Mean Droplet Radius Research Articles

Impact of a polysidpersed fuel distribution on the ignition characteristic

Determining the thermal profile of ignition is important because the desired ignition behavior varies with the objective. For example, extended ignition prolongs the time that the engine runs; however, fast ignition offers a higher power gain. The pollution caused by undesirable chemical reactions, as determined by the ignition profile, is another important aspect. Based on a previously developed method, we examined the impact of different theoretical particle size distributions (PSDs) on the thermal ignition profile. We compared different PSDs of polydispersed fuel spray with normal distributions with various means, each corresponding to the same fuel volume. Our results revealed a significant dependence of thermal ignition on the PSD. Systems that comprised only low-radius droplets did not reach ignition, whereas systems with only high-radius droplets required a long time to establish ignition. Moreover, the change in the mean droplet radius unexpectedly resulted in a double hump in the maximum temperature of the combustion process.

Critical charges for droplet collisions

Two micron-sized water droplets approaching each other do not always coalesce due to the cushioning effect of the air between them. When the droplets do not carry any electrical charges, one needs to consider the breakdown of hydrodynamics at very small scales to decide whether the droplets collide and coalesce or not. In contrast, two approaching droplets that are oppositely charged always coalesce if the charges are large enough. To find the charge for which the transition to charge-dominated collisions occurs, we computed the collision efficiency of charged, hydrodynamically interacting droplets settling in quiescent air, including the noncontinuum regime at small interfacial distances. For oppositely charged droplets, we find that the transition occurs when a saddle point of the relative droplet dynamics exits the region within which the continuum hydrodynamics breaks down. For cloud droplets with radii 16 and 20µm, we observe that the transition occurs at ∼103 elementary charges e. For charges smaller than this, we predict that the coalescence rate depends primarily upon the Knudsen number (Kn, the ratio of the mean-free-path of air to the mean droplet radius), whereas coalescence for much larger charges does not depend upon Kn. For droplets charged with the same polarity, we find the critical charge to be substantially larger (∼104e for the above radii) for reasons that we discuss. Published by the American Physical Society 2024

CCN Activation and Droplet Growth in Pi Chamber Simulations with Lagrangian Particle–Based Microphysics

Abstract Numerical simulations of turbulent moist Rayleigh–Bénard convection driving CCN activation and droplet growth in the laboratory Pi chamber are discussed. Supersaturation fluctuations come from isobaric mixing of warm and humid air rising from the lower boundary with colder air featuring lower water vapor concentrations descending from the upper boundary. Lagrangian particle–based microphysics is used to represent the growth of haze CCN and cloud droplets with kinetic, solute, and surface tension effects included. Dry CCN spectra in the range between 2- and 200-nm radii from field observations are considered. Increasing the total CCN concentration from pristine to polluted conditions results in an increase in the droplet concentration and reduction in the mean droplet radius and spectral width. These are in agreement with Pi chamber observations and numerical simulations, as well as with numerous past studies of CCN cloud-base activation in natural clouds. The key result is that a relatively small fraction of the available CCN is activated in the Pi chamber fluctuating supersaturations, from about a half in the pristine case to only a 10th in the polluted case. The activation fraction as a function of the dry CCN radius is similar in all simulations, close to zero at the CCN small end, increasing to a maximum at CCN radius around 50 nm, and decreasing to close to zero at the large CCN end. This is explained as too small supersaturations to activate small CCN as in natural clouds and insufficient time to allow large CCN reaching the critical radius. Significance Statement Impact of turbulence on the formation and growth of cloud droplets is an important cloud physics problem. Laboratory experiments in the Michigan Technological University cloud chamber provide key insights into this problem. Numerical simulations of cloud chamber processes discussed in this paper complement laboratory experiments by providing insights difficult or impossible to obtain in the laboratory. The study contrasts the formation and growth of cloud droplets in the laboratory cloud chamber with processes taking place in natural clouds. The differences documented in this paper pose questions concerning the impact of turbulence on the formation and growth of cloud droplets as a result of interactions of clouds with their environment.

