scholarly journals Effect of hygroscopic seeding on warm rain clouds – numerical study using a hybrid cloud microphysical model

2010 ◽  
Vol 10 (7) ◽  
pp. 3335-3351 ◽  
Author(s):  
N. Kuba ◽  
M. Murakami
Keyword(s):  
Numerical Study ◽  
Cloud Condensation Nuclei ◽  
Convective Cloud ◽  
Droplet Growth ◽  
Hybrid Cloud ◽  
Stratiform Cloud ◽  
Air Mass ◽  
Warm Rain ◽  
Surface Rainfall ◽  
Model Combining

Abstract. The effect of hygroscopic seeding on warm rain clouds was examined using a hybrid cloud microphysical model combining a Lagrangian Cloud Condensation Nuclei (CCN) activation model, a semi-Lagrangian droplet growth model, and an Eulerian spatial model for advection and sedimentation of droplets. This hybrid cloud microphysical model accurately estimated the effects of CCN on cloud microstructure and suggested the following conclusions for a moderate continental air mass (an air mass with a large number of background CCN). (1) Seeding can hasten the onset of surface rainfall and increase the accumulated amount of surface rainfall if the amount and radius of seeding particles are appropriate. (2) The optimal radius of monodisperse particles to increase rainfall becomes larger with the increase in the total mass of seeding particles. (3) Seeding with salt micro-powder can hasten the onset of surface rainfall and increase the accumulated amount of surface rainfall if the amount of seeding particles is sufficient. (4) Seeding by a hygroscopic flare decreases rainfall in the case of large updraft velocity (shallow convective cloud) and increases rainfall slightly in the case of small updraft velocity (stratiform cloud). (5) Seeding with hygroscopic flares including ultra-giant particles (r>5 μm) hastens the onset of surface rainfall but may not significantly increase the accumulated surface rainfall amount. (6) Hygroscopic seeding increases surface rainfall by two kinds of effects: the "competition effect" by which large soluble particles prevent the activation of smaller particles and the "raindrop embryo effect" in which giant soluble particles can immediately become raindrop embryos. In some cases, one of the effects works, and in other cases, both effects work, depending on the updraft velocity and the amount and size of seeding particles.

scholarly journals Effect of hygroscopic seeding on warm rain clouds – numerical study using a hybrid cloud microphysical model

2009 ◽  
Vol 9 (6) ◽  
pp. 24145-24192
Author(s):  
N. Kuba ◽  
M. Murakami
Keyword(s):  
Numerical Study ◽  
Cloud Condensation Nuclei ◽  
Convective Cloud ◽  
Droplet Growth ◽  
Hybrid Cloud ◽  
Stratiform Cloud ◽  
Air Mass ◽  
Warm Rain ◽  
Surface Rainfall ◽  
Model Combining

Abstract. The effect of hygroscopic seeding on warm rain clouds was examined using a hybrid cloud microphysical model combining a Lagrangian cloud condensation nuclei (CCN) activation model, a semi-Lagrangian droplet growth model, and an Eulerian spatial model for advection and sedimentation of droplets. This hybrid cloud microphysical model accurately estimated the effects of CCN on cloud microstructure and suggested the following conclusions for a moderate continental air mass (an air mass with a large number of background CCN). (1) Seeding can hasten the onset of surface rainfall and increase the accumulated amount of surface rainfall if the amount and radius of seeding particles are appropriate. (2) The optimal radius of monodisperse particles to increase rainfall becomes larger with the increase in the total mass of seeding particles. (3) Seeding with salt micro-powder can hasten the onset of surface rainfall and increase the accumulated amount of surface rainfall if the amount of seeding particles is sufficient. (4) Seeding by a hygroscopic flare decreases rainfall in the case of large updraft velocity (shallow convective cloud) and increases rainfall slightly in the case of small updraft velocity (stratiform cloud). (5) Seeding with hygroscopic flares including ultra-giant particles (r>5 μm) hastens the onset of surface rainfall but may not significantly increase the accumulated surface rainfall amount. (6) Hygroscopic seeding increases surface rainfall by two kinds of effects: the ''competition effect'' by which large soluble particles prevent the activation of smaller particles and the ''raindrop embryo effect'' in which giant soluble particles can immediately become raindrop embryos. In some cases, one of the effects works, and in other cases, both effects work, depending on the updraft velocity and the amount and size of seeding particles.

