Effects Of Cloud Condensation Nuclei Research Articles

Explicitly Modeling the Effects of Cloud Condensation Nuclei on Warm Rain Initiation

Abstract A bin (or spectral) model is developed to investigate the sensitivity of warm rain initiation to cloud condensation nuclei (CCN). It explicitly represents CCN with a formula whose parameters come from the Twomey relationship (or CCN measurements). By seamlessly integrating CCN activation and drop collection with thousands of bins, the model can replicate the effect of CCN on rain initiation, providing a benchmark to test the process parameterizations in rain initiation. The model is used to simulate two extreme cases with CCN parameters of maritime and continental clouds, respectively, where other actual cases usually lie between these two extreme cases. Its simulations show that rain can initiate within half an hour or less as observed in cumulus clouds. The fast rain initiation modeled is attributed mainly to a new process: the condensational conversion of cloud drops to raindrops via collision–coalescence initiators (or drops with radius between 28 and 100 μm). Since the new process is more important in rain initiation than the autoconversion of cloud drops to raindrops when large CCN exist, it is suggested that the process be parameterized into the weather and climate models to better represent CCN and subsequently remove the common bias of “too dense clouds.” Significance Statement The current weather and climate models represent aerosols via implicit parameterizations and have a bias of “too dense clouds.” Their implicit parameterizations of aerosols usually overlook (or misrepresent) some cloud processes. In this paper and its preceding part (Zeng and Li 2020) we proposed a new framework to explicitly parameterize one subset of aerosols: cloud condensation nuclei (CCN). To embody an explicit parameterization of CCN, we still need quantitative information to connect CCN activation and rain initiation, which motivates this study. In the study we developed an accurate microphysical model to simulate the growth of small CCN to large raindrops, providing information on the sensitivity of rain initiation to CCN. We performed many sensitivity simulations and found the condensational conversion of cloud drops to raindrops via collision–coalescence initiators is a vital process in warm rain initiation. Since the process has been overlooked by all the weather and climate models, the study suggests that the process be introduced in the weather and climate models to properly represent the fast warm rain initiation observed and subsequently remove the bias of “too dense clouds.”

Numerical Simulations of Cloud Number Concentration and Ice Nuclei Influence on Cloud Processes and Seeding Effects

Aerosols, through cloud condensation nuclei (CCN) or ice nuclei (IN), affect cloud microphysics. With increasing concentrations of aerosols, it is important to consider the impact of IN along with CCN on clouds and precipitation in numerical simulations; further, aerosols may also affect the weather-modification seeding effect. On the basis of the observation of natural IN concentration and cloud-drop number concentrations, numerical sensitivity experiments for a snowfall case were designed to study the effects of parameters of IN and cloud number concentrations at the cloud base to consider the CCN effects on clouds and precipitation as well as weather-modification seeding effects. Generally, with smaller cloud-drop number concentration, the mass contents were much lower. With more ice nuclei, more ice crystals were able to nucleate, and additional snow particles were generated through ice crystals. Cloud-drop number concentrations heavily affected the location and amount of snowfall. During the 1e9 test, 2.4 mm was the highest reduction in the amount of snowfall; additionally, the amount of snowfall from the combined impacts of increased IN and cloud-drop number decreased in wide areas, and its maximum precipitation reduction exceeded 2.7 mm as well as up to 15% of the daily amount of snowfall. More IN reduced the artificial seeding effect, lowered the increase in snowfall in the center of the seeding, and lowered the reduction of snowfall in the reduction center of the seeding. With more IN, the seeding effect was able to shift approximately 0.6% from the 3.9% seeding effect of the control simulation.

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors.

Cloud drop number concentrations (Nd) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing Nd on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-Nd days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-Nd days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing Nd to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to Nd for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol–Nd relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of Nd.