Optimization of operating conditions in the stage of steam turbine by black-box method

From the point of view of performance and economical in power plants, it is necessary to pay attention to the measurement of wet steam. The objective of this research is to employ the multi-objective black-box technique to minimize thermodynamic losses related to wet losses and improve the efficiency of the steam turbine, disregarding the process of film water deposition on the blade surface. For this purpose, a complete model of the steam turbine stage consisting of a stator-rotor is used to study wet steam. The simultaneous effects of two design variables on the performance of the steam turbine stage have been analyzed. The numerical model of wet steam flow has been used for calculating the values of the optimization criteria, including integral of wetness fraction (IWF), integral of mean droplet radius (IDR), turbine stage efficiency (TSE), condensation loss rate (Lr), and mass flow rate (Mr). According to the results, the temperature and pressure ratio were suggested to be 339.44 (K) and 0.51 (−), respectively, which improved the IWF by 30% and the IDR by about 7.3%. Also, the optimal mode increased TSE by about 1.3% and led to the reduction of Lr and Mr, by about 29%, and 1.3%, respectively.

Optimization of the Air Cleaning Properties of Fog

Fog droplets are very often used as a cleaning agent when air pollution can be dangerous for health conditions and ecosystem. This work presents a new system to optimize the cleaning properties of fog by tuning its microphysical parameters. For this purpose, a newly developed system, which is based on the electromagnetic echo effect (EMEE) sensor, is used to detect the most efficient interaction between fog and impurities, i.e., which fog droplets can be used to most effectively clean a certain type of pollutant from the air. Fog droplet spectra controlled by the nozzle pressure system can be used to effectively remove pollutants from the air. For this purpose, an automated system for aerosol generation can allow an accurate control over the fog microphysical parameters and the use of fluids with specific concentrations of pulverized chemical compounds. Fog droplet size distribution is controlled by the feeding gas pressure at the nozzle and chemical simulants. The experimental results showed that the microphysical parameters (MP) are directly related to the impurity of species used in the cleanup simulation process. The MP parameters of fog are liquid water content (LWC), droplet mean radius (Rm), droplet number concentration (Nd), and both aerosol type and mass concentration. In the lab testing, harmless simulants of CBRN (chemical, biological, radiological and nuclear) species were used. During the tests, fog droplet size distribution is controlled by the air pressure at the nozzle and simulants. It is concluded that an integrated fog generator system (IFGS) with EMEE sensor developed in the current work can be utilized broadly to control fog microphysical parameters, leading to an optimum aerosol/chemical species’ cleaning process.

Optimization of operating conditions in the steam turbine blade cascade using the black-box method

Water droplets cause corrosion and erosion, condensation loss, and thermal efficiency reduction in low-pressure steam turbines. In this study, multi-objective optimization was carried out using the black-box method through the automatic linking of a genetic algorithm (GA) and a computational fluid dynamics (CFD) code to find the optimal values of two design variables (inlet stagnation temperature and cascade pressure ratio) to reduce wetness in the last stages of turbines. The wet steam flow numerical model was used to calculate the optimization parameters, including wetness fraction rate, mean droplet radius, erosion rate, condensation loss rate, kinetic energy rate, and mass flow rate. Examining the validation results showed a good agreement between the experimental data and the numerical outcomes. According to the optimization results, the inlet stagnation temperature and the cascade pressure ratio were proposed to be 388.67 (K) and 0.55 (−), respectively. In particular, the suggested optimal temperature and pressure ratio improved the liquid mass fraction and mean droplet radius by about 32% and 29%, respectively. Also, in the identified optimal operating state, the ratios of erosion, condensation loss, and kinetic energy fell by 76%, 32.7%, and 15.85%, respectively, while the mass flow rate ratio rose by 0.68%.