scholarly journals Broadening of Cloud Droplet Spectra through Eddy Hopping: Turbulent Entraining Parcel Simulations

2018 ◽  
Vol 75 (10) ◽  
pp. 3365-3379 ◽  
Author(s):  
Gustavo C. Abade ◽  
Wojciech W. Grabowski ◽  
Hanna Pawlowska
Keyword(s):  
Droplet Size ◽  
Turbulent Mixing ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Droplet Growth ◽  
Size Spectrum ◽  
Entrainment Rate ◽  
The Mean ◽  
The Impact

This paper discusses the effects of cloud turbulence, turbulent entrainment, and entrained cloud condensation nuclei (CCN) activation on the evolution of the cloud droplet size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events modeled as a random process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet activation and growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate, CCN concentration, and the mean fraction of environmental air entrained in an event are all specified as independent external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. These are either unactivated CCN or cloud droplets that grow from activated CCN. The model accounts for the addition of environmental CCN into the cloud by entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using the classical linear relaxation to the mean model. We show that turbulence plays an important role in aiding entrained CCN to activate, and thus broadening the droplet size distribution. These findings are consistent with previous large-eddy simulations (LESs) that consider the impact of variable droplet growth histories on the droplet size spectra in small cumuli. The scheme developed in this work is ready to be used as a stochastic subgrid-scale scheme in LESs of natural clouds.

scholarly journals Broadening of Cloud Droplet Size Spectra by Stochastic Condensation: Effects of Mean Updraft Velocity and CCN Activation

2018 ◽  
Vol 75 (2) ◽  
pp. 451-467 ◽  
Author(s):  
Gaetano Sardina ◽  
Stéphane Poulain ◽  
Luca Brandt ◽  
Rodrigo Caballero
Keyword(s):  
Chemical Composition ◽  
Droplet Size ◽  
Isotropic Turbulence ◽  
Cloud Condensation Nuclei ◽  
Collision Probability ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Size Spectrum ◽  
Similar Reduction ◽  
Size Spectra

Abstract The authors study the condensational growth of cloud droplets in homogeneous isotropic turbulence by means of a large-eddy simulation (LES) approach. The authors investigate the role of a mean updraft velocity and of the chemical composition of the cloud condensation nuclei (CCN) on droplet growth. The results show that a mean constant updraft velocity superimposed onto a turbulent field reduces the broadening of the droplet size spectra induced by the turbulent fluctuations alone. Extending the authors’ previous results regarding stochastic condensation, the authors introduce a new theoretical estimation of the droplet size spectrum broadening that accounts for this updraft velocity effect. A similar reduction of the spectra broadening is observed when the droplets reach their critical size, which depends on the chemical composition of CCN. The analysis of the square of the droplet radius distribution, proportional to the droplet surface, shows that for large particles the distribution is purely Gaussian, while it becomes strongly non-Gaussian for smaller particles, with the left tail characterized by a peak around the haze activation radius. This kind of distribution can significantly affect the later stages of the droplet growth involving turbulent collisions, since the collision probability kernel depends on the droplet size, implying the need for new specific closure models to capture this effect.

scholarly journals Automated Mapping of Convective Clouds (AMCC) Thermodynamical, Microphysical, and CCN Properties from SNPP/VIIRS Satellite Data

2019 ◽  
Vol 58 (4) ◽  
pp. 887-902 ◽  
Author(s):  
Zhiguo Yue ◽  
Daniel Rosenfeld ◽  
Guihua Liu ◽  
Jin Dai ◽  
Xing Yu ◽  
...  
Keyword(s):  
Climate Models ◽  
Weather Forecasting ◽  
Meteorological Data ◽  
Cloud Condensation Nuclei ◽  
Convective Cloud ◽  
Cloud Base ◽  
Base Temperature ◽  
Cloud Drop ◽  
Automated Mapping ◽  
Convective Clouds