Effect of cloud condensation nuclei concentration on a hail event with weak warm rain process in a semi-arid region of China

Although there are several studies on the effects of cloud condensation nuclei (CCN) concentration on convection, it requires more attention. A hail event in semi-arid China is simulated with four different CCN concentration levels, which correspond to the marine area, mid-continental, continental, and polluted background CCN concentrations. It was found that the auto-conversion of cloud water to rainwater is not significant in the simulated convection. The increase in CCN concentration was accompanied by a large number of graupel particles of smaller size, which consequently induced smaller rain droplets. It is shown that increasing CCN concentration changed the dominant average mass-weighted diameters of the graupel, hail particles and rain droplet. The number concentration of rain droplets increased with CCN concentration, corresponding to the significant evaporation during the falling process. Consequently, the maximum of rainfall on the ground did not increase. Additionally, increasing the CCN concentration does not have the same apparent impact on the size of hail particles.

Impacts of Aerosol and Environmental Conditions on Maritime and Continental Deep Convective Systems Using a Bin Microphysical Model

AbstractA series of model simulations were conducted to investigate the effects of cloud condensation nuclei (CCN) loading and convective available potential energy (CAPE) on tropical maritime and midlatitude continental deep convection. Dynamical downscaling from global aerosol reanalysis was used to represent aerosol fields for the two convective regimes. We describe a control run and multiple sensitivity experiments using a limited‐area model, employing spectral‐bin cloud microphysics. The CCN loading is perturbed between the target maritime and continental conditions, roughly 40–2,000 cm−3 at 850 hPa and 1% supersaturation. Surface precipitation rates monotonically increase with increasing CCN loading for both the maritime and continental situations, while these monotonic increases are disrupted in the simulations with reduced CAPE. The increase in precipitation is in the form of convective precipitation, at the expense of stratiform precipitation. CCN increases promote increases in supercooled cloud water, in agreement with previous modeling studies. However, in the simulations investigated herein, the changes in supercooled water have different impacts on the cloud microphysics in the maritime and continental simulations. Increased supercooled water contents lead to more hail and less graupel in the continental simulation. For the maritime simulation, enhanced supercooled cloud water contents promote an increase in graupel since little or no hail is produced. This distinction is due to the difference in relative magnitudes and peak altitudes of supercooled water and snow amounts, which is further attributable to moisture and dynamical differences in the two cases.

Lagrangian condensation microphysics with Twomey CCN activation

Abstract. We report the development of a novel Lagrangian microphysics methodology for simulations of warm ice-free clouds. The approach applies the traditional Eulerian method for the momentum and continuous thermodynamic fields such as the temperature and water vapor mixing ratio, and uses Lagrangian super-droplets to represent condensed phase such as cloud droplets and drizzle or rain drops. In other applications of the Lagrangian warm-rain microphysics, the super-droplets outside clouds represent unactivated cloud condensation nuclei (CCN) that become activated upon entering a cloud and can further grow through diffusional and collisional processes. The original methodology allows for the detailed study of not only effects of CCN on cloud microphysics and dynamics, but also CCN processing by a cloud. However, when cloud processing is not of interest, a simpler and computationally more efficient approach can be used with super-droplets forming only when CCN is activated and no super-droplet existing outside a cloud. This is possible by applying the Twomey activation scheme where the local supersaturation dictates the concentration of cloud droplets that need to be present inside a cloudy volume, as typically used in Eulerian bin microphysics schemes. Since a cloud volume is a small fraction of the computational domain volume, the Twomey super-droplets provide significant computational advantage when compared to the original super-droplet methodology. Additional advantage comes from significantly longer time steps that can be used when modeling of CCN deliquescence is avoided. Moreover, other formulation of the droplet activation can be applied in case of low vertical resolution of the host model, for instance, linking the concentration of activated cloud droplets to the local updraft speed. This paper discusses the development and testing of the Twomey super-droplet methodology, focusing on the activation and diffusional growth. Details of the activation implementation, transport of super-droplets in the physical space, and the coupling between super-droplets and the Eulerian temperature and water vapor field are discussed in detail. Some of these are relevant to the original super-droplet methodology as well and to the ice phase modeling using the Lagrangian approach. As a computational example, the scheme is applied to an idealized moist thermal rising in a stratified environment, with the original super-droplet methodology providing a benchmark to which the new scheme is compared.