A Mechanistic Sea Spray Generation Function Based on the Sea State and the Physics of Bubble Bursting

AbstractBubbles bursting at the ocean surface are an important source of ocean‐spray aerosol, with implications on radiative and cloud processes. Yet, very large uncertainties exist on the role of key physical controlling parameters, including wind speed, sea state and water temperature. We propose a mechanistic sea spray generation function that is based on the physics of bubble bursting. The number and mean droplet radius of jet and film drops is described by scaling laws derived from individual bubble bursting laboratory and numerical experiments, as a function of the bubble radius and the water physico‐chemical properties (viscosity, density and surface tension, all functions of temperature), with drops radii at production from 0.1 to 500 µm. Next, we integrate over the bubble size distribution entrained by breaking waves. Finally, the sea spray generation function is obtained by considering the volume flux of entrained bubbles due to breaking waves in the field constrained by the third moment of the breaking distribution (akin to the whitecap coverage). This mechanistic approach naturally integrates the role of wind and waves via the breaking distribution and entrained air flux, and a sensitivity to temperature via individual bubble bursting mechanisms. The resulting sea spray generation function has not been tuned or adjusted to match any existing data sets, in terms of magnitude of sea salt emissions and recently observed temperature dependencies. The remarkable coherence between the model and observations of sea salt emissions therefore strongly supports the mechanistic approach and the resulting sea spray generation function.

Comparison of Lagrangian Superdroplet and Eulerian Double-Moment Spectral Microphysics Schemes in Large-Eddy Simulations of an Isolated Cumulus Congestus Cloud

Abstract Advanced microphysics schemes (such as Eulerian bin and Lagrangian superdroplet) are becoming standard tools for cloud physics research and parameterization development. This study compares a double-moment bin scheme and a Lagrangian superdroplet scheme via large-eddy simulations of nonprecipitating and precipitating cumulus congestus clouds. Cloud water mixing ratio in the bin simulations is reduced compared to the Lagrangian simulations in the upper part of the cloud, likely from numerical diffusion, which is absent in the Lagrangian approach. Greater diffusion in the bin simulations is compensated by more secondary droplet activation (activation above cloud base), leading to similar or somewhat higher droplet number concentrations and smaller mean droplet radius than the Lagrangian simulations for the nonprecipitating case. The bin scheme also produces a significantly larger standard deviation of droplet radius than the superdroplet method, likely due to diffusion associated with the vertical advection of bin variables. However, the spectral width in the bin simulations is insensitive to the grid spacing between 50 and 100 m, suggesting other mechanisms may be compensating for diffusion as the grid spacing is modified. For the precipitating case, larger spectral width in the bin simulations initiates rain earlier and enhances rain development in a positive feedback loop. However, with time, rain formation in the superdroplet simulations catches up to the bin simulations. Offline calculations using the same drop size distributions in both schemes show that the different numerical methods for treating collision–coalescence also contribute to differences in rain formation. The stochastic collision–coalescence in the superdroplet method introduces more variability in drop growth for a given rain mixing ratio.

Droplet characteristics in monsoon clouds before rain as observed over a high altitude site in Western Ghats, India

The cloud droplet size distribution (CDSD) and microphysical properties prior to monsoon rain events is studied using in-situ ground observations over a high altitude site in Western Ghats, India. The cloud microphysical properties, such as cloud droplet number concentration (CDNC), liquid water content (LWC), cloud droplet spectrum, droplet effective diameter (ED), droplet mean radius (Rm), spectral width (σ), and relative dispersion (ε) showed a considerable variation. A detailed analysis of CDSD before rain events showed single and multi-mode patterns which varied from case to case. An apparent variation in cloud microphysical properties is noted for both single and multi-mode cases. Large cloud droplets were found in both single and multi-mode clouds, and analysis revealed the possibility of entrainment of aerosols into these clouds leading to multi modes in the CDSD. Observed rain event duration indirectly suggested higher warm rain depths (D*) when multi-mode cases are observed.