AbstractThe advent of the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi NPP (SNPP) satellite made it possible to retrieve a new class of convective cloud properties and the aerosols that they ingest. An automated mapping system of retrieval of some properties of convective cloud fields over large areas at the scale of satellite coverage was developed and is presented here. The system is named Automated Mapping of Convective Clouds (AMCC). The input is level-1 VIIRS data and meteorological gridded data. AMCC identifies the cloudy pixels of convective elements; retrieves for each pixel its temperature T and cloud drop effective radius re; calculates cloud-base temperature Tb based on the warmest cloudy pixels; calculates cloud-base height Hb and pressure Pb based on Tb and meteorological data; calculates cloud-base updraft Wb based on Hb; calculates cloud-base adiabatic cloud drop concentrations Nd,a based on the T–re relationship, Tb, and Pb; calculates cloud-base maximum vapor supersaturation S based on Nd,a and Wb; and defines Nd,a/1.3 as the cloud condensation nuclei (CCN) concentration NCCN at that S. The results are gridded 36 km × 36 km data points at nadir, which are sufficiently large to capture the properties of a field of convective clouds and also sufficiently small to capture aerosol and dynamic perturbations at this scale, such as urban and land-use features. The results of AMCC are instrumental in observing spatial covariability in clouds and CCN properties and for obtaining insights from such observations for natural and man-made causes. AMCC-generated maps are also useful for applications from numerical weather forecasting to climate models.

scholarly journals Direct Lagrangian tracking simulation of droplet growth in vertically developing cloud

2018 ◽  
Vol 18 (22) ◽  
pp. 16619-16630 ◽  
Author(s):  
Yuichi Kunishima ◽  
Ryo Onishi
Keyword(s):  
Cloud Condensation Nuclei ◽  
Ground Surface ◽  
Droplet Growth ◽  
Back Trajectory ◽  
Lagrangian Statistics ◽  
Lagrangian Simulation ◽  
Comparison Results ◽  
Snow Crystals ◽  
Lagrangian Tracking ◽  
Condensational Growth

Abstract. We present a direct Lagrangian simulation that computes key warm-rain processes in a vertically developing cloud, including cloud condensation nuclei (CCN) activation, condensational growth, collisional growth, and droplet gravitational settling. This simulation, which tracks the motion and growth of individual particles, is applied to a kinematic simulation of an extremely vertically elongated quasi-one-dimensional domain, after which the results are compared with those obtained from a spectral-bin model, which adopts the conventional Eulerian framework. The comparison results, which confirm good bulk statistical agreement between the Lagrangian and conventional spectral-bin simulations, also show that the Lagrangian simulation is free from the numerical diffusion found in the spectral-bin simulation. After analyzing the Lagrangian statistics of the surface raindrops that reach the ground surface, back-trajectory scrutiny reveals that the Lagrangian statistics of surface raindrops contains the information about the sky where the raindrops grow like the shape does for snow crystals.

scholarly journals Impact of interannual variations in sources of insoluble aerosol species on orographic precipitation over California's central Sierra Nevada

2015 ◽  
Vol 15 (11) ◽  
pp. 6535-6548 ◽  
Author(s):  
J. M. Creamean ◽  
A. P. Ault ◽  
A. B. White ◽  
P. J. Neiman ◽  
F. M. Ralph ◽  
...  
Keyword(s):  
Long Range ◽  
Sierra Nevada ◽  
Biomass Burning ◽  
Water Resource Management ◽  
Cloud Condensation Nuclei ◽  
Convective Cloud ◽  
Orographic Precipitation ◽  
Cloud Systems ◽  
Precipitation Processes ◽  
Aerosol Sources

Abstract. Aerosols that serve as cloud condensation nuclei (CCN) and ice nuclei (IN) have the potential to profoundly influence precipitation processes. Furthermore, changes in orographic precipitation have broad implications for reservoir storage and flood risks. As part of the CalWater field campaign (2009–2011), the variability and associated impacts of different aerosol sources on precipitation were investigated in the California Sierra Nevada using an aerosol time-of-flight mass spectrometer for precipitation chemistry, S-band profiling radar for precipitation classification, remote sensing measurements of cloud properties, and surface meteorological measurements. The composition of insoluble residues in precipitation samples collected at a surface site contained mostly local biomass burning and long-range-transported dust and biological particles (2009), local sources of biomass burning and pollution (2010), and long-range transport (2011). Although differences in the sources of insoluble residues were observed from year to year, the most consistent source of dust and biological residues were associated with storms consisting of deep convective cloud systems with significant quantities of precipitation initiated in the ice phase. Further, biological residues were dominant (up to 40%) during storms with relatively warm cloud temperatures (up to −15 °C), supporting the important role bioparticles can play as ice nucleating particles. On the other hand, lower percentages of residues from local biomass burning and pollution were observed over the three winter seasons (on average 31 and 9%, respectively). When precipitation quantities were relatively low, these insoluble residues most likely served as CCN, forming smaller more numerous cloud droplets at the base of shallow cloud systems, and resulting in less efficient riming processes. Ultimately, the goal is to use such observations to improve the mechanistic linkages between aerosol sources and precipitation processes to produce more accurate predictive weather forecast models and improve water resource management.

