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Comparison of Simulations of Updraft Mass Fluxes and Their Response to Increasing Aerosol Concentration between a Bin Scheme and a Bulk Scheme in a Deep-Convective Cloud System

Comparison of Simulations of Updraft Mass Fluxes and Their Response to Increasing Aerosol... Hindawi Advances in Meteorology Volume 2019, Article ID 9292535, 29 pages https://doi.org/10.1155/2019/9292535 Research Article Comparison of Simulations of Updraft Mass Fluxes and Their Response to Increasing Aerosol Concentration between a Bin Scheme and a Bulk Scheme in a Deep-Convective Cloud System 1 2 3 4 Seoung Soo Lee , Chang-Hoon Jung, Sen Chiao , Junshik Um , 5 6 Yong-Sang Choi, and Won Jun Choi Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, Maryland, USA Department of Health Management, Kyungin Women’s University, Incheon, Republic of Korea Center for Applied Atmospheric Research and Education, San Jose State University, San Jose, California, USA Department of Atmospheric Sciences, Pusan National University, Busan, Republic of Korea Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea National Institute of Environmental Research, Incheon, Republic of Korea Correspondence should be addressed to Seoung Soo Lee; cumulss@gmail.com Received 21 December 2018; Revised 19 February 2019; Accepted 12 March 2019; Published 12 June 2019 Academic Editor: Pedro Jime´nez-Guerrero Copyright © 2019 Seoung Soo Lee et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Key microphysical processes whose parameterizations have substantial impacts on the simulation of updraft mass fluxes and their response to aerosol are investigated in this study. For this investigation, comparisons of these parameterizations are made between a bin scheme and a bulk scheme. -ese comparisons show that the differences in the prediction of cloud droplet number concentration (CDNC) between the two schemes determine whether aerosol-induced invigoration of updrafts or convection occurs. While the CDNC prediction leads to aerosol-induced invigoration of updrafts and an associated 20% increase in the peak value of the updraft-mass-flux vertical profile in the bin scheme, it leads to aerosol-induced suppression of updrafts and an associated 7% decrease in the peak value in the bulk scheme. -e comparison also shows that the differences in ice processes, in particular, in the snow loading lead to the different vertical patterns of the updraft-mass-flux profile, which is represented by the peak value and its altitude, between the schemes. Higher loading of snow leads to around 20–30% higher mean peak value and its around 40% higher altitude in the bin scheme than in the bulk scheme. When differences in the CDNC prediction and ice processes are removed, differences in the invigoration and the vertical pattern disappear between the schemes. However, despite this removal, differences in the magnitude of updraft mass fluxes still remain between the schemes. Associated with this, the peak value is around 10% different between the schemes. Also, after the removal, there are differences in the magnitude between cases with different aerosol concentrations for each scheme. Associated with this, the peak value is also around 10% different between those cases for each scheme. -e differences between the cases with different aerosol concentrations for each scheme are generated by different evaporative cooling and different intensity of gust fronts between those cases. -e remaining differences between the schemes are generated by different treatments of collection and sedimentation processes. tropopause and are well-known modulators of global 1. Introduction dynamic, hydrological, and energy circulations since Recent studies have shown that convective clouds, which these clouds form (1) the cloud regime that regulates a include deep convective clouds, are substantially affected significant portion of global momentum and shortwave by aerosol-cloud interactions and associated feedbacks and longwave radiation and (2) generates the largest between increasing aerosol concentration, microphysics, portion of the global precipitation [8–10]. Hence, the and dynamics [1–7]. -ese deep clouds grow to reach the interactions between aerosol and clouds and associated 2 Advances in Meteorology comparison, it is well accepted that there are two types of feedbacks in deep clouds are essential for understanding climate change. microphysics schemes, which are bin schemes and bulk schemes [21]. It is believed that there are more substantial or -e invigoration of convection is a well-known repre- sentation of the feedbacks between increasing aerosol greater differences in the representation of microphysics concentration, microphysics, and dynamics in deep clouds between these schemes than among bin schemes themselves [11, 12]. It has been suggested that an aerosol perturbation or bulk schemes themselves since bin schemes and bulk (or increasing aerosol concentration) enhances freezing and schemes have fundamental differences between them cloud buoyancy, which leads to the invigoration of con- [21, 25–27]. A good example of these fundamental differ- vection that accompanies increases in the intensity of up- ences is that, in bin schemes, hydrometeor size distributions are explicitly predicted, while in bulk schemes, assumed drafts and cloud top heights [11] Figure 1). However, there is a wide variety of reported responses of deep convective forms of the distributions are used. -is motivates this study to focus on comparisons between a bin scheme and a bulk clouds to aerosol perturbations in simulations [3, 6, 12, 15–17]. For example, some studies have shown scheme but not on those between bin schemes or between bulk schemes. For these comparisons, we try to select a strong aerosol-induced invigoration for both cloud systems and single clouds, while others have not even for identical representative bin scheme and a representative bulk scheme cases [3, 12, 17]. Aerosol-induced invigoration is well known to draw representative and preliminary, though not general, to be dependent on environmental and aerosol conditions conclusions from the comparisons. -e reality is that [14, 18–20]. However, each of these identical cases has comparisons between bin schemes themselves or between identical environmental and aerosol conditions. -is in- bulk schemes themselves or between bin schemes and bulk dicates that the differences in invigoration among simula- schemes, in terms of numerous individual microphysical processes, are not established adequately well [21]. Hence, tions are not caused by environmental and aerosol conditions and demonstrates that some modeling frame- we do not have general statistical information on which bin scheme or which bulk scheme is representative in terms of works appear to have a propensity to manifest invigoration while others do not [3, 12, 17]. -is exemplifies that the representation of numerous individual microphysical pro- cesses [21]. We also do not have general information on simulated feedbacks between increasing aerosol concen- tration, microphysics, and dynamics are strongly dependent which pair of a bin scheme and a bulk scheme shows on modeling frameworks and has been raising questions representative differences between bin schemes and bulk about the credibility of the simulated feedbacks including schemes regarding those representations [21]. Based on this, aerosol-induced invigoration. instead of trying to select perfectly representative schemes, As a first step to deal with this credibility issue, we have this study relies on rather subjective criteria for the selection to identify key cloud processes that create the discrepancy in of the schemes. -e subjective criteria indicate that a selected scheme for bin approach, which is the scheme of Khain and the simulation of the feedbacks among models. -e iden- tification of key processes in turn enables us to identify key Lynn [28], and a selected scheme for bulk approach, which is the scheme of -ompson and Eidhammer [29], for this study quantified causes of the discrepancy and thus acts as a valuable stepping stone to resolve the credibility issue. have been implemented into widely used models such as the Motivated by this, as a first step to resolve the credibility Advanced Research Weather Research and Forecasting issue, this paper focuses on microphysics representations (ARW) model and thus frequently used. Stated differently, and aims to identify and gain a preliminary understanding of the subjective criteria indicate that conclusions from com- key represented microphysical processes whose different parisons between these two selected schemes can have some representations play a key role in the discrepancy in the level of broad implications though not perfectly general simulation of the feedbacks among models. Note that the implications. -ese subjective criteria follow that in other identification of the key processes has been rarely performed representative studies, which compare schemes and select two schemes for the comparison, such as the study of and the community does not have a clear understanding of those processes themselves [21–24]. -e identification of Dawson et al. and Morrison et al. [30, 31]. -e comparison between the selected schemes enables those key processes provides the community with focal processes that the community should pay more attention to the isolation of the influences of the representation (or and thus enables it to resolve the credibility issue efficiently. parameterization) of microphysical processes on the dis- Based on this, the identification itself can be considered a crepancy, which acts as a basis on which the isolation of the valuable effort [21–24]. Hence, this study primarily aims to key microphysical processes can be performed. A series of achieve the identification itself. -is means that this study numerical simulations is performed in which the impact of does not take interest in understanding detailed mechanisms the representations of microphysical processes on the dis- crepancy in the simulations of the feedbacks between in- through which those identified processes affect the dis- crepancy in the simulation of the feedbacks. creasing aerosol concentration, microphysics, and dynamics is examined. -e goal of this study is to identify a set of key To fulfill the primary aim, this study compares aerosol influences on tropical deep convection between two fre- microphysical processes whose differences account for most of the discrepancy between the schemes. Note that the quently used microphysical schemes within a common dynamical framework and common model setup (grid representation of the feedbacks in climate models is the resolution, domain configuration, initial conditions, and primary cause of uncertainties in the prediction of climate