The enhancement of droplet collision by electric charges and atmospheric electric fields

Abstract. The effects of electric charges and fields on droplet collision–coalescence and the evolution of cloud droplet size distribution are studied numerically. Collision efficiencies for droplet pairs with radii from 2 to 1024 µm and charges from −32 r2 to +32 r2 (in units of elementary charge; droplet radius r in units of µm) in different strengths of downward electric fields (0, 200, and 400 V cm−1) are computed by solving the equations of motion for the droplets. It is seen that the collision efficiency is increased by electric charges and fields, especially for pairs of small droplets. These can be considered as being electrostatic effects. The evolution of the cloud droplet size distribution with the electrostatic effects is simulated using the stochastic collection equation. Results show that the electrostatic effect is not notable for clouds with the initial mean droplet radius of r¯=15 µm or larger. For clouds with the initial r¯=9 µm, the electric charge without a field could evidently accelerate raindrop formation compared to the uncharged condition, and the existence of electric fields further accelerates it. For clouds with the initial r¯=6.5 µm, it is difficult for gravitational collision to occur, and the electric field could significantly enhance the collision process. The results of this study indicate that electrostatic effects can accelerate raindrop formation in natural conditions, particularly for polluted clouds. It is seen that the aerosol effect on the suppression of raindrop formation is significant in polluted clouds, when comparing the three cases with r¯=15, 9, and 6.5 µm. However, the electrostatic effects can accelerate raindrop formation in polluted clouds and mitigate the aerosol effect to some extent.

Comparison of Eulerian Bin and Lagrangian Particle-Based Microphysics in Simulations of Nonprecipitating Cumulus

AbstractA single nonprecipitating cumulus congestus setup is applied to compare droplet spectra grown by the diffusion of water vapor in Eulerian bin and particle-based Lagrangian microphysics schemes. Bin microphysics represent droplet spectral evolution applying the spectral density function. In the Lagrangian microphysics, computational particles referred to as superdroplets are followed in time and space with each superdroplet representing a multiplicity of natural cloud droplets. The same cloud condensation nuclei (CCN) activation and identical representation of the droplet diffusional growth allow the comparison. The piggybacking method is used with the two schemes operating in a single simulation, one scheme driving the dynamics and the other one piggybacking the simulated flow. Piggybacking allows point-by-point comparison of droplet spectra predicted by the two schemes. The results show the impact of inherent limitations of the two microphysics simulation methods, numerical diffusion in the Eulerian scheme and a limited number of superdroplets in the Lagrangian scheme. Numerical diffusion in the Eulerian scheme results in a more dilution of the cloud upper half and thus smaller cloud droplet mean radius. The Lagrangian scheme typically has larger spatial fluctuations of droplet spectral properties. A significantly larger mean spectral width in the bin microphysics across the entire cloud depth is the largest difference between the two schemes. A fourfold increase of the number of superdroplets per grid volume and a twofold increase of the spectral resolution and thus the number of bins have small impact on the results and provide only minor changes to the comparison between simulated cloud properties.

Impact of aerosols and turbulence on cloud droplet growth: an in-cloud seeding case study using a parcel–DNS (direct numerical simulation) approach