Comparison of aerosol effects on simulated spring and summer hailstorm clouds

Numerical simulations are carried out to investigate the effect of cloud condensation nuclei (CCN) concentrations on microphysical processes and precipitation characteristics of hailstorms. Two hailstorm cases are simulated, a spring case and a summer case, in a semiarid region of northern China, with the Regional Atmospheric Modeling System. The results are used to investigate the differences and similarities of the CCN effects between spring and summer hailstorms. The similarities are: (1) The total hydrometeor mixing ratio decreases, while the total ice-phase mixing ratio enhances, with increasing CCN concentration; (2) Enhancement of the CCN concentration results in the production of a greater amount of small-sized hydrometeor particles, but a lessening of large-sized hydrometeor particles; (3) As the CCN concentration increases, the supercooled cloud water and rainwater make a lesser contribution to hail, while the ice-phase hydrometeors take on active roles in the growth of hail; (4) When the CCN concentration increases, the amount of total precipitation lessens, while the role played by liquid-phase rainfall in the amount of total precipitation reduces, relatively, compared to that of ice-phase precipitation. The differences between the two storms include: (1) An increase in the CCN concentration tends to reduce pristine ice mixing ratios in the spring case but enhance them in the summer case; (2) Ice-phase hydrometeor particles contribute more to hail growth in the spring case, while liquid water contributes more in the summer case; (3) An increase in the CCN concentration has different effects on surface hail precipitation in different seasons.

Effects of cloud condensation nuclei and ice nucleating particles on precipitation processes and supercooled liquid in mixed-phase orographic clouds

Abstract. How orographic mixed-phase clouds respond to the change in cloud condensation nuclei (CCN) and ice nucleating particles (INPs) are highly uncertain. The main snow production mechanism in warm and cold mixed-phase orographic clouds (referred to as WMOCs and CMOCs, respectively, distinguished here as those having cloud tops warmer and colder than −20 °C) could be very different. We quantify the CCN and INP impacts on supercooled water content, cloud phases, and precipitation for a WMOC case and a CMOC case, with sensitivity tests using the same CCN and INP concentrations between the WMOC and CMOC cases. It was found that deposition plays a more important role than riming for forming snow in the CMOC case, while the role of riming is dominant in the WMOC case. As expected, adding CCN suppresses precipitation, especially in WMOCs and low INPs. However, this reverses strongly for CCN of 1000 cm−3 and larger. We found a new mechanism through which CCN can invigorate mixed-phase clouds over the Sierra Nevada and drastically intensify snow precipitation when CCN concentrations are high (1000 cm−3 or higher). In this situation, more widespread shallow clouds with a greater amount of cloud water form in the Central Valley and foothills west of the mountain range. The increased latent heat release associated with the formation of these clouds strengthens the local transport of moisture to the windward slope, invigorating mixed-phase clouds over the mountains, and thereby producing higher amounts of snow precipitation. Under all CCN conditions, increasing the INPs leads to decreased riming and mixed-phase fraction in the CMOC as a result of liquid-limited conditions, but has the opposite effects in the WMOC as a result of ice-limited conditions. However, precipitation in both cases is increased by increasing INPs due to an increase in deposition for the CMOC but enhanced riming and deposition in the WMOC. Increasing the INPs dramatically reduces supercooled water content and increases the cloud glaciation temperature, while increasing CCN has the opposite effect with much smaller significance.