forcing). Regarding the selection of the two schemes for the changes [32]. -e different feedbacks among different Advances in Meteorology 3 With no pollution (clean) With aerosol pollution (polluted) 0°C Initial Mature Initial Mature Cloud-generated airflow Small cloud droplets Cloud-generated airflow Small cloud droplets Aerosol Large ice crystals Aerosol Large ice crystals Large cloud droplets Large cloud droplets Small ice crystals Small ice crystals (a) (b) Figure 1: (a) Airflow generated by convective clouds carries water droplets upwards, leading to the formation of ice crystals in the upper cloud layers. (b) Aerosol pollution (or perturbation) leads to formation of more ice crystals and latent-heat release upon ice crystal formation, which stimulates the updrafts and the vertical growth of clouds (adapted from Lee [13]). microphysical schemes contribute substantially to those Fouquart and Bonnel [35], is utilized to represent radiation uncertainties by producing a large variation of the feedbacks processes. and their impacts on climate changes among different cli- -e microphysical processes are represented by two mate models that are coupled to different microphysical microphysical schemes (or representations). -ey are the bin scheme of Khain and Lynn [28] and the double-moment schemes [12, 21, 32]. As a way of reducing this variation as a process of reducing the uncertainties, we need to identify the bulk microphysics scheme of -ompson and Eidhammer key microphysical processes whose differences explain most [29]. Here, it should be noted that, in the scheme of of the variation and develop the schemes in a way that -ompson and Eidhammer [29], cloud liquid, snow, and reduces the variation associated with the representation of graupel adopt the one-moment prediction of mass-mixing the key processes. By concentrating on development efforts ratio, while cloud ice and rain adopt the two-moment on these key processes, but not all numerous microphysical prediction of mass-mixing ratio and number concentra- processes, the development of the schemes can be performed tion. Henceforth, the former scheme is referred to as “BIN,” efficiently. while the latter scheme is referred to as “BULK.” In both of Accordingly, we aim to find key microphysical processes the two microphysics schemes, aerosol mass is prognosed by that collectively remove most of the discrepancy when considering advection, diffusion, and activation-induced differences in these processes between the schemes are re- removal of the aerosol mass-mixing ratio. moved collectively. Hence, in a large portion of simulations In both microphysics schemes, Ko¨hler theory is applied to in this study, differences in the processes between the droplet activation. When the predicted parcel supersaturation schemes are collectively removed. In other words, in a large for BIN and the diagnosed parcel supersaturation for BULK portion of simulations, differences in two or more potential are higher than critical supersaturation of aerosol particles, key processes between the schemes are removed together they are assumed to be activated. -e aerosol size distribution rather than differences in each of processes removed in- is assumed to follow the lognormal distributions, and it is dividually. We do not try to cover the huge parameter space assumed that ammonium sulfate comprises aerosol in both of that might need to be explored. Instead, we focus on up- the schemes. -e size distribution, which is at the initial time drafts, which are represented by updraft mass fluxes, and one step and for background aerosol, at the altitude of 0.5 km is of the important indicators of the feedbacks and associated depicted in Figure 2. At the other altitudes, background invigoration [11, 12, 18]. aerosol follows this initial size distribution as well although the initial total concentration of background aerosol varies with altitudes, as exemplified in Figure 3. Figure 3 shows the 2. Cloud-System Resolving Model (CSRM) vertical variation of the initial total concentration of back- -e ARW model is employed for this study. -e ARW ground aerosol which is adopted by this study and for the model functions as a CSRM, and this model is not only accumulation mode only. Note that a largest portion of cloud nonhydrostatic but also compressible. A higher-order condensation nuclei (CCN) is well known to be included in scheme, which is developed by Wang et al. [33], is used the accumulation mode when it comes to a general super- for the advection of variables, which are particularly related saturation regime. In the accumulation mode, the initial to microphysics. -e rapid radiation transfer model background aerosol number concentration in the planetary −3 (RRTMG), which is described by Mlawer et al. [34] and boundary layer is around 100 cm and it reduces to around 4 Advances in Meteorology Aerosol size distribution supersaturation in BIN. In contrast to this, a saturation adjustment in BULK diagnoses the diffusion by taking water vapor and temperature in the environment into account. While BIN does not assume a specific type of the size distribution of hydrometeors and does make explicit pre- diction of the distribution, BULK uses basis functions (gamma) with fixed breadth parameters for the size distri- bution of hydrometeors. In BIN, the size distribution of each –2 –1 0 1 10 10 10 10 hydrometeor class is discretized into 33 size bins and hy- D (diameter, micron) drometeor number and mass in each size bin is explicitly Figure 2: Initial aerosol size distribution at the altitude of 0.5 km. predicted. When hydrometeors collide with and collect each N represents the aerosol number concentration per unit volume of other, at each grid point, to represent the collection, col- air and D the aerosol diameter. lection efficiency for each combination of a size of collecting hydrometeor and that of collected hydrometeor is obtained in BIN. Note that there are 33 times 33 combinations of sizes Aerosol vertical distribution in BIN, for example, when it comes to collection between two different classes of hydrometeors in BIN. Hence, the- oretically, 33 times 33 different collection efficiency values are used for the representation of the collection processes between two different classes of hydrometeors at each grid point in BIN. In BIN, for the representation of sedimen- tation processes, at each grid point, each terminal velocity, which varies with varying size bin, in each size bin is ob- tained and hydrometeors in each size bin fall down based on terminal velocity in each bin. Hence, for the representation of sedimentation processes, there are 33 different terminal velocities for each hydrometeor class at each grid point. BULK uses a one-value mass (number) weighted terminal velocity for the sedimentation of hydrometeor mass (number) at each grid point. BULK uses a one-value col- lection efficiency that is calculated by using the mean volume sizes of collecting and collected hydrometeors at each grid point. In this study, the effect of aerosol on radiation via 50 100 –3 Aerosol concentration (cm ) reflection, scattering, and absorption of radiation by aerosol before its activation is not considered. Figure 3: Initial vertical distribution of total aerosol concentration in the accumulation mode. 3. Simulation Design −3 −3 70 cm at the altitude of 2 km and then to 20 cm at the 3.1. Case. An adopted case for this study is an observed altitude of 10 km (Figure 3). It is assumed that the distribution mesoscale system. -is system involved deep convective parameters such as modal diameter and standard deviation of clouds. -is system was observed between 12 : 00 LST (local the distribution are fixed over all grid points and the whole solar time) on January 23th and 12 : 00 LST on January 25th simulation period for each mode of the distribution. -is in 2006. -is observation was performed by the TWP-ICE means that the form of the distribution in Figure 2 is taken by campaign which occurred in Darwin, Australia. -e latitude aerosol over all grid points and the whole period. However, and longitude of the campaign site were 12.47 S and aerosol total number concentration is subject to the spatio- ° 130.85 W, respectively [36]. temporal variation since clouds affect aerosol mass as men- tioned above. -e assumed fixed form of size distribution may overmeasure CCN for nucleation in clouds, which is referred 3.2. Model Setup. A two-day simulation is performed for the to as secondary nucleation. However, in strong convection in adopted case with BULK, which is named the control-BULK deep clouds here, primary nucleation, which occurs in cloud- run. For the simulation, the length of the domain in the free condition, depletes most of CCN; thus, the secondary horizontal direction is set at 120 km whether it is the east- nucleation plays a negligible role in nucleation, other related west or north-south direction and this length enables the microphysical processes, and cloud dynamics (e.g., updraft). simulation of the mesoscale structure of the system. -e -is indicates that the weakness from the assumption of the length over the vertical direction is 20 km, and this enables fixed form is not likely to play an important role in results us to capture deep convective clouds a portion of which can here. grow to the tropopause. 