Abstract. This paper investigates the relative importance of turbulence and aerosol effects on the broadening of the droplet size distribution (DSD) during the early stage of cloud and raindrop formation. A parcel–DNS (direct numerical simulation) hybrid approach is developed to seamlessly simulate the evolution of cloud droplets in an ascending cloud parcel. The results show that turbulence and cloud condensation nuclei (CCN) hygroscopicity are key to the efficient formation of large droplets. The ultragiant aerosols can quickly form embryonic drizzle drops and thus determine the onset time of autoconversion. However, due to their scarcity in natural clouds, their contribution to the total mass of drizzle drops is insignificant. In the meantime, turbulence sustains the formation of large droplets by effectively accelerating the collisions of small droplets. The DSD broadening through turbulent collisions is significant and therefore yields a higher autoconversion rate compared to that in a nonturbulent case. It is argued that the level of autoconversion is heavily determined by turbulence intensity. This paper also presents an in-cloud seeding scenario designed to scrutinize the effect of aerosols in terms of number concentration and size. It is found that seeding more aerosols leads to higher competition for water vapor, reduces the mean droplet radius, and therefore slows down the autoconversion rate. On the other hand, increasing the seeding particle size can buffer such a negative feedback. Despite the fact that the autoconversion rate is prominently altered by turbulence and seeding, bulk variables such as liquid water content (LWC) stays nearly identical among all cases. Additionally, the lowest autoconversion rate is not co-located with the smallest mean droplet radius. The finding indicates that the traditional Kessler-type or Sundqvist-type autoconversion parameterizations, which depend on the LWC or mean radius, cannot capture the drizzle formation process very well. Properties related to the width or the shape of the DSD are also needed, suggesting that the scheme of Berry and Reinhardt (1974) is conceptually better. It is also suggested that a turbulence-dependent relative-dispersion parameter should be considered.

Laboratory and numerical modeling of the formation of superfog from wildland fires

Smoke from human-induced fires such as prescribed fires can occasionally cause significant reduction in visibility on highways in the southern United States. Visibility reduction to less than 3 m has been termed “superfog” and environmental conditions that lead to its formation have been proposed previously. Accurate characterization and prediction of precursor conditions for superfog is needed to prevent dangerous low visibility situations when planning prescribed fires. It is hypothesized that extremely hygroscopic cloud condensation nuclei from the smoldering phase of a fire can produce a large number of droplets smaller in size than in naturally occurring fog. This large number of small droplets can produce superfog conditions with relatively low liquid water content. A thermodynamics-based model for fog formation was developed. Laboratory generated superfog measured by a Phase Doppler Particle Analyzer determined that mean droplet radius was 1.5 μm and the size distribution could be modeled with a lognormal distribution. Experiments in an environmentally-conditioned wind tunnel using longleaf pine (Pinus palustris Mill.) needle fuel beds provided visibility, heat flux, temperature, humidity, and particle data for model validation. Numerical modeling was used to approximate the growth of a superfog boundary-layer with liquid water content values of 2 g m−3 or greater. The model successfully predicted previous superfog events.

The effect of the orientation and the height of periodic sub-micrometric texturing on dropwise condensation

Controlling condensation conditions by surface topography is of prime interest. The aim of this work is to investigate the behavior of water droplets condensing on oriented sub-micrometric structures representing ripples with wavelengths around 800 nm.Droplet behavior was studied on different ripples heights and on untextured surfaces. It was specifically looked at how the presence of ripples creates geometrical confinement, and how that influences the deformation and the orientation of single droplets. Results show that the condensed droplets follow the orientation of textured features, especially with high structures height (150 nm). This is shown by the decreasing of droplet roundness with ripples height. The relative number of circular droplets (roundness near to 1) is around 0.6 for 70 nm high ripples and decrease to around 0.2 for 150 nm high ripples. The corresponding relative number on untextured surface is around 0.5.A mechanism, based on droplets pinning and hysteresis, is proposed to explain the influence of the ripples orientation in a vertical plane, onto the droplet deformation during coalescence step.Finally, the presence of ripples is shown to barely impact breath figure dynamics. Number of droplets and mean droplet radius for the textured and untextured surfaces present a comparable evolution.