scholarly journals Cloud condensation nuclei measurements in the marine boundary layer of the Eastern Mediterranean: CCN closure and droplet growth kinetics

2009 ◽  
Vol 9 (18) ◽  
pp. 7053-7066 ◽  
Author(s):  
A. Bougiatioti ◽  
C. Fountoukis ◽  
N. Kalivitis ◽  
S. N. Pandis ◽  
A. Nenes ◽  
...  
Keyword(s):  
Size Distribution ◽  
Growth Kinetics ◽  
Eastern Mediterranean ◽  
Cloud Condensation Nuclei ◽  
Bulk Composition ◽  
Organic Content ◽  
Water Soluble ◽  
Aerosol Size Distribution ◽  
Droplet Growth ◽  
Condensation Nuclei

Abstract. Measurements of cloud condensation nuclei (CCN) concentrations (cm−3) between 0.2 and 1.0% supersaturation, aerosol size distribution and chemical composition were performed at a remote marine site in the eastern Mediterranean, from September to October 2007 during the FAME07 campaign. Most of the particles activate at ~0.6% supersaturation, characteristic of the aged nature of the aerosol sampled. Application of Köhler theory, using measurements of bulk composition, size distribution, and assuming that organics are insoluble resulted in agreement between predicted and measured CCN concentrations within 7±11% for all supersaturations, with a tendency for CCN underprediction (16±6%; r2=0.88) at the lowest supersaturations (0.21%). Including the effects of the water-soluble organic fraction (which represent around 70% of the total organic content) reduces the average underprediction bias at the low supersaturations, resulting in a total closure error of 0.6±6%. Using threshold droplet growth analysis, the growth kinetics of ambient CCN is consistent with NaCl calibration experiments; hence the presence of aged organics does not suppress the rate of water uptake in this environment. The knowledge of the soluble salt fraction is sufficient for the description of the CCN activity in this area.

scholarly journals Rain Initiation Time in Turbulent Warm Clouds

2006 ◽  
Vol 45 (4) ◽  
pp. 591-599 ◽  
Author(s):  
Gregory Falkovich ◽  
Mikhail G. Stepanov ◽  
Marija Vucelja
Keyword(s):  
Numerical Simulation ◽  
Numerical Scheme ◽  
Field Model ◽  
Water Mass ◽  
Cloud Condensation Nuclei ◽  
Mean Field ◽  
Droplet Growth ◽  
Initiation Time ◽  
Condensation Nuclei ◽  
Mean Field Model

Abstract A mean field model is presented that describes droplet growth resulting from condensation and collisions and droplet loss resulting from fallout. The model allows for an effective numerical simulation. The numerical scheme that is conservative in water mass and keeps accurate count of the number of droplets is applied, and the way in which the rain initiation time depends on different parameters is studied. In particular, it is shown that the rain initiation time depends nonmonotonically (has a minimum) on the number of cloud condensation nuclei. Also presented is a simple model that allows one to estimate the rain initiation time for turbulent clouds with an inhomogeneous concentration of cloud condensation nuclei. It is argued that by overseeding even a part of a cloud by small hygroscopic nuclei one can substantially delay the onset of precipitation.

scholarly journals A Satellite-Based Parameter to Monitor the Aerosol Impact on Convective Clouds