1 km grid spacing in the horizontal Note that the diffusion of water vapor onto hydrome- direction and a varying grid spacing from approximately teors is explicitly calculated by using the predicted 50 m around the surface to approximately 500 m around the –3 dN/d lnD (cm ) Height (km) Advances in Meteorology 5 simulation period. -ese additional sensitivity simulations model top in the vertical direction are used to resolve convective cores. are named the control-BIN-noice-cdnc run, the 10M-BIN- noice-cdnc run, the control-BULK-noice-cdnc run, and the Horizontal boundary conditions are periodic conditions, as described in Fridlind et al. [37]. Observed surface sensible 10M-BULK-noice-cdnc run. Effects of the loading of graupel and latent heat fluxes are imposed at the surface. Large-scale and snow, which explains a large portion of the total loading, forcings of potential temperature and specific humidity as are tested by repeating the standard simulations by removing advective tendencies are provided by the TWP-ICE obser- the loading of each of graupel and snow. -ese sensitivity vations. -ese forcings dictate the net energy and water simulations are named the control-BIN-s run, the 10M-BIN- budget in the domain but not cloud-scale processes. -e s run, the control-BIN-g run, the 10M-BIN-g run, the control-BULK-g run, the 10M-BULK-g run, the control- process of relaxing the horizontal momentum to observed counterpart is applied. BULK-s run, and the 10M-BULK-s run. We test effects of latent-heat processes related to ice hydrometeors or processes, those to rain evaporation, and 3.3. Additional Runs. -e control-BULK run is repeated to those to cloud-liquid evaporation based on recent studies that look into how aerosol affects updrafts. -is sensitivity run is show importance of those processes (e.g., [11, 17, 39, 40]). To performed by escalating the initial aerosol concentration in test effects of latent-heat processes related to ice hydrome- the background by a factor of 10. -is run is named “the teors, the standard runs with BULK are repeated by turning 10M-BULK run.” -en, to examine the sensitivity of up- off ice-related latent-heat processes and these sensitivity runs drafts and the effect of aerosol on them to microphysics are named control-BULK-no-ice-lt run and the 10M-BULK- representations via comparisons between BULK and BIN, no-ice-lt run. To test those effects related to rain evaporation, we repeat the control-BULK run and the 10M-BULK run by the control-BIN-noice-cdnc run, the 10M-BIN-noice-cdnc replacing BULK with BIN. -ese sensitivity runs are named run, the control-BULK-noice-cdnc run, and the 10M- “the control-BIN run” and “the 10M-BIN run.” -ese four BULK-noice-cdnc run are repeated by turning off rain simulations constitute “the standard simulations” in this evaporative cooling. -ese sensitivity simulations are named study. the control-BIN-no-rain-evp run, the 10M-BIN-no-rain-evp Updrafts are strongly controlled by the buoyancy of a run, the control-BULK-no-rain-evp run, and the 10M-BULK- rising air parcel [9, 38]. -e buoyancy is in turn controlled by no-rain-evp run. To test those effects related to cloud-liquid the loading of hydrometeors, latent-heat processes, and evaporation, the sensitivity simulations with rain evaporative associated microphysical processes [9, 38]. Based on recent cooling turned off are repeated by turning off cloud-liquid studies such as Rosenfeld et al. [11] and Lee et al. (2013), this evaporative cooling, and these additional sensitivity simula- paper focuses on latent-heat processes which are associated tions are named the control-BIN-no-cld-evp run, the 10M- with not only solid or ice hydrometeors but also liquid BIN-no-cld-evp run, the control-BULK-no-cld-evp run, and hydrometeors. Here, we deal with microphysical processes the 10M-BULK-no-cld-evp run. that are related to overall life cycle of cloud particles: the To understand the role played by microphysical pro- formation of cloud particles, their growth, interactions cesses related to the particle growth in the simulation of between solid particles and liquid particles, which are as- updrafts and aerosol effects on them, we test effects of sociated with the invigoration of convection, and their saturation and collection processes (i.e., autoconversion and sedimentation to the ground. -e classic theory in cloud accretion) on the simulation. To test effects of saturation physics indicates that the formation of cloud particles is (collection processes), the control-BIN-no-cld-evp run and affected by water vapor saturation, and byproduct of the the 10M-BIN-no-cld-evp run are repeated by adopting formation, which is a starting point of effects of formation saturation adjustment (collection scheme) in BULK, and on clouds, is cloud particle number concentration such as these sensitivity simulations are named the control-BIN-sat cloud droplet number concentration (CDNC). -e theory run and the 10M-BIN-sat run (the control-BIN-col run and also indicates that condensation and deposition, which are a the 10M-BIN-col run). To see effects of sedimentation on the function of water vapor saturation, and autoconversion and simulation of updrafts and aerosol effects on them, the accretion between cloud particles govern the growth of cloud control-BIN-col run and the 10M-BIN-col run are repeated particles. As a way of identifying “key cloud processes” with the sedimentation scheme in BULK, and these sensi- which create the discrepancy in the simulations of updrafts tivity simulations are named the control-BIN-sed run and and aerosol effects on them between BULK and BIN, we the 10M-BIN-sed run. primarily take into account those latent-heat processes, Some of the simulations that are described above are loading of hydrometeors, and microphysical processes. performed with multiple microphysical processes which are To see effects of interactions between solid particles and modified together. For example, in the control-BIN-noice- liquid particles on the simulation of updrafts and aerosol cdnc run, the 10M-BIN-noice-cdnc run, the control-BULK- effects on them, the standard simulations are repeated with noice-cdnc run, and the 10M-BULK-noice-cdnc run, both ice processes turned off. -ese sensitivity runs are named the ice processes and CDNC are modified. -is disables us from control-BULK-noice run, the 10M-BULK-noice run, the the perfect isolation of effects of ice processes from those of control-BIN-noice run, and the 10M-BIN-noice run. To see CDNC, or vice versa. Motivated by this, for better isolation effects of CDNC, these sensitivity simulations are repeated of effects of individual microphysical processes, the standard with CDNC fixed at one value over the domain and the simulations are repeated by modifying a process of interest 6 Advances in Meteorology this study is given. For the sake of brevity of Table 1 and only. -ese repeated simulations are named by including “only” in their name. based on the fact that simulations whose name include “only” and “2 mt” are a simple extension of the basic sim- For the isolation of effects of CDNC, the standard simulations are repeated by fixing CDNC, following the ulations, these simulations are not included in Table 1. -e method in the “noice-cdnc” runs, yet with ice processes that description of the simulations in this section and Table 1 is are turned on. -ese repeated simulations are the control- supposed to give their brief outline, and their details are BIN-cdnc-only run, the 10M-BIN-cdnc-only run, the given below in Section 4. control-BULK-cdnc-only run and the 10M-BULK-cdnc- only run. In addition to the “noice-cdnc” runs, it is nota- 4. Results ble that the above-described simulations to test each of effects of rain and cloud-liquid evaporative cooling, satu- In figures below that depict results from the simulations, the ration, collection, and sedimentation processes involve other simulations with prefixes “control-BULK,” “10M-BULK,” processes which are modified together. For better isolation “control-BIN,” and “10M-BIN” in their names are repre- of each of these processes, the standard simulations are sented by yellow, blue, black, and red lines, respectively. In repeated only by turning off rain evaporative cooling, fol- case, there are two or more simulations whose name is with lowing the same method as in the “no-rain-evp” runs, and an identical prefix in a figure, and these simulations use then they are repeated again only by turning off cloud-liquid different line types (i.e., solid, dashed, and dotted lines) with evaporative cooling, following the same method as in the an identical line color. -e updraft mass fluxes, which are “no-cld-evp” runs. -ese repeated simulations with rain described below, are obtained simply by multiplying the evaporative cooling off are named the control-BIN-no-rain- updraft speed with air density. For all the simulations, the evp-only run, the 10M-BIN-no-rain-evp-only run, the updraft speed is predicted. Air density varies negligibly as control-BULK-no-rain-evp-only run, and the 10M-BULK- compared to the variation of updraft speed at each altitude no-rain-evp-only run. -ese repeated simulations with among the simulations; hence, differences in updraft mass cloud-liquid evaporative cooling off are named the control- fluxes are mostly caused by differences in updraft speed, and BIN-no-cld-evp-only run, the 10M-BIN-no-cld-evp-only contributions by differences in air density to those in updraft run, the control-BULK-no-cld-evp-only run, and the mass fluxes are negligible at each altitude among the sim- 10M-BULK-no-cld-evp-only run. For better isolation of ulations. -is indicates that conclusions drawn based on roles by the saturation process, the control-BIN run and the updraft mass fluxes below are not qualitatively different 10M-BIN run are repeated by adopting saturation adjust- from those based on updraft speed. ment in BULK as in “sat” runs. -ese simulations are the control-BIN-sat-only run and the 10M-BIN-sat-only run. For better isolation of roles by the collection process, the 4.1. Evaluation of the Control-BIN Run and the Control-BULK control-BIN run and the 10M-BIN run are repeated by Run. To evaluate the control-BIN run and control-BULK adopting the collection scheme in BULK as in “col” runs. run, cloud and precipitation variables that are simulated by -ese simulations are the control-BIN-col-only run and the the runs are compared to observed counterparts. -e cloud 10M-BIN-col-only run. Finally, for better isolation of roles fraction, cloud-top height, the liquid-water path (LWP), the by the sedimentation process, the control-BIN run and the ice-water path (IWP), and cumulative precipitation are 10M-BIN run are repeated by adopting the sedimentation selected to be those variables. -is is based on the fact that scheme in BULK as in “sed” runs. -ese simulations are the the selected variables are well known to be representative control-BIN-sed-only run and the 10M-BIN-sed-only run. variables that are able to give us information on the overall It should be remembered that, in BULK, among pre- structure of a system of interest [9, 12, 14]. Hence, by cipitable hydrometeors, snow, and graupel adopt the one- selecting the variables, we are able to evaluate how the moment prediction, while rain adopts the two-moment overall simulation of a system of interest is performed. prediction. As indicated by Wacker and Seifert [41], Mil- -e cloud fractions are 0.45 (0.48) for clouds below 5 km brandt and Yau [42], and Milbrandt and McTaggart-Cowan in altitude, 0.55 (0.49) for clouds between 5 and 10 km in [43], whether the one-moment or the two-moment pre- altitude, and 0.85 (0.78) for clouds between 10 and 15 km in diction is used for precipitable hydrometeors affects how the altitude in the control-BIN (control-BULK) run. -e observed mass of precipitable hydrometeors is distributed in the fractions are 0.49 for clouds below 5 km in altitude, 0.51 for vertical domain. -is can have impacts on results here by clouds between 5 and 10 km in altitude, and 0.82 for clouds altering microphysical factors such as the vertical distri- between 10 and 15 km in altitude. -e simulated fractions butions of loading and latent-heat processes. Motivated by deviate from observation by less than around 10%. -e cloud- this, the standard simulations with BULK are repeated by top height, averaged over the simulation period, is 8.1 km for replacing the one-moment prediction with the two-moment the control-BIN run and 7.4 km for the control-BULK run, prediction for snow and graupel. -ese sensitivity runs are and those simulated heights show around 3–5% discrepancy named the control-BULK-2 mt run and the 10M-BULK- against an observed height that is 7.8 km. -e LWP, averaged −2 2 mt runs. Also, the other BULK simulations are repeated over the domain and the simulation period, is 920 (734) g·m , −2 with the two-moment prediction, and these simulations are while the averaged IWP is 85 (70) g·m for the control-BIN named by including “2 mt” in their name. In Table 1, the (control-BULK) run. -e observed LWP and IWP are 819 and −2 description of basic standard and repeated simulations in 77 g·m , respectively, and thus, the differences in LWP and Advances in Meteorology 7 Table 1: Summary of simulations. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Use of the mean Use of constant Control- Saturation terminal velocity BULK 100 Present Predicted Present Present Present Present Present collection BULK adjustment and the flux efficiencies approach Use of the mean Use of constant Saturation terminal velocity 10M-BULK BULK 1000 Present Predicted Present Present Present Present Present collection adjustment and the flux efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Present Predicted Present Present Present Present Present hydrometeor BIN prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Supersaturation of collection 10M-BIN BIN 1000 Present Predicted Present Present Present Present Present hydrometeor prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Control- Use of constant Saturation terminal velocity BULK- BULK 100 Absent Predicted Absent Absent Absent Present Present collection adjustment and the flux noice efficiencies approach Use of the mean 10M- Use of constant Saturation terminal velocity BULK- BULK 1000 Absent Predicted Absent Absent Absent Present Present collection adjustment and the flux noice efficiencies approach 8 Advances in Meteorology Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Absent Predicted Absent Absent Absent Present Present hydrometeor BIN-noice prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Supersaturation of collection BIN 1000 Absent Predicted Absent Absent Absent Present Present hydrometeor noice prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Control- Use of constant Fixed at Saturation terminal velocity BULK- BULK 100 Absent Absent Absent Absent Present Present collection 55 adjustment and the flux noice-cdnc efficiencies approach Use of the mean 10M- Use of constant Fixed at Saturation terminal velocity BULK- BULK 1000 Absent Absent Absent Absent Present Present collection 451 adjustment and the flux noice-cdnc efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence Control- velocity on the Fixed at Supersaturation of collection BIN-noice- BIN 100 Absent Absent Absent Absent Present Present hydrometeor 55 prediction efficiencies on cdnc size and the use the hydrometeor of a semi- size Lagrangian method Advances in Meteorology 9 Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Fixed at Supersaturation of collection BIN 1000 Absent Absent Absent Absent Present Present hydrometeor noice-cdnc 451 prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Present Predicted Absent Present Present Present Present hydrometeor BIN-g prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Supersaturation of collection 10M-BIN-g BIN 1000 Present Predicted Absent Present Present Present Present hydrometeor prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Present Predicted Present Absent Present Present Present hydrometeor BIN-s prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method 10 Advances in Meteorology Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the Supersaturation of collection 10M-BIN-s BIN 1000 Present Predicted Present Absent Present Present Present hydrometeor prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Use of constant Control- Saturation terminal velocity BULK 100 Present Predicted Absent Present Present Present Present collection BULK-g adjustment and the flux efficiencies approach Use of the mean Use of constant 10M- Saturation terminal velocity BULK 1000 Present Predicted Absent Present Present Present Present collection BULK-g adjustment and the flux efficiencies approach Use of the mean Use of constant Control- Saturation terminal velocity BULK 100 Present Predicted Present Absent Present Present Present collection BULK-s adjustment and the flux efficiencies approach Use of the mean Use of constant 10M- Saturation terminal velocity BULK 1000 Present Predicted Present Absent Present Present Present collection BULK-s adjustment and the flux efficiencies approach Use of the mean Control- Use of constant Saturation terminal velocity BULK-no- BULK 100 Present Predicted Present Present Absent Present Present collection adjustment and the flux ice-lt efficiencies approach Use of the mean 10M- Use of constant Saturation terminal velocity BULK-no- BULK 1000 Present Predicted Present Present Absent Present Present collection adjustment and the flux ice-lt efficiencies approach Use of the mean Control- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 100 Absent Absent Absent Absent Absent Present collection 55 adjustment and the flux rain-evp efficiencies approach Advances in Meteorology 11 Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Use of the mean 10M- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 1000 Absent Absent Absent Absent Absent Present collection 451 adjustment and the flux rain-evp efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence Control- velocity on the Fixed at Supersaturation of collection BIN-no- BIN 100 Absent Absent Absent Absent Absent Present hydrometeor efficiencies on 55 prediction rain-evp size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence 10M-BIN- velocity on the Fixed at Supersaturation of collection no-rain- BIN 1000 Absent Absent Absent Absent Absent Present hydrometeor 451 prediction efficiencies on evp size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Control- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 100 Absent Absent Absent Absent Absent Absent collection 55 adjustment and the flux cld-evp efficiencies approach Use of the mean 10M- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 1000 Absent Absent Absent Absent Absent Absent collection 451 adjustment and the flux cld-evp efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence Control- velocity on the Fixed at Supersaturation of collection BIN-no- BIN 100 Absent Absent Absent Absent Absent Absent hydrometeor 55 prediction efficiencies on cld-evp size and the use the hydrometeor of a semi- size Lagrangian method 12 Advances in Meteorology Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Fixed at Supersaturation of collection BIN 1000 Absent Absent Absent Absent Absent Absent hydrometeor no-cld-evp 451 prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Fixed at Saturation of collection hydrometeor BIN 100 Absent Absent Absent Absent Absent Absent BIN-sat 55 adjustment efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Fixed at Saturation of collection BIN 1000 Absent Absent Absent Absent Absent Absent hydrometeor sat 451 adjustment efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence of the terminal Use of constant velocity on the Control- Fixed at Supersaturation BIN 100 Absent Absent Absent Absent Absent Absent collection hydrometeor BIN-col 55 prediction efficiencies size and the use of a semi- Lagrangian method Advances in Meteorology 13 Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence of the terminal Use of constant velocity on the 10M-BIN- Fixed at Supersaturation BIN 1000 Absent Absent Absent Absent Absent Absent collection hydrometeor col 451 prediction efficiencies size and the use of a semi- Lagrangian method Use of the mean Use of constant Control- Fixed at Supersaturation terminal velocity BIN 100 Absent Absent Absent Absent Absent Absent collection BIN-sed 55 prediction and the flux efficiencies approach Use of the mean Use of constant 10M-BIN- Fixed at Supersaturation terminal velocity BIN 1000 Absent Absent Absent Absent Absent Absent collection sed 451 prediction and the flux efficiencies approach 14 Advances in Meteorology IWP between the control-BIN (control-BULK) run and ob- servation are around 12 (10)% and 10 (9)%. -e cumulative precipitation, averaged over the horizontal domain at the last time step, in the control-BIN run (the control-BULK run) is 97.3 (98.5) mm, which is around 3 (4)% greater than that for observation that is 94.7 mm. -ese comparisons provide a fairly good confidence that the simulation of the overall system structure is performed reasonably well. -ey also show that the averaged fields vary insignificantly from the control-BIN run to the control-BULK. 4.2. Standard Runs with Complete Physics. -e control- BULK run, the 10M-BULK run, the control-BIN run, and the 10M-BIN run, as the standard runs, using standard, “complete” physics are compared in Figure 4. -e profiles of updraft mass fluxes vary significantly between simulations with BIN and those with BULK despite the above shown small variation in the averaged fields of cloud fraction, top height, LWP, IWP, and precipitation from the control-BIN run to the control-BULK run. 0 0.1 0.2 0.3 0.4 –2 –1 Profiles of updraft mass fluxes in the control-BULK run Updraft mass f lux (kg·m ·s ) show rapid increases up to 2.8 km and peak at 2.8 km, which Control-BULK Control-BIN are followed by rapid decreases in the fluxes above 2.8 km. 10M-BULK 10M-BIN -e similar rapid increases and decreases are shown in the Figure 4: Vertical distributions of the time- and domain-averaged 10M-BULK run (Figure 4). However, the control-BIN run updraft mass fluxes for the standard runs (e.g., the control-BULK and the 10M-BIN run show less rapid increases in the fluxes run, the 10M-BULK run, the control-BIN run, and the 10M-BIN to the peak at 3.9 km and less rapid decreases after the peak, run). as compared to the simulations with BULK (Figure 4). -e magnitude or the value of the peak is from 0.28 to −2 −1 −2 −1 0.35 kg·m ·s with its mean value of 0.32 kg·m ·s in the 4.3. Ice Processes. Rosenfeld et al. [11] have shown that the −2 −1 simulations with BIN, while it is from 0.25 to 0.27 kg·m ·s suppressed conversion of cloud liquid to rain, which is −2 −1 with its mean value of 0.26 kg·m ·s in the simulations caused by increasing aerosol concentration, induces in- with BULK. Hence, the altitude of the peak is 39% higher, creases in cloud liquid and its transportation to places where and the mean peak value is 23% higher in the standard BIN freezing occurs. -is enhances freezing, associated latent runs than