Nucleation pressure threshold in acoustic droplet vaporization

Acoustic droplet vaporization (ADV) has been studied by several laboratories around the world, including the parametric dependence of its nucleation. In this abstract, we will present our approach of combining classical homogeneous nucleation theory with superharmonic focusing to predict necessary pressures to induce nucleation in ADV. We will show that linear acoustics is a valid approximation to leading order when particle displacements in the sound field are small relative to the radius of the exposed droplet. This is done by perturbation analysis of an axisymmetric compressible inviscid flow about a micrometer-sized droplet with small surface perturbations relative to the mean droplet radius when subjected to an incoming ultrasonic wave. A calibrated single element spherical focus transducer (Olympus A321S 7.5 MHz) was positioned in a water tank above an inverted microscope (Leica DM IL) to emit single ten-cycle bursts. Single droplets (3–30 μm) were placed on ultrasound gel and exposed quasi free-field. Theoretical derivations and predictions will be compared to experimental findings. The ADV nucleation pressure threshold inside the droplet is calculated to be −9.33±0.30 MPa for typical experimental parameters. As a result we are able to predict if a given incident pressure waveform will induce nucleation in an exposed perfluorocarbon droplet.

Development and application of a simplified radiative transport equation in water curtain systems

In this study, a simplified radiative transfer equation (RTE) for water curtain is introduced. The scattering phase function, asymmetric factor, single scattering albedo, and efficiency factors are investigated with non-gray and gray medium, respectively. The prediction values by a simplified equation are compared with previous results by the two-flux, P3 and F9 methods in non-gray medium. The deviations of reduced intensities are less than 10%. As the droplet size increases more than 100 μm, the asymmetry factor, scattering phase function, and scattering albedo are converged as 0.975, 0.992 and 0.501, respectively. Thus, a more simplified equation for the reduced intensity of radiation can be determined with the exponential function of optical depth.To correlate the relations between the flow characteristics of water curtain and the optical depth, the droplet mean diameter and the number density are analyzed with a modified gamma distribution function. In addition, the FTIR spectrometer is calibrated to obtain the spectral intensity in the thermal infrared and large droplet region.Finally, the important engineering parameters such as the mass flow rate, the droplet mean diameter, the number density, the optical depth, and the reduced intensity are systematically investigated. It can be predicted that optical depth (τ > 0.89), number density (N > O(4 × 106 m−3)), droplet mean radius (rm < 180 μm) and flow rate (Qflow > 1.2 kg/s) are determined to reduce the radiation intensity less than 50% for the selected water curtain nozzle in this study.

Modeling Condensation in Deep Convection

Abstract Cloud-scale models apply two drastically different methods to represent condensation of water vapor to form and grow cloud droplets. Maintenance of water saturation inside liquid clouds is assumed in the computationally efficient saturation adjustment approach used in most bulk microphysics schemes. When super- or subsaturations are allowed, condensation/evaporation can be calculated using the predicted saturation ratio and (either predicted or prescribed) mean droplet radius and concentration. The study investigates differences between simulations of deep unorganized convection applying a saturation adjustment condensation scheme (SADJ) and a scheme with supersaturation prediction (SPRE). A double-moment microphysics scheme with CCN activation parameterized as a function of the local vertical velocity is applied to compare cloud fields simulated applying SPRE and SADJ. Clean CCN conditions are assumed to demonstrate upper limits of the SPRE and SADJ difference. Microphysical piggybacking is used to extract the impacts with confidence. Results show a significant impact on deep convection dynamics, with SADJ featuring more cloud buoyancy and thus stronger updrafts. This leads to around a 3% increase of the surface rain accumulation in SADJ. Upper-tropospheric anvil cloud fractions are much larger in SPRE than in SADJ because of the higher ice concentrations and thus longer residence times of anvil particles in SPRE, as demonstrated by sensitivity tests. Higher ice concentrations in SPRE come from significantly larger ice supersaturations in strong convective updrafts that feature water supersaturations of several percent.