Effect of aerosol concentration and absorbing aerosol on the radiation fog life cycle

Analogous to cloud formation, the formation and life cycle of fogs is largely influenced by aerosol particles. The objective of this work is to analyze how changes in aerosol properties affect the fog life cycle, with special emphasis on how droplet concentrations change with cloud condensation nuclei (CCN) concentrations and on the effect that absorbing black carbon (BC) particles have on fog dissipation. For our simulation case study, we chose a typical fall time radiation fog at mid-latitudes (45° north) in fairly highly polluted conditions. Our results show that CCN concentrations have a strong influence on the fog lifetime. This is because the immediate effect of CCN on cloud droplet number concentrations (CDNC) is enhanced through two positive feedback loops: (1) Higher CDNC leads to more radiative cooling at the fog top, which leads to even stronger activation and (2) if CDNC is higher, the average droplet size is smaller, which slows down droplet removal through sedimentation. The effect that radiation fogs have on solar surface irradiation is large – the daily mean can change by 50% if CCN concentrations are doubled or halved (considering a reference CCN mixing ratio of 800 #/mg). With the same changes in CCN, the total fog lifetime increases 160 min or decreases 65 min, respectively. Although BC has a noticeable effect on fog height and dissipation time, its relative effect compared to CCN is small, even if BC concentrations are high. The fog formation is very sensitive to initial meteorological conditions which may be altered considerably if fog was present the previous day. This effect was neglected here, and future simulations, which span several days, may thus be a valuable extension of this study.

A global satellite view of the seasonal distribution of mineral dust and its correlation with atmospheric circulation

Aerosols make a considerable contribution to the climate system through their radiative and cloud condensation nuclei effects, which underlines the need for understanding the origin of aerosols and their transport pathways. Seasonal distribution of mineral dust around the globe and its correlation with atmospheric circulation is investigated using satellite data, and meteorological data from ECMWF. The most important sources of dust are located in North Africa, the Middle East and Southwest Asia with an observed summer maximum, and East Asia with a spring peak. Maximum dust activity over North Africa and the Middle East in summer is attributed to dry convection associated with the summertime low-pressure system, while unstable weather and dry conditions are responsible for the spring peak in dust emission in East Asia. Intercontinental transport of mineral dust by atmospheric circulation has been observed, including trans-Atlantic transport of North African dust, trans-Pacific transport of Asian dust, and transport of dust from the Middle East across the Indian Ocean. The extent of African dust over the Atlantic Ocean and its latitudinal variation with season is related to the large-scale atmospheric circulation, including seasonal changes in the position of the intertropical convergence zone (ITCZ) and variation of wind patterns. North African aerosols extend over longer distances across the North Atlantic in summer because of greater dust emission, an intensified easterly low level jet (LLJ) and strengthening of the Azores-Bermuda anticyclonic circulation. Transport of East Asian aerosol is facilitated by the existence of a LLJ that extends from East Asia to the west coast of North America.

A modeling study of ice formation affected by aerosols

This study investigates the effects of cloud condensation nuclei (CCN) and ice nuclei (IN) on ice formation in mixed‐phase clouds using an adiabatic parcel model. The simulations with lower updrafts represent mixed‐phase stratiform clouds, and those with higher updrafts represent deep convective clouds. Increasing CCN concentration can lead to more ice crystals with smaller sizes, but does not affect the height of freezing nucleation at lower updrafts. At higher updrafts, ice number concentration is more sensitive to CCN, and CCN effect on ice nucleation height is also more noticeable. This study also investigates the effects of IN properties (number concentration, size, contact angle) on ice formation assuming the immersion freezing mechanism. At very low IN number concentration, ice nucleation is dominated by homogeneous freezing and ice number concentration is relatively high. As IN number concentration is increased, ice number concentration decreases because both heterogeneous and homogeneous freezing processes occur. A mixed‐phase layer extends up to the height for homogeneous freezing and there is a competition between the two freezing processes. As IN number concentration is further increased, ice number concentration increases because heterogeneous freezing dominates ice nucleation. IN number concentration needs to be higher for heterogeneous freezing to dominate ice nucleation at higher updrafts and lower at lower updrafts. Increasing IN size and contact coefficient also increases the contribution of heterogeneous freezing to ice nucleation. Finally, spheroids are used to represent columnar and plate‐like ice crystals. CCN and IN effects are not dependent on the assumption of ice crystal shapes.