in the standard BULK runs (Figure 4). heat and buoyancy, and invigorates updrafts and convection. Another point to make is that the control-BIN run and In this invigoration hypothesis, aerosol-induced changes in the 10M-BIN run exhibit an increase in updraft mass fluxes freezing and buoyancy are a main source of the invigoration- as aerosol concentration increases. Associated with this, the related changes in updrafts with increasing aerosol con- −2 −1 peak value increases by 20% from 0.28 to 0.35 kg·m ·s centration. Hence, the different ice processes (involving with increasing aerosol concentration between the control- freezing) may be the main cause of the different responses of BIN run and the 10M-BIN run. However, the control-BULK updraft mass fluxes to increasing aerosol concentration run and the 10M-BULK run exhibit slight decreases in the between the simulations with BULK and those with BIN. flux with increasing aerosol concentration (Figure 4). As- Hence, to isolate the effect of ice processes on the different sociated with this, the peak value decreases by 7% from 0.27 responses among the four standard simulations (i.e., the −2 −1 to 0.25 kg·m ·s with increasing aerosol concentration control-BULK run, the 10M-BULK run, the control-BIN between the control-BULK run and the 10M-BULK run. In run, and the 10M-BIN run), the four standard simulations other words, simulations with BIN show aerosol-induced are repeated with ice processes turned off completely. In invigoration of convection, while simulations with BULK these sensitivity runs, which are the control-BULK-noice show aerosol-induced suppression of convection to the run, the 10M-BULK-noice run, the control-BIN-noice run, contrary. Two frequently used microphysical schemes ex- and the 10M-BIN-noice run, precipitation is formed entirely hibit different responses to a large aerosol perturbation. To by warm rain processes (collision and collection of cloud fulfill the aim of this study, instead of trying to understand liquid by rain and autoconversion of cloud liquid to rain). In which microphysics scheme performs better, we focus on the BIN, drops whose size is smaller than 80 μm in diameter are identification of key cloud processes that create the dis- classified to be droplets (or cloud liquid), while drops whose crepancy among the simulations. In each of the following size is greater than 80 µm in diameter are classified to be rain figures from Figure 5 to Figure 12 which show the profiles of drops (or rain). Here, autoconversion is a process where updraft mass fluxes, fluxes in the standard runs are also droplets collide with and collect each other to form rain. -e shown as a reference. control-BIN-noice run, the 10M-BIN-noice run, the Height (km) Advances in Meteorology 15 control-BULK-noice run, and the 10M-BULK-noice run BULK runs as a process of removing the differences in the show that the differences in the pattern of the vertical CDNC distributions between the control-BIN-noice run and the control-BULK-noice run or between the 10M-BIN-noice variation of updraft mass fluxes (as shown between the standard runs in Figures 4 and 5(a)) nearly disappear run and the 10M-BULK-noice run. For the control-BIN- (Figures 4 and 5(a)). In this paper, the pattern of the vertical noice run and control-BULK-noice run with the CDNC −3 variation of updraft mass fluxes means the altitude of the fixed, CDNC is fixed at 55 cm , while for the 10M-BIN- updraft-mass-flux peak, the peak value, and the rate of noice run and 10M-BULK-noice run with the CDNC fixed, −3 changes in updraft mass fluxes with altitudes around the CDNC is fixed at 451 cm . Here, it is seen that about peak. -e altitude of the peak is 4.3 km in the “noice” runs, 40–50% of aerosol particles in the accumulation mode are which is 54% higher than that in the control-BULK run and activated in the “noice” runs. -is activation ratio is also the 10M-BULK run and 10% higher than that in the control- applicable to the standard runs whose results are depicted in BIN run and the 10M-BIN run. -e peak value is similar Figure 4. CDNC is averaged over time and places with non- between the “noice” runs since it varies slightly from 0.26 to zero CDNC for each of the runs with ice processes turned −2 −1 −2 −1 0.28 kg·m ·s with the mean peak value of 0.27 kg·m ·s off. -en, two averaged CDNCs in the control-BIN-noice between the runs. -is mean peak value is 4 (16)% higher (10M-BIN-noice) run and the control-BULK-noice (10M- BULK-noice) run are summed and divided by two to obtain (lower) than that in the standard simulations with BULK (BIN). the CDNC value that is input to the control-BIN-noice run -ese sensitivity simulations (as compared to the and the control-BULK-noice run with CDNC fixed (the standard runs in Figures 4 and 5(a)) also show that the fact 10M-BIN-noice run and the 10M-BULK-noice run with that simulations with BIN only show aerosol-induced in- CDNC fixed). In each of these sensitivity runs with CDNC vigoration of convection is robust to whether ice processes fixed, which are the control-BIN-noice-cdnc run, the 10M- are turned off or not although the control-BIN-noice run BIN-noice-cdnc run, the control-BULK-noice-cdnc run, and the 10M-BIN-noice run show much less aerosol- and the 10M-BULK-noice-cdnc run, the obtained CDNC induced increases in updraft mass fluxes as compared to value replaces a predicted CDNC value at each grid point those in the control-BIN run and in the 10M-BIN run with none-zero predicted CDNC value at each time step. (Figures 4 and 5(a)). -ese increases are 4% from 0.27 to Comparisons among the simulations with CDNC fixed −2 −1 0.28 kg·m and ice processes off show that the differences in the pattern ·s , which is smaller than 20% in the control- BIN run and the 10M-BIN run. -is demonstrates that of the vertical variation of updraft mass fluxes reduce different ice processes are responsible for the different substantially, as shown in Figure 5(b) in comparisons with shapes of the updraft-mass-flux profile but not for the ab- those differences between the standard simulations in Fig- sence of aerosol-induced invigoration with BULK and the ures 4 and 5(b). -is is similar to the situation among the presence of the invigoration with BIN. control-BIN-noice run, the 10M-BIN-noice run, the control-BULK-noice run, and the 10M-BULK-noice run, as seen in comparisons between Figures 4, 5(a), and 5(b). -e 4.4. CDNC. In addition, it is very likely that there are the altitude of the peak of the updraft-mass-flux vertical profile different spatiotemporal distributions of CDNCs for an is similar and at 3.7 km in the simulations with CDNC fixed identical background aerosol condition between the control- and ice processes off, which is 5% lower than that in the BIN-noice run and the control-BULK-noice run or between control-BIN run and the 10M-BIN run, 32% higher than the 10M-BIN-noice run and the 10M-BULK-noice run that in the control-BULK run and the 10M-BULK run, and whose results are depicted in Figure 5(a). With the droplet 14% lower than that in the “noice” runs. However, as seen in nucleation, droplets are formed, and CDNC, one of the comparisons between Figures 4 and 5(b), there are still droplet properties, affects subsequent cloud microphysical significant differences in the magnitude of updraft mass and dynamic processes. Since aerosol properties determine fluxes among the simulations with CDNC fixed and ice CDNC during the nucleation, it is generally considered that processes off as in the standard runs. Associated with this, −2 −1 CDNC acts as a proxy for aerosol in subsequent cloud the peak value increases by 6% from 0.32 kg·m ·s in the −2 −1 processes after the nucleation. Hence, if we want to apply an control-BULK-noice-cdnc run to 0.34 kg·m ·s in the identical aerosol condition to cloud processes (i.e., both 10M-BULK-noice-cdnc run, while it increases by 6% from −2 −1 nucleation and subsequent processes after it) in a rigorous 0.36 kg·m ·s in the control-BIN-noice-cdnc run to −2 −1 manner among different simulations, it is better that not 0.38 kg·m ·s in the 10M-BIN-noice-cdnc run. -e mean −2 −1 only aerosol condition (before nucleation) but also CDNC peak value is 0.33 kg·m ·s between the control-BULK- distributions are identical between those simulations. noice-cdnc run and the 10M-BULK-noice-cdnc run, while it −2 −1 To make sure that the pair of the control-BIN-noice run is 0.37 kg·m ·s between the control-BIN-noice-cdnc run and the control-BULK-noice run or the pair of the 10M- and the 10M-BIN-noice-cdnc run. Hence, when it comes to BIN-noice run and the 10M-BULK-noice run is in an the mean peak value, the “BIN-noice-cdnc” runs show a 12% identical aerosol condition for all of cloud processes in a higher value than the “BULK-noice-cdnc” runs. Of interest rigorous way, the four sensitivity runs with ice processes is that, in “noice-cdnc” runs, both BULK and BIN show the turned off are repeated. In these runs, in addition to ice enhancement of updraft mass fluxes as aerosol concentra- processes turned off, CDNC is fixed at one value for each of tion increases contrary to the situation in the standard aerosol conditions (before nucleation) for the BIN and simulations (Figures 4 and 5(b)). -is demonstrates that 16 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK-noice Control-BULK Control-BULK-noice-cdnc Control-BULK 10M-BULK-noice 10M-BULK 10M-BULK-noice-cdnc 10M-BULK Control-BIN-noice Control-BIN Control-BIN-noice-cdnc Control-BIN 10M-BIN-noice 10M-BIN 10M-BIN-noice-cdnc 10M-BIN (a) (b) Figure 5: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-noice run, the 10M-BULK-noice run, the control-BIN-noice run, and the 10M-BIN-noice run. (b) Vertical distributions of the time- and domain- averaged updraft mass fluxes for the standard runs, the control-BULK-noice-cdnc run, the 10M-BULK-noice-cdnc run, the control-BIN- noice-cdnc run, and the 10M-BIN-noice-cdnc run. different distributions of CDNC, after nucleation due to runs are the control-BULK run, the 10M-BULK run, the different microphysical schemes, for the identical aerosol control-BIN run, and the 10M-BIN run. Henceforth, the condition before nucleation between the control-BIN-noice freezing level indicates an altitude where freezing starts to run and the control-BULK-noice run and/or between the occur in a rising air parcel, and this altitude is located around 4 km in this study. -e much larger loading or mass of ice 10M-BIN-noice run and the 10M-BULK-noice run are the main cause of the different signs of responses of updraft hydrometeors around 4 km can curb the growth of updraft mass fluxes to increasing aerosol concentration between the mass fluxes more by inducing greater gravity on the mass two different microphysical schemes. -is also demonstrates that tends to pull down a rising air parcel to the ground or that how CDNC