Improving intracellular uptake of 5-demethyltangeretin by food grade nanoemulsions

5-Demethyltangeretin (5DT) is a unique citrus flavonoid that has been shown to have anti-cancer effects, but its low water-solubility and poor oral bioavailability may limit its application as a nutraceutical. In this study, we utilized emulsion-based delivery systems to increase the bioavailability of 5DT and its uptake by intestinal cancer cells. Oil-in-water emulsions with different mean droplet radii (r=67, 125 and 203nm) were fabricated using high-pressure homogenization. The amount of 5DT absorbed by intestinal cancer cells was quantified by HPLC using an electrochemistry detector. The relative percentages of 5DT absorption compared to a reference emulsion (r=67nm) were: 5.9% (in water, crystal); 13.1% (in medium chain triglyceride (MCT), crystal); 30.6% (emulsion, r=203nm); and 92.9% (emulsion, r=125nm). A cytotoxicity assay showed that 5DT encapsulated in smaller droplets produced stronger growth inhibition than those in larger droplets, and much higher than those dispersed in bulk MCT or bulk water. 5DT encapsulated within emulsions with small droplet sizes (nanoemulsions) produced higher cellular absorption and lower cancer cell viability. Our results suggested that this type delivery system may be useful for the application of 5DT and other similar nutraceuticals in functional foods and beverages.

Homogeneity of the Subgrid-Scale Turbulent Mixing in Large-Eddy Simulation of Shallow Convection

Abstract This paper presents an approach to locally predict homogeneity of the subgrid-scale turbulent mixing in large-eddy simulation of shallow clouds applying double-moment warm-rain microphysics. The homogeneity of subgrid-scale mixing refers to the partitioning of the cloud water evaporation due to parameterized entrainment between changes of the mean droplet radius and changes of the mean droplet concentration. Homogeneous and extremely inhomogeneous mixing represent two limits of possible scenarios, where the droplet concentration and the mean droplet radius remains unchanged during the microphysical adjustment, respectively. To predict the subgrid-scale mixing scenario, the double-moment microphysics scheme is merged with the approach to delay droplet evaporation resulting from entrainment. Details of the new scheme and its application in the Barbados Oceanographic and Meteorological Experiment (BOMEX) shallow convection case are discussed. The simulated homogeneity of mixing varies significantly inside small convective clouds, from close to homogeneous to close to extremely inhomogeneous. The mean mixing characteristics become more homogeneous with height, reflecting increases of the mean droplet size and the mean turbulence intensity, both favoring homogeneous mixing. Model results are consistent with microphysical effects of entrainment and mixing deduced from field observations. Mixing close to homogeneous is predicted in volumes with the highest liquid water content (LWC) and strongest updraft at a given height, whereas mixing in strongly diluted volumes is typically close to extremely inhomogeneous. The simulated homogeneity of mixing has a small impact on mean microphysical characteristics. This result agrees with the previous study applying prescribed mixing scenarios and can be explained by the high humidity of the clear air involved in the subgrid-scale mixing.

Spectral width of premonsoon and monsoon clouds over Indo‐Gangetic valley

The combined effect of humidity and aerosol on cloud droplet spectral width (σ) in continental monsoon clouds is a topic of significant relevance for precipitation and radiation budgets over monsoon regions. The droplet spectral width in polluted, dry premonsoon conditions and moist monsoon conditions observed near the Himalayan Foothills region during Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX) is the focus of this study. Here σis small in premonsoon clouds developing from dry boundary layers. This is attributed to numerous aerosol particles and the absence/suppression of collision‐coalescence during premonsoon. For polluted and dry premonsoon clouds,σ is constant with height. In contrast to premonsoon clouds, σ in monsoon clouds increases with height irrespective of whether they are polluted or clean. The mean radius of polluted monsoon clouds is half that of clean monsoon clouds. In monsoon clouds, both mean radius and σ decreased with total cloud droplet number concentration (CDNC). The spectral widths of premonsoon clouds were independent of total droplet number concentrations, but both σ and mean radius decreased with small droplet (diameter &lt; 20 μm) number concentrations in the diluted part of the cloud. Observational evidence is provided for the formation of large droplets in the adiabatic regions of monsoon clouds. The number concentration of small droplets is found to decrease in the diluted cloud volumes that may be characterized by various spectral widths or mean droplet radii.