Aerosol Effects on Simulated Storm Electrification and Precipitation in a Two-Moment Bulk Microphysics Model

Abstract The effects of cloud condensation nuclei (CCN) concentrations are found to strongly affect the microphysical and electrical evolution of a numerically simulated small multicell storm. The simulations reproduce the well-known effects of updraft invigoration and delay of precipitation formation as increasing CCN from low to intermediate concentrations causes droplet sizes to decrease. Peak updrafts increased from 16 m s−1 at the lowest CCN to a maximum of 21–22 m s−1 at moderate CCN, where condensation latent heating is maximized. The transition from low to high CCN first maximizes warm-rain production before switching over to the ice process as the dominant precipitation mechanism. Average graupel density stays fairly high and constant at lower CCN, but then drops monotonically at higher CCN concentration, although high CCN also foster the appearance of small regions of larger, high-density graupel with high simulated radar reflectivity. Graupel production increases monotonically as CCN concentration rises from 50 to about 2000 cm−3. The lightning response is relatively weak until the Hallett–Mossop rime-splintering ice multiplication becomes more active at CCN > 700 cm−3. At very high CCN concentrations (>2000 cm−3), graupel production decreases slowly, but lightning activity drops dramatically when the parameterization of Hallett–Mossop rime-splintering ice multiplication is based on the number of large cloud droplets collected by graupel. Conversely, lightning activity remains steady at extremely high CCN concentration when the Hallett–Mossop parameterization is based simply on the rate of rime mass accumulation. The results lend support to the aerosol hypothesis as applied to lightning production, whereby greater CCN concentration tends to lead to greater lightning activity, but with a large sensitivity to ice multiplication.

Can aerosols influence deep tropical convection? Aerosol indirect effects in the Hector island thunderstorm

AbstractThis article addresses the effects of cloud condensation nuclei on the evolution of an intense tropical convective system, known as Hector, using data taken from the ACTIVE and TWP‐ICE field campaigns, which were conducted in 2005 and 2006. The Hector thunderstorms were observed in a variety of aerosol conditions so the data serve as an ideal dataset to test whether aerosols have a significant impact on the evolution of convective clouds and precipitation. We find evidence for an aerosol effect on the storm's properties, which are reproduced with a state‐of‐the‐art mesoscale cloud‐resolving model. Including the measured aerosol concentration within the model is shown to improve the fractions skill‐score metric for every case presented in the article, thus giving us confidence that the deep convection observed during the period was indeed influenced by the aerosol entering the storm's inflow. However, we do not find a general relationship for the way aerosols affect properties such as cloud‐top height, precipitation or radiative properties, as has been suggested in previous work. The reasons for this appear to be because of the nonlinearity of interactions between neighbouring cells and because of the variability in the meteorological profiles of temperature, wind and humidity.

Lidar investigation of aerosol–cloud–precipitation interactions over a tropical monsoon environment: Recharging of atmosphere

In this paper, we present the results of the analysis of aerosol/cloud backscattered signals recorded with a state-of-the-art LIDAR at a tropical urban station, Pune in India. The study reveals that a major portion of cloud condensation nuclei (CCN) within the cloud cells is contributed by the sub-cloud region. Cloud/rain scavenging reduces the CCN concentration within the saturated zone. Cloud dissipation followed by drizzle is explained based on increased local atmospheric stability. Delay in the production of fresh CCN and associated cloud formation is observed after the wet removal – a phenomenon called “Recharging of the Atmosphere”. A substantial effect of CCNs on the growth and dissipation of clouds and the subsequent changes in the local hydrological cycle are elucidated by some novel approach.