is predicted after nucleation for an identical decelerate the parcel more in the standard simulations with aerosol condition before nucleation has a substantial impact BULK than in the standard simulations with BIN. -is can on how updraft mass fluxes respond to increasing aerosol lower the peak value in the standard BULK simulations in concentration. comparison with the standard BIN simulations. -e much larger loading can also “squash” down the vertical profile of updraft mass fluxes around the freezing level in the standard 4.5. Loading of Ice Hydrometeors. -e rapid increases and BULK simulations. Note that the profile around the peak decreases in updraft mass fluxes in the lower atmosphere in between approximately 3 km and approximately 4 km in the the standard simulations with BULK, as shown in Figure 4, standard simulations with BULK in Figure 4 appears to be may be related to loading effects that are exerted by ice pushed (or squashed) down compared to the profile in the hydrometeors. -is is based on the finding that ice processes standard simulations with BIN in Figure 4. -e squashed have an impact on the vertical profile of updraft mass fluxes, profile accompanies the rapid increases and decreases in as discussed in Section 4.3. We can easily envision that there updraft mass fluxes around the peak in the standard BULK are much greater loading effects of solid hydrometeors in the simulations in Figure 4. standard simulations with BULK which are depicted in To understand the rapid increases and decreases in Figure 4 than in the standard simulations with BIN which updraft mass fluxes in the lower atmosphere in the standard are depicted in Figure 4, particularly around the freezing BULK simulations, based on abovementioned conjecture level that is around 4 km. Remember that these four standard which is related to loading effects, the control-BULK run Height (km) Height (km) Advances in Meteorology 17 together with the 10M-BULK run is repeated by turning off To see effects of the loading of snow and graupel for BIN, the loading effect of the graupel mass. -is is based on the the control-BIN run and the 10M-BIN run are repeated by well-known fact that the graupel mass accounts for a sig- removing snow loading and graupel loading, respectively. nificant portion of loading effects particularly in deep clouds. -ese sensitivity runs are the control-BIN-s run, the 10M- In these sensitivity runs, which are the control-BULK-g run BIN-s run, the control-BIN-g run, and the 10M-BIN-g run. and the 10M-BULK-g run, despite the absence of the loading As seen in Figure 6(c), whether snow loading or graupel effect of the graupel mass, graupel particles experience the loading is turned off, both the response of updraft mass dynamic, thermodynamic, and microphysical processes as in fluxes to increasing aerosol concentration and the pattern of the standard runs. Comparisons between the control-BULK the vertical variation of updraft mass fluxes do not change run, the 10M-BULK run, the control-BULK-g run, and the significantly in the simulations with BIN. Associated with 10M-BULK-g run indicate that the vertical shape or pattern of this, the altitude and magnitude of the peak varies less than the updraft-mass-flux profile does not vary much with the 6% from the standard BIN runs to the BIN runs with either presence or absence of the loading effect of graupel mass snow loading removed or graupel loading removed. (Figure 6(a)). -e altitude of the peak value of the profile is 2.8 km in the control-BULK-g run and the 10M-BULK-g run, which is identical to that in the control-BULK run and the 4.6. Latent Heating and Cooling of Ice Hydrometeors. To test −2 −1 roles played by latent heating and cooling related to ice 10M-BULK run. -e peak value is 0.26 and 0.24 kg·m ·s in the control-BULK-g run and the 10M-BULK-g run, re- processes and aerosol effects on them in the shapes of the updraft-mass-flux vertical profile in the control-BULK run spectively, which shows a slightly 4% lower value than that in the control-BULK run and the 10M-BULK run, respectively. and the 10M-BULK run, relative to those played by the loading effect of snow and aerosol influences on it, the -en, the control-BULK run and the 10M-BULK run are repeated with the absence of the snow loading, based on the control-BULK run and the 10M-BULK run are repeated by turning off the effect of latent heating and cooling from fact that snow and graupel accounts for a significant portion of the loading effect. In these sensitivity runs, which are the freezing, melting, deposition, and sublimation. -ese sen- sitivity simulations are the control-BULK-no-ice-lt run and control-BULK-s run and the 10M-BULK-s run, despite the the 10M-BULK-no-ice-lt run. Note that in the control- absence of the loading effect of the snow mass, snow particles experience the dynamic, thermodynamic, and microphysical BULK-noice run and the 10M-BULK-noice run, as depic- ted in Figure 5(a), ice hydrometeors are absent or the mass of processes as in the standard runs. -e control-BULK run, the 10M-BULK run, the control-BULK-s run, and the 10M- ice hydrometeors is zero; thus, both loading and latent heating or cooling related to ice hydrometeors are absent. BULK-s run are compared, and this comparison shows sig- nificant changes in the vertical shape of updraft mass fluxes However, in the control-BULK-no-ice-lt run and the 10M- BULK-no-ice-lt run, the effect of latent heating related to ice due to the presence or the absence of the snow loading in the simulations with BULK, although the qualitative nature of hydrometeors on temperature is only turned off and ice processes are allowed to generate ice hydrometeors. responses of updraft mass fluxes to increases in aerosol -erefore, the loading of ice hydrometeors is present in these concentration does not vary with whether the snow loading is runs. -ey show results whose qualitative nature is similar to considered or not (Figure 6(a)). By removing the snow that in the control-BULK run and the 10M-BULK run when loading in the control-BULK-s run and the 10M-BULK-s run, the altitude and magnitude of the updraft-mass-flux peak and it comes to the shape of the vertical profile of updraft mass fluxes and updraft-mass-flux responses to increasing aerosol the increases and decreases of the fluxes around the peak in these sensitivity runs become similar to those in the control- concentration, as shown in Figure 6(d). Associated with this, the altitude of the updraft-mass-flux peak increase slightly BIN run and the 10M-BIN run (Figure 6(a)). Associated with this, the altitude of the peak value increases by 39% from only by 7 (4)% from 2.8 km in the control-BULK (10M- BULK) run to 3.0 (2.9) km in the control-BULK-no-ice-lt 2.8 km in the control-BULK run and the 10M-BULK run to 3.9 km in the control-BULK-s run and the 10M-BULK-s run, (10M-BULK-no-ice-lt) run. -e peak value also increases −2 −1 slightly only by 4% from 0.27 (0.25) kg·m ·s in the while the peak value increases by 22 (28)% from 0.27 (0.25) −2 −1 −2 −1 kg·m ·s in the control-BULK (10M-BULK) run to 0.33 control-BULK (10M-BULK) run to 0.28 (0.26) kg·m ·s in −2 −1 the control-BULK-no-ice-lt (10M-BULK-no-ice-lt) run. (0.32) kg·m ·s in the control-BULK-s (10M-BULK-s) run. -e vertical distribution of the mass density of snow for Hence, the effect of latent heating and cooling (related to ice processes) on the shapes of the updraft-mass-flux vertical the 10M-BULK run and the 10M-BIN run is shown in Figure 6(b). -ere is much higher mass density of snow in profile in the simulations with BULK is negligible in the 10M-BULK run than in the 10M-BIN run, in particular, comparison with the effect of the snow loading. Of interest is that, as seen in Figure 6(d), there is a slight around the freezing level. -is explains the much larger loading of snow in the standard simulations with BULK than increase in updraft mass flux in the control-BULK-no-ice-lt run, as compared to the control-BULK run, and in the 10M- in the standard simulations with BIN, which lowers the value of the updraft-mass-flux peak and pushes down the updraft- BULK-no-ice-lt run, as compared to the 10M-BULK run. -is is despite ice-process-related latent heating which mass-flux profile around 3 km and around 4 km in the standard simulations with BULK as demonstrated by the enhances buoyancy in updrafts and is turned off in the control-BULK-no-ice-lt run and the 10M-BULK-no-ice-lt sensitivity simulations with the loading of snow turned off in Figure 6(a). run. Increases in ice-process-related latent heating enhance 18 Advances in Meteorology 18 18 10 10 8 8 2 2 0 0.05 0.1 0.15 0.2 0.25 0 0.1 0.2 0.3 0.4 –3 –2 –1 Mass density (g·m ) Updraft mass flux (kg·m ·s ) 10M-BULK Control-BULK Control-BULK-g 10M-BIN 10M-BULK 10M-BULK-g Control-BIN Control-BULK-s 10M-BIN 10M-BULK-s (a) (b) 12 12 10 10 8 8 6 6 4 4 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK Control-BIN-g Control-BULK Control-BULK-no-ice-lt 10M-BULK 10M-BULK-no-ice-lt 10M-BULK 10M-BIN-g Control-BIN Control-BIN Control-BIN-s 10M-BIN 10M-BIN 10M-BIN-s (c) (d) Figure 6: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-g run, the 10M-BULK-g run, the control-BULK-s run, and the 10M-BULK-s run. (b) Vertical distributions of the time- and domain-averaged snow mass density for the 10M-BULK run and the 10M-BIN run. (c) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-g run, the 10M-BIN-g run, the control-BIN-s run, and the 10M-BIN-s run. (d) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-no-ice-lt run, and the 10M-BULK-no-ice-lt run. Height (km) Height (km) Height (km) Height (km) Advances in Meteorology 19 buoyancy and updraft speed. -ese increases in updraft rain evaporation, which are induced by aerosol, and those in speed in turn increase the mass of ice-phase hydrometeors the gust front intensity. Motivated by this, the control-BIN- and thus the loading of ice-phase hydrometeors by en- noice-cdnc run, the 10M-BIN-noice-cdnc run, the control- hancing supersaturation and deposition. -ese increases in BULK-noice-cdnc run, and the 10M-BULK-noice-cdnc run, loading tend to reduce buoyancy and updraft speed. When as depicted in Figure 5(b), are repeated by additionally ice-process-related latent heating is turned off as in the turning off rain evaporative cooling. In these sensitivity runs, control-BULK-no-ice-lt run and the 10M-BULK-no-ice-lt rain evaporation affects the rain mass but does not affect run, not only ice-process-related latent heating is removed temperature. -ese sensitivity simulations are the control- but also the associated increases in the loading of ice-phase BIN-no-rain-evp run, the 10M-BIN-no-rain-evp run, the hydrometeors are reduced. Effects of reduction in the control-BULK-no-rain-evp run, and the 10M-BULK-no- loading outweighs effects of the removal of ice-process- rain-evp run. By