 100 cloud condensation nuclei per cm3 at a super-saturation of 0.5% (CCN0.5%). In polluted clouds, the diameter of modal liquid water content grows much slower with cloud depth (at least by a factor of ~2), due to the large number of droplets that compete for available water and to the suppressed coalescence processes. Contrary to what other studies have suggested, we did not observe this effect to reach saturation at 3000 or more accumulation mode particles per cm3. The CCN0.5% concentration was found to be a very good predictor for the cloud depth required for the onset of warm precipitation and other microphysical factors, leaving only a secondary role for the updraft velocities in determining the cloud drop size distributions. The effective radius of the cloud droplets (re) was found to be a quite robust parameter for a given environment and cloud depth, showing only a small effect of partial droplet evaporation from the cloud's mixing with its drier environment. This supports one of the basic assumptions of satellite analysis of cloud microphysical processes: the ability to look at different cloud top heights in the same region and regard their re as if they had been measured inside one well developed cloud. The dependence of re on the adiabatic fraction decreased higher in the clouds, especially for cleaner conditions, and disappeared at re≥~10 μm. We propose that droplet coalescence, which is at its peak when warm rain is formed in the cloud at re=~10 μm, continues to be significant during the cloud's mixing with the entrained air, cancelling out the decrease in re due to evaporation.

scholarly journals The Potential of 8-mm Radars for Remotely Sensing Cloud Drop Size Distributions

1997 ◽  
Vol 14 (1) ◽  
pp. 76-87 ◽  
Author(s):  
E. E. Gossard ◽  
J. B. Snider ◽  
E. E. Clothiaux ◽  
B. Martner ◽  
J. S. Gibson ◽  
...  
Keyword(s):  
Drop Size ◽  
Size Distributions ◽  
Cloud Drop ◽  
Drop Size Distributions
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