The scientific basis for a satellite mission to retrieve CCN concentrations and their impacts on convective clouds

Abstract. The cloud-mediated aerosol radiative forcing is widely recognized as the main source of uncertainty in our knowledge of the anthropogenic forcing on climate. The current challenges for improving our understanding are (1) global measurements of cloud condensation nuclei (CCN) in the cloudy boundary layer from space, and (2) disentangling the effects of aerosols from the thermodynamic and meteorological effects on the clouds. Here, we present a new conceptual framework to help us overcome these two challenges, using relatively simple passive satellite measurements in the visible and infared (IR). The idea is to use the clouds themselves as natural CCN chambers by retrieving simultaneously the number of activated aerosols at cloud base, Na, and the cloud base updraft speed. The Na is obtained by analyzing the distribution of cloud drop effective radius in convective elements as a function of distance above cloud base. The cloud base updraft velocities are estimated by double stereoscopic viewing and tracking of the evolution of cloud surface features just above cloud base. In order to resolve the vertical dimension of the clouds, the field of view will be 100 m for the microphysical retrievals, and 50 m for the stereoscopic measurements. The viewing geometry will be eastward and 30 degrees off nadir, with the Sun in the back at 30 degrees off zenith westward, requiring a Sun-synchronous orbit at 14 LST. Measuring simultaneously the thermodynamic environment, the vertical motions of the clouds, their microstructure and the CCN concentration will allow separating the dynamics from the CCN effects. This concept is being applied in the proposed satellite mission named Clouds, Hazards and Aerosols Survey for Earth Researchers (CHASER).

Aerosol impacts on clouds and precipitation in eastern China: Results from bin and bulk microphysics

Using the Weather Research and Forecasting model coupled with a spectral‐bin microphysics (“SBM”) and measurements from the Atmospheric Radiation Measurement Mobile Facility field campaign in China (AMF‐China), the authors examine aerosol indirect effects (AIE) in the typical cloud regimes of the warm and cold seasons in Southeast China: deep convective clouds (DCC) and stratus clouds (SC), respectively. Comparisons with a two‐moment bulk microphysics (“Bulk”) are performed to gain insights for improving bulk schemes in estimating AIE in weather and climate simulations. For the first time, measurements of aerosol and cloud properties acquired in China are used to evaluate model simulations to better understand aerosol impact on clouds in the southeast of China. It is found that changes in cloud condensation nuclei (CCN) concentration significantly change the timing of storms, the spatial and temporal distributions of precipitation, the frequency distribution of precipitation rate, as well as cloud base and top heights for the DCC, but not for the SC. Increasing CCN increases cloud droplet number (Nc) and mass concentrations, decreases raindrop number concentration, and delays the onset of precipitation. Compared with SBM, Bulk predicts much higher Ncand the opposite CCN effects on convection and heavy rain, stemming from the fixed CCN prescribed in Bulk. CCN have a significant effect on ice microphysical properties with SBM but not Bulk and different condensation/deposition freezing parameterizations employed could be the main reason. This study provided insights to further improve the bulk scheme to better account for aerosol‐cloud interactions in regional and global climate simulations, which will be the focus for a follow‐on paper.

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

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.

Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations

Abstract. Large cloud condensation nuclei (CCN) (e.g., aged dust particles and seasalt) cannot attain their equilibrium size during the typical timescale of cloud droplet activation. Cloud activation parameterizations applied to aerosol with a large fraction of large CCN often do not account for this limitation adequately and can give biased predictions of cloud droplet number concentration (CDNC). Here we present a simple approach to address this problem that can easily be incorporated into cloud activation parameterizations. This method is demonstrated with activation parameterizations based on the "population splitting" concept of Nenes and Seinfeld (2003); it is shown that accounting for large CCN effects eliminates a positive bias in CDNC where the aerosol dry geometric diameter is greater than 0.5 μm. The method proposed here can also be extended to include the water vapor depletion from pre-existing droplets and ice crystals in global and regional atmospheric models.