turning off rain evaporative cooling, we related latent heating, resulting in a slight increase in the remove a pathway for the aerosol to influence gust fronts updraft speed as in the control-BULK-no-ice-lt and the through aerosol effects on rain evaporative cooling. -e flux profile shapes are now more consistent amongst simulations 10M-BULK-no-ice-lt (Figure 6(d)). In other words, there is competition between effects of reduction in the loading and with the rain evaporative cooling turned off (Figure 7(a)). effects of the removal of ice-process-related latent heating in -e altitude of the updraft-mass-flux peak is 3.6–3.8 km the control-BULK-no-ice-lt and the 10M-BULK-no-ice-lt among the “no-rain-evp” runs, which is similar to 3.9 km in run. -is competition leads to just the slight change in the the control-BIN run and the 10M-BIN run. -e control- updraft mass flux in the control-BULK-no-ice-lt, as com- BIN-no-rain-evp run and the 10M-BIN-no-rain-evp run in pared to the control-BULK run, and in the 10M-BULK-no- Figure 7(a) still show strong aerosol influences on the up- ice-lt run, as compared to the 10M-BULK run (Figure 6(d)). draft mass fluxes in comparison with those in the control- Here, it is notable that snow gains its mass mainly BIN-noice-cdnc run and the 10M-BIN-noice-cdnc run in through other processes such as the riming of liquid hy- Figure 5(b). However, aerosol-related differences are small drometeors onto snow than deposition. -e time- and in the control-BULK-no-rain-evp run and the 10M-BULK- no-rain-evp run in Figure 7(a) in comparison with those in domain-averaged rate of the riming of liquid hydrometeors −2 −2 −1 onto snow is 8.391, 8.402, 8.261, and 8.333 ×10 g·m ·h , the control-BULK-noice-cdnc run and the 10M-BULK- noice-cdnc run in Figure 5(b). Associated with this, the while that of deposition is 1.011, 1.002, 0.582, and −2 −2 −1 0.551 × 10 g·m ·h in the control-BULK run, the 10M- peak value of the updraft-mass-flux profile varies slightly by −2 −1 BULK run, the control-BULK-no-ice-lt run, and the 10M- 2% from 0.41 kg·m ·s in the control-BULK-no-rain-evp −2 −1 BULK-no-ice-lt run, respectively. Here, we see that the run to 0.42 kg·m ·s in the 10M-BULK-no-rain-evp run, −2 −1 riming rate is around one order of magnitude greater than while the value varies by 9% from 0.44 kg·m ·s in the −2 −1 the deposition rate, and the riming rate shows insignificant control-BIN-no-rain-evp run to 0.48 kg·m ·s in the 10M- change around 1% or less changes between the control- BIN-no-rain-evp run. Comparing the simulations in BULK run and the control-BULK-no-ice-lt run or between Figures 5(b) to those in Figure 7(a), it appears that aerosol the 10M-BULK run and the 10M-BULK-no-ice-lt run. Due responses in BULK are controlled to a large extent by rain to this, despite substantial around 40–45% changes in the evaporative cooling and gust front generation; however, deposition rates between the control-BULK run and the those responses in BIN appear to be less sensitive to aerosol control-BULK-no-ice-lt run or between the 10M-BULK run influences on rain evaporation. and the 10M-BULK-no-ice-lt run, the snow loading does not change significantly in the control-BULK-no-ice-lt run, as 4.8. Cooling from Cloud-Liquid Evaporation. Recent studies compared to the control-BULK run, and in the 10M-BULK- no-ice-lt run, as compared to the 10M-BULK run. -e snow have shown that not only rain evaporative cooling but also cloud-liquid evaporative cooling can affect the intensity of loading, which is defined to be the time- and domain- averaged snow mass density, is 0.147, 0.152, 0.139, and gust fronts and aerosol effects on it. Hence, we hypothesize −3 that different treatments in the cloud-liquid evaporation 0.144 g·m in the control-BULK run, the 10M-BULK run, the control-BULK-no-ice-lt run, and the 10M-BULK-no- may explain some of the remaining differences in Figure 7(a). Based on this hypothesis, we repeat the control- ice-lt run, respectively. -is leads to the negligible changes in the shapes of the updraft-mass-flux vertical profile in the BIN-no-rain-evp run, the 10M-BIN-no-rain-evp run, the control-BULK-no-rain-evp run, and the 10M-BULK-no- control-BULK-no-ice-lt run, as compared to the control- BULK run, and in the 10M-BULK-no-ice-lt run, as com- rain-evp run in Figure 7(a) by additionally turning off pared to the 10M-BULK run (Figure 6(d)). cloud-liquid evaporative cooling. In these sensitivity runs, which are the control-BIN-no-cld-evp run, the 10M-BIN- no-cld-evp run, the control-BULK-no-cld-evp run, and the 4.7. Cooling from Rain Evaporation. It has been known that 10M-BULK-no-cld-evp run, cloud-liquid evaporation af- changes in rain evaporation, which are induced by aerosol, fects the cloud-liquid mass, but temperature is not altered by can cause those in the intensity of gust fronts and subsequent cloud-liquid evaporation. -e control-BIN-no-cld-evp run updrafts (e.g., [6, 15, 16]). Hence, the differences in updraft and the 10M-BIN-no-cld-evp run in Figure 7(b) show that mass fluxes in Figure 5(b) despite the fixed CDNC and the updraft mass fluxes are now much smaller and exhibit little removed ice processes may have been caused by changes in aerosol influences as compared to the control-BIN-no-rain- 20 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 2 2 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK-no-rain-evp Control-BULK Control-BULK-no-cld-evp Control-BULK 10M-BULK-no-rain-evp 10M-BULK 10M-BULK-no-cld-evp 10M-BULK Control-BIN-no-rain-evp Control-BIN Control-BIN-no-cld-evp Control-BIN 10M-BIN-no-rain-evp 10M-BIN 10M-BIN-no-cld-evp 10M-BIN (a) (b) Figure 7: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-rain- evp run, the 10M-BIN-no-rain-evp run, the control-BULK-no-rain-evp run, and the 10M-BULK-no-rain-evp run. (b) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-cld-evp run, the 10M-BIN-no-cld-evp run, the control-BULK-no-cld-evp run, and the 10M-BULK-no-cld-evp run. evp run and the 10M-BIN-no-rain-evp run in Figure 7(a), smaller in the control-BULK-no-cld-evp run as compared to particularly at altitudes below the tropopause where clouds the control-BULK-no-rain-evp run, and it is 40% smaller in form. -e tropopause is located around 12 km. Associated the 10M-BULK-no-cld-evp run as compared to the 10M- with this, below the tropopause, the peak value of the updraft- BULK-no-rain-evp run. −2 −1 mass-flux profile varies slightly by 2% from 0.20 kg·m ·s in While mass flux profile shapes are similar between the −2 −1 the 10M-BIN-no-cld-evp run to 0.21 kg·m ·s in the sensitivity simulations, as seen in Figure 7(b), there are still control-BIN-no-cld-evp run. -e altitude of the peak is significant differences in the magnitudes between the pair of 1.6 km, which is identical between the 10M-BIN-no-cld-evp the control-BIN-no-cld-evp run and the 10M-BIN-no-cld- run and the control-BIN-no-cld-evp run. -e peak value is evp run and that of the control-BULK-no-cld-evp run and 52% smaller in the control-BIN-no-cld-evp run as compared the 10M-BULK-no-cld-evp run below the tropopause (order to the control-BIN-no-rain-evp run, and it is 58% smaller in 30%). Overall, it can be said that both rain evaporative the 10M-BIN-no-cld-evp run as compared to the 10M-BIN- cooling and cloud-liquid evaporative cooling have strong no-rain-evp run. -e mass fluxes in the control-BULK-no- leverage on the mass flux profiles and the aerosol influence thereon. cld-evp run and the 10M-BULK-no-cld-evp run in Figure 7(b) also decrease in magnitude as compared to the control-BULK-no-rain-evp run and the 10M-BULK-no-rain- evp run in Figure 7(a), although to a lesser extent, particularly 4.9. Saturation. We hypothesize that the treatment of sat- at altitudes below the tropopause. Aerosol-related differences uration might explain remaining differences in Figure 7(b). are also small between the control-BULK-no-cld-evp run and To check this hypothesis, the control-BIN-no-cld-evp run the 10M-BULK-no-cld-evp run below the tropopause and the 10M-BIN-no-cld-evp run in Figure 7(b) are repeated (Figure 7(b)). Related to this, below the tropopause, the peak using the saturation adjustment treatment in BULK. -ese −2 −1 value varies slightly by 2% from 0.24 kg·m ·s in the control- sensitivity simulations are the control-BIN-sat run and the −2 −1 BULK-no-cld-evp run to 0.25 kg·m ·s in the 10M-BULK- 10M-BIN-sat run, and results from these sensitivity simu- no-cld-evp run. -e altitude of the peak is 1.7– 1.8 km, which lations are presented in Figure 8. Differences in the mag- nitude of the updraft mass fluxes between the pair of the is very similar between the control-BULK-no-cld-evp run and the 10M-BULK-no-cld-evp run. -e peak value is 41% control-BIN-sat run and the 10M-BIN-sat run and that of Height (km) Height (km) Advances in Meteorology 21 among the simulations in Figure 7(b). Based on this hy- pothesis, we repeat the simulations with BIN (i.e., the control-BIN-no-cld-evp run and the 10M-BIN-no-cld-evp run) in Figure 7(b) by using the same autoconversion and accretion schemes as in the simulations with BULK (i.e., the control-BULK-no-cld-evp run and the 10M-BULK-no-cld- evp run). -ese sensitivity simulations are the control-BIN- col run and the 10M-BIN-col run. With the identical autoconversion and accretion schemes between the pair of the control-BIN-col run and the 10M-BIN-col run and the pair of the control-BULK-no-cld-evp run and the 10M- BULK-no-cld-evp run, as seen in Figure 9, differences in the updraft-mass-flux profiles between these two pairs of simulations are now smaller as compared to the differences between the pair of the control-BULK-no-cld-evp run and the 10M-BULK-no-cld-evp run and that of the control-BIN- no-cld-evp run and the 10M-BIN-no-cld-evp run below the tropopause; note that the control-BIN-no-cld-evp run and the 10M-BIN-no-cld-evp run in Figure 7(b) are shown with dashed lines in Figure 9 and in Figure 9, and the control- BULK-no-cld-evp run and the con-BULK-no-cld-evp run in 0 0.1 0.2 0.3 0.4 –2 –1 Figure 7(b) are shown with the same lines as in Figure 7(b). Updraft mass flux (kg·m ·s ) Regarding the differences which get smaller, the peak value Control-BULK-no-cld-evp Control-BULK of the updrafts mass fluxes increases by 10% from 10M-BULK 10M-BULK-no-cld-evp −2 −1 0.21 kg·m ·s in the control-BIN-no-cld-evp run to Control-BIN-no-cld-evp Control-BIN −2 −1 0.23 kg·m ·s in the control-BIN-col run, while it increases 10M-BIN-no-cld-evp 10M-BIN −2 −1 by 10% from 0.20 kg·m ·s in the 10M-BIN-no-cld evp run Control-BIN-sat 10M-BIN-sat −2 −1 to 0.22 kg·m ·s in the 10M-BIN-col run although the Figure 8: Vertical distributions of the time- and domain-averaged altitude of the peak value does not change among these runs. updraft mass fluxes for the simulations in Figure 7(b), the control- -is results in around 10% differences between