2007 ◽  
Vol 46 (5) ◽  
pp. 660-666 ◽  
Author(s):  
Itamar M. Lensky ◽  
Ron Drori
Keyword(s):  
Forest Fires ◽  
Land Surface ◽  
Cloud Condensation Nuclei ◽  
Urban Air Pollution ◽  
Sensible Heat Flux ◽  
Urban Pollution ◽  
Convective Cloud ◽  
Cloud Base ◽  
Suppression Effect ◽  
Convective Clouds

Abstract A method to monitor the aerosol impact on convective clouds using satellite data is presented. The impacts of forest fires and highly polluting megacities on cloud precipitation formation processes are quantified by the vertical extent above cloud base to which convective cloud tops have to develop for onset of precipitation in terms of temperature difference D15. Large D15 is a manifestation of the precipitation suppression effect of small cloud condensation nuclei aerosols that elevate the altitude where effective precipitation processes are initiated. A warmer land surface with a greater sensible heat flux that increases the updraft velocity at cloud base may also contribute to the same effect. Therefore, D15 is greater for clouds that develop over more polluted and/or warmer surfaces that result from smoke and urban pollution and/or urban heat island, respectively. The precipitation suppression effects of both smoke from forest fires and urban effects can be vividly seen in a case study over Southeast Asia. Typical values of D15 are 1°–6°C for tropical maritime clouds, 8°–15°C for tropical clouds over land, 16°–26°C for urban air pollution, and 18°–39°C for clouds ingesting smoke from forest fires.

scholarly journals Aerosol measurements during COPE: composition, size, and sources of CCN and INPs at the interface between marine and terrestrial influences

2016 ◽  
Vol 16 (18) ◽  
pp. 11687-11709 ◽  
Author(s):  
Jonathan W. Taylor ◽  
Thomas W. Choularton ◽  
Alan M. Blyth ◽  
Michael J. Flynn ◽  
Paul I. Williams ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Convective Cloud ◽  
Cloud Formation ◽  
Convective Precipitation ◽  
Cloud Base ◽  
Sea Spray ◽  
Cloud Drop ◽  
Aerosol Mass ◽  
Order Of Magnitude ◽  
The Uk

Abstract. Heavy rainfall from convective clouds can lead to devastating flash flooding, and observations of aerosols and clouds are required to improve cloud parameterisations used in precipitation forecasts. We present measurements of boundary layer aerosol concentration, size, and composition from a series of research flights performed over the southwest peninsula of the UK during the COnvective Precipitation Experiment (COPE) of summer 2013. We place emphasis on periods of southwesterly winds, which locally are most conducive to convective cloud formation, when marine air from the Atlantic reached the peninsula. Accumulation-mode aerosol mass loadings were typically 2–3 µg m−3 (corrected to standard cubic metres at 1013.25 hPa and 273.15 K), the majority of which was sulfuric acid over the sea, or ammonium sulfate inland, as terrestrial ammonia sources neutralised the aerosol. The cloud condensation nuclei (CCN) concentrations in these conditions were  ∼  150–280 cm−3 at 0.1 % and 400–500 cm−3 at 0.9 % supersaturation (SST), which are in good agreement with previous Atlantic measurements, and the cloud drop concentrations at cloud base ranged from 100 to 500 cm−3. The concentration of CCN at 0.1 % SST was well correlated with non-sea-salt sulfate, meaning marine sulfate formation was likely the main source of CCN. Marine organic aerosol (OA) had a similar mass spectrum to previous measurements of sea spray OA and was poorly correlated with CCN. In one case study that was significantly different to the rest, polluted anthropogenic emissions from the southern and central UK advected to the peninsula, with significant enhancements of OA, ammonium nitrate and sulfate, and black carbon. The CCN concentrations here were around 6 times higher than in the clean cases, and the cloud drop number concentrations were 3–4 times higher. Sources of ice-nucleating particles (INPs) were assessed by comparing different parameterisations used to predict INP concentrations, using measured aerosol concentrations as input. The parameterisations based on total aerosol produced INP concentrations that agreed within an order of magnitude with measured first ice concentrations at cloud temperatures as low as −12 °C. Composition-specific parameterisations for mineral dust, fluorescent particles, and sea spray OA were 3–4 orders of magnitude lower than the measured first ice concentrations, meaning a source of INPs was present that was not characterised by our measurements and/or one or more of the composition-specific parameterisations greatly underestimated INPs in this environment.

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