scholarly journals CLOUD DROP SPECTRA IN MARITIME AND INLAND REGIONS

MAUSAM ◽  
2021 ◽  
Vol 43 (4) ◽  
pp. 415-420
Author(s):  
S. K. PAUL ◽  
A. G . PILLAI

Measurements o f clo ud drop ..ire spectra on non-preci pitating cumulus clouds, 1·2 km thick,were made at differe nt levels o ver the Arabian Sea (maritime) and over r une (inland) regio n during the end ofthe summer monsoo n seasons of 1973, 1974 and 1979.The macimurn size of clo ud drops for the. Arabian Sea generally increased with height. while that for run eJiJ not show a systematic change with height. At bot h the local ions. the total concentration o f drops decreasedwith height. The maritime dist ributions were bimodal at all levels while those o..-er Punc were usually unimodal.The average values of liquid water content. mean vo lume diameter. dispersion and conccnt rarion of drops withdiameter > 50 «m were a lin le greater and total concentration a little smaller over the maritime region as ' om'pared to those over inland. The co ncentrations of drops with diameter < 14 ,...m and those > 78 I'm and thema ximum ~ i 7e were greater over Pune than o..er the sea. The ..'a riarions in cloud drop spectra and the clo udphysical parameters over beth the locations are discussed.Kc) words - Cloud drop size spectra, Drop co ncentration,

2019 ◽  
Vol 147 (2) ◽  
pp. 477-493
Author(s):  
Mikael K. Witte ◽  
Patrick Y. Chuang ◽  
Orlando Ayala ◽  
Lian-Ping Wang ◽  
Graham Feingold

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.


2010 ◽  
Vol 3 (3) ◽  
pp. 671-681 ◽  
Author(s):  
C. D. Westbrook ◽  
R. J. Hogan ◽  
E. J. O'Connor ◽  
A. J. Illingworth

Abstract. A method to estimate the size and liquid water content of drizzle drops using lidar measurements at two wavelengths is described. The method exploits the differential absorption of infrared light by liquid water at 905 nm and 1.5 μm, which leads to a different backscatter cross section for water drops larger than ≈50 μm. The ratio of backscatter measured from drizzle samples below cloud base at these two wavelengths (the colour ratio) provides a measure of the median volume drop diameter D0. This is a strong effect: for D0=200 μm, a colour ratio of ≈6 dB is predicted. Once D0 is known, the measured backscatter at 905 nm can be used to calculate the liquid water content (LWC) and other moments of the drizzle drop distribution. The method is applied to observations of drizzle falling from stratocumulus and stratus clouds. High resolution (32 s, 36 m) profiles of D0, LWC and precipitation rate R are derived. The main sources of error in the technique are the need to assume a value for the dispersion parameter μ in the drop size spectrum (leading to at most a 35% error in R) and the influence of aerosol returns on the retrieval (≈10% error in R for the cases considered here). Radar reflectivities are also computed from the lidar data, and compared to independent measurements from a colocated cloud radar, offering independent validation of the derived drop size distributions.


2017 ◽  
Vol 74 (2) ◽  
pp. 375-392 ◽  
Author(s):  
Daniel H. Moser ◽  
Sonia Lasher-Trapp

Abstract Cumulus clouds are frequently observed as comprising multiple successive thermals, yet numerical simulations of entrainment have not investigated this level of detail. Here, an idealized simulated cumulus congestus consisting of three successive thermals is used to analyze and understand their role in maintaining the high liquid water content in the core of the cloud, which past 1D modeling studies have suggested can ultimately determine its ability to precipitate. Entrainment and detrainment are calculated directly at the edge of the cloud core at frequent time intervals. Entrainment maxima occur at the rear of the toroidal circulation associated with each thermal and thus are transient features in the lifetime of multithermal clouds. The evolution of the least diluted parcels within each thermal shows that the entrainment rates alone cannot predict the erosion of the high liquid water content cores. A novel analysis of samples of entrained and detrained air within each successive thermal illustrates tendencies for even positively buoyant air, containing condensate, to be entrained by later thermals that rise in the wakes of their predecessors, limiting their dilution. The later thermals can achieve greater depths and produce precipitation when a single thermal could not. Future work is yet needed to evaluate the generality of these results using multiple clouds simulated in different environments with less-idealized modeling frameworks. Implications for current cumulus parameterizations are briefly discussed.


2008 ◽  
Vol 8 (6) ◽  
pp. 1661-1675 ◽  
Author(s):  
E. Freud ◽  
D. Rosenfeld ◽  
M. O. Andreae ◽  
A. A. Costa ◽  
P. Artaxo

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.


2010 ◽  
Vol 3 (2) ◽  
pp. 891-921
Author(s):  
C. D. Westbrook ◽  
R. J. Hogan ◽  
E. J. O'Connor ◽  
A. J. Illingworth

Abstract. A method to estimate the size and liquid water content of drizzle drops using lidar measurements at two wavelengths is described. The method exploits the differential absorption of infrared light by liquid water at 905 nm and 1.5 µm, which leads to a different backscatter cross section for water drops larger than ≈50 µm. The ratio of backscatter measured from drizzle samples below cloud base at these two wavelengths (the colour ratio) provides a measure of the median volume drop diameter D0. This is a strong effect: for D0=200 µm, a colour ratio of ≈6 dB is predicted. Once D0 is known, the measured backscatter at 905 nm can be used to calculate the liquid water content (LWC) and other moments of the drizzle drop distribution. The method is applied to observations of drizzle falling from stratocumulus and stratus clouds. High resolution (32 s, 36 m) profiles of D0, LWC and precipitation rate R are derived. The main sources of error in the technique are the need to assume a value for the dispersion parameter μ in the drop size spectrum (leading to at most a 35% error in R) and the influence of aerosol returns on the retrieval (≈10% error in R for the cases considered here). Radar reflectivities are also computed from the lidar data, and compared to independent measurements from a colocated cloud radar, offering independent validation of the derived drop size distributions.


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