Simulation of the effects of increasing cloud condensation nuclei on mixed-phase clouds and precipitation of a front system

Increasing cloud condensation nuclei (CCN) concentration usually leads to increasing cloud albedo and decreasing precipitation for warm clouds but its effect on the precipitation of mixed-phase clouds is less clear. Here, a bulk-formula semi-two-moment mixed-phase cloud scheme is incorporated with a regional model to study this aspect on a front system associated with convection. Although this cloud scheme is comparably simpler than most detailed bin-resolving cloud schemes used in cloud resolving models, certain features of CCN effects are reasonably simulated. Results show that both the first and the second indirect effects are simulated and that ice-phase precipitation effectively removes cloud water from the upper troposphere, leading to weaker first indirect effects. Sensitivity simulations show that although increasing CCN number results in more cloud drops and ice, its effect on surface precipitation depends on the interplay between the decreased warm-rain production and the decreased/increased ice-phase precipitation. The increase in cloud drops consequently enhances the diffusional growth of ice particles in water-subsaturated environments but inhibit it in water-supersaturated environments. Moreover, the change in riming depends on the balance between the enhancement due to more cloud drops and the suppression due to smaller cloud drops. For the case studied here, the precipitation responds nonlinearly to CCN number change, causing precipitation decrease in high CCN concentration environments but showing no clear tendency in low CCN concentration environments.

Effects of prescribed initial cloud droplet spectra on convective cloud and precipitation developments under different thermodynamic conditions: A modeling and observational study

A two-dimensional cloud model with bin microphysics was used to investigate the effects of cloud condensation nuclei (CCN) concentrations and thermodynamic conditions on convective cloud and precipitation developments. Two different initial cloud droplet spectra were prescribed based on the total CCN concentrations of maritime (300 cm − 3 ) and continental (1000 cm − 3 ) air masses, and the model was run on eight thermodynamic conditions obtained from observational soundings. Six-hourly sounding data and 1-hourly precipitation data from two nearby weather stations in Korea were analyzed for the year 2002 to provide some observational support for the model results. For one small Convective Available Potential Energy (CAPE) (∼ 300 J kg − 1 ) sounding, the maritime and continental differences were incomparably large. The crucial difference was the production of ice phase hydrometeors in the maritime cloud and only water drops in the continental cloud. Ice phase hydrometeors and intrinsically large cloud drops of the maritime cloud eventually lead to significant precipitation. Meanwhile negligible precipitation developed from the continental cloud. For the three other small CAPE soundings, generally weak convective clouds developed but the maritime and continental clouds were of the same phases (both warm or both cold) and their differences were relatively small. Model runs with the four large CAPE (∼ 3000 J kg − 1 ) soundings demonstrated that the depth between the freezing level (FL) and the lifting condensation level (LCL) was crucial to determine whether a cloud becomes a cold cloud or not, which in turn was found to be a crucial factor to enhance cloud invigoration with the additional supply of freezing latent heat. For two large CAPE soundings, FL–LCL was so deep that penetration of FL was prohibitive, and precipitation was only mild in the maritime clouds and negligible in the continental clouds. Two other soundings of similarly large CAPE had small FL–LCL, and both the maritime and continental clouds became cold clouds. Precipitation was strong for both but much more so in the maritime clouds, while the maximum updraft velocity and the cloud top were slightly higher in continental clouds. Although limited to small CAPE cases, more precipitation for smaller FL–LCL for a selected group of precipitation and thermodynamic sounding data from Korea was in support of these model results in its tendency. These results clearly demonstrated that the CCN effects on cloud and precipitation developments critically depended on the given thermodynamic conditions and not just the CAPE but the entire structure of the thermodynamic profiles had to be taken into account.