the pair of BIN-sat run, and the 10M-BIN-sat run. the control-BIN-col run and the 10M-BIN-col run and the pair of the control-BULK-no-cld-evp run and the 10M- BULK-no-cld-evp run, which are smaller than around the control-BULK-no-cld-evp run and the 10M-BULK-no- cld-evp run in Figure 8 are now slightly larger than those 30% differences between the pair of the control-BIN-no-cld- evp run and the 10M-BIN-no-cld-evp run and the pair of the between the pair of the control-BIN-no-cld-evp run and the 10M-BIN-no-cld-evp run and the pair of the control-BULK- control-BULK-no-cld-evp run and the 10M-BULK-no-cld- evp run. However, in Figure 9, there are still remaining no-cld-evp run and the 10M-BULK-no-cld-evp run below the tropopause; note that the control-BIN-no-cld-evp run differences in the fluxes among the simulations. Both and the 10M-BIN-no-cld-evp run in Figure 7(b) are shown autoconversion and accretion treatments seem to be of importance but are insufficient in explaining all differences with dashed lines in Figure 8 and in Figure 8, and the control-BULK-no-cld-evp run and the con-BULK-no-cld- in Figure 7(b). evp run in Figure 7(b) are shown with the same lines as in Figure 7(b). Regarding the differences which get larger, the 4.11. Sedimentation. We again hypothesize that one im- peak value of the updrafts mass fluxes reduces from −2 −1 portant remaining process—namely, sedimentation—might 0.21 kg·m ·s in the control-BIN-no-cld-evp run to −2 −1 explain the remaining differences in Figure 7(b). Based on 0.19 kg·m ·s in the control-BIN-sat run, while it reduces −2 −1 this hypothesis, the control-BIN-col run and the 10M-BIN- from 0.20 kg·m ·s in the 10M-BIN-no-cld evp run to −2 −1 col run in Figure 9 are repeated but with the version of 0.18 kg·m ·s in the 10M-BIN-sat run although the altitude sedimentation in BULK. -ese sensitivity simulations are of the peak value does not change among these runs. Here, the control-BIN-sed run and the 10M-BIN-sed run. As we see that the different treatment of saturation does not shown in Figure 10, differences, which are around 1–3%, help figure out the cause of the discrepancy between the BIN between the pair of the control-BIN-sed run and the 10M- simulations and the BULK simulations, as shown in BIN-sed run and the pair of the control-BULK-no-cld-evp Figure 7(b). run and the 10M-BULK-no-cld-evp run are now very small as compared to differences, which are around 30%, between the pair of the control-BIN-no-cld-evp run and the 10M- 4.10. Autoconversion and Accretion. We hypothesize that differences in the treatment of autoconversion and accretion BIN-no-cld-evp run and the pair of the control-BULK-no- cld-evp run and the 10M-BULK-no-cld-evp run below the of cloud ice and cloud liquid by precipitable hydrometeors may play a role in the differences in the updraft mass fluxes tropopause in Figure 7(b); note that the control-BIN-no-cld- Height (km) 22 Advances in Meteorology 16 16 14 14 8 8 6 6 4 4 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK-no-cld-evp Control-BULK Control-BULK-no-cld-evp Control-BULK 10M-BULK-no-cld-evp 10M-BULK 10M-BULK-no-cld-evp 10M-BULK Control-BIN-no-cld-evp Control-BIN Control-BIN-no-cld-evp Control-BIN 10M-BIN-no-cld-evp 10M-BIN 10M-BIN-no-cld-evp 10M-BIN Control-BIN-sed 10M-BIN-sed Control-BIN-col 10M-BIN-col Figure 10: Vertical distributions of the time- and domain-averaged Figure 9: Vertical distributions of the time- and domain-averaged updraft mass fluxes for the simulations in Figure 7(b), the control- updraft mass fluxes for the simulations in Figure 7(b), the control- BIN-sed run, and the 10M-BIN-sed run. BIN-col run, and the 10M-BIN-col run. the 10M-BULK-cdnc-only run in Figure 11(a), both BIN and evp run and the 10M-BIN-no-cld-evp run in Figure 7(b) are shown with dashed lines in Figure 10 and in Figure 10, and BULK show aerosol-induced enhancement of updraft mass fluxes as shown in “noice-cdnc runs.” Associated with this, the control-BULK-no-cld-evp run and the con-BULK-no- cld-evp run in Figure 7(b) are shown with the same lines as the peak value of the updraft-mass-flux profile increases by −2 −1 16% from 0.32 kg·m ·s in the control-BIN-cdnc-only run in Figure 7(b). Regarding this, the peak value in the updraft −2 −1 −2 −1 mass fluxes increases by 9% from 0.23 kg·m ·s in the to 0.37 kg·m ·s in the 10M-BIN-cdnc-only run, while it −2 −1 −2 −1 increases by 11% from 0.27 kg·m ·s in the control-BULK- control-BIN-col run to 0.25 kg·m ·s in the control-BIN- −2 −1 −2 −1 sed run, while it increases by 9% from 0.22 kg·m ·s in the cdnc-only run to 0.30 kg·m ·s in the 10M-BULK-cdnc- −2 −1 10M-BIN-col run to 0.24 kg·m ·s in the 10M-BIN-sed only run. -e altitude of the peak is 3.9 (2.8) km in the control-BIN-cdnc-only run and the 10M-BIN-cdnc-only run. Sedimentation treatment appears to be of significant importance in making differences in updraft mass fluxes run (the control-BULK-cdnc-only run and the 10M- BULK-cdnc-only run) as in the control-BIN run and the between the schemes. 10M-BIN run (the control-BULK run and the 10M-BULK run). -is confirms that different distributions of CDNC are 4.12. Tests for Individual Effects of CDNC, Rain, and Cloud- the main cause of different responses of updraft mass fluxes Liquid Evaporative Cooling, Saturation, Collection, and to increasing aerosol concentration between the micro- Sedimentation Processes. Some of the simulations above physical schemes, in comparison with the standard runs, as involve multiple microphysical processes which are modi- shown in “noice-cdnc” runs. fied together. Hence, as described in Section 3.3, this pre- As seen in the control-BIN-no-rain-evp-only run, the vents the isolation of individual effects of some of processes. 10M-BIN-no-rain-evp-only run, the control-BULK-no- To isolate effects of each of those processes, the standard rain-evp-only run, and the 10M-no-rain-evp-only run in simulations are repeated by modifying a process of interest Figure 11(b), aerosol-induced differences are smaller be- only. -e basic setup and naming of those repeated simu- tween the control-BULK-no-rain-evp-only run and the lations are described in Section 3.3, and here, their results are 10M-BULK-no-rain-evp-only run as compared to a situa- described as follows. tion between the control-BULK run and 10M-BULK run. As seen in the control-BIN-cdnc-only run, the 10M- Associated with this, aerosol-induced difference in the peak BIN-cdnc-only run, the control-BULK-cdnc-only run, and value between the control-BULK-no-rain-evp-only run and Height (km) Height (km) Advances in Meteorology 23 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK-cdnc-only Control-BULK Control-BULK-no-rain- Control-BULK 10M-BULK-cdnc-only 10M-BULK evp-only 10M-BULK 10M-BULK-no-rain-evp-only Control-BIN-cdnc-only Control-BIN Control-BIN 10M-BIN-cdnc-only 10M-BIN Control-BIN-no-rain-evp-only 10M-BIN 10M-BIN-no-rain-evp-only (a) (b) 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK Control-BIN-sat-only Control-BULK-no-cld- Control-BULK evp-only 10M-BULK 10M-BIN-sat-only 10M-BULK 10M-BULK-no-cld-evp-only Control-BIN Control-BIN Control-BIN-no-cld-evp-only 10M-BIN 10M-BIN 10M-BIN-no-cld-evp-only (c) (d) Figure 11: Continued. Height (km) Height (km) Height (km) Height (km) 24 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK Control-BIN-col-only Control-BULK Control-BIN-sed-only 10M-BULK 10M-BIN-col-only 10M-BULK 10M-BIN-sed-only Control-BIN Control-BIN 10M-BIN 10M-BIN (e) (f) Figure 11: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-cdnc- only run, the 10M-BIN-cdnc-only run, the control-BULK-cdnc-only run, and the 10M-BULK-cdnc-only run. (b) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-rain-evp-only run, the 10M-BIN-no-rain- evp-only run, the control-BULK-no-rain-evp-only run, and the 10M-BULK-no-rain-evp-only run. (c) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-cld-evp-only run, the 10M-BIN-no-cld-evp-only run, the control-BULK-no-cld-evp-only run, and the 10M-BULK-no-cld-evp-only run. (d) Vertical distributions of the time- and domain- averaged updraft mass fluxes for the standard runs, the control-BIN-sat-only run, and the 10M-BIN-sat-only run. (e) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-col-only run, and the 10M-BIN-col-only run. (f) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-sed-only run, and the 10M-BIN-sed-only run. the 10M-BULK-no-rain-evp-only run is less than between the control-BIN-no-cld-evp-only run and the 10M- −2 −1 0.01 kg·m ·s , and this is 80% smaller than that difference BIN-no-cld-evp-only run as compared to a situation be- between the control-BULK run and the 10M-BULK run. -e tween the control-BIN run and 10M-BIN run. Associated altitude of the peak in the control-BULK-no-rain-evp-only with this, the aerosol-induced difference in the peak value run and the 10M-BULK-no-rain-evp-only run is 2.8 km as in between the control-BIN-no-cld-evp-only run and the 10M- −2 −1 the control-BULK run and the 10M-BULK run. However, BIN-no-cld-evp-only run is 0.01 kg·m ·s , and this is 86% aerosol-induced differences are greater between the control- smaller than that difference between the control-BIN run BIN-no-rain-evp-only run and the 10M-BIN-no-rain-evp- and the 10M-BIN run. -e altitude of the peak in the only run than between the control-BIN run and the 10M- control-BIN-no-cld-evp-only run and the 10M-BIN-no-cld- BIN run. Associated with this, the aerosol-induced differ- evp-only run is 3.9 km as in the control-BIN run and the ence in the peak value between the control-BIN-no-rain- 10M-BIN run. However, the aerosol-induced difference evp-only run and the 10M-BIN-no-rain-evp-only run is between the control-BULK-no-cld-evp-only run and the −2 −1 0.09 kg·m ·s , and this is 29% greater than that difference 10M-BULK-no-cld-evp-only run is 18% different from that between the control-BIN run and the 10M-BIN run. -e between the control-BULK run and the 10M-BULK run in altitude of the peak in the control-BIN-no-rain-evp-only run terms of the peak values. -is demonstrates that aerosol and the 10M-BIN-no-rain-evp-only run is 3.9 km as in the responses in BIN, but not BULK, are controlled to a large control-BIN run and the 10M-BIN run. -is confirms that extent by cloud-liquid evaporative cooling, as shown in “no- aerosol responses in BULK, but not BIN, are controlled to a cld-evp” runs. large extent by rain evaporative cooling and gust front As seen in Figure 11(d), differences between the pair of generation, as shown in “no-rain-evp” runs. the control-BIN-sat-only run and the 10M-BIN-sat-only run As seen in the control-BIN-no-cld-evp-only run, the and the pair of the control-BULK run and the 10M-BULK 10M-BIN-no-cld-evp-only run, the control-BULK-no-cld- run are slightly greater than those between the pair of the evp-only run, and the 10M-BULK-no-cld-evp-only run in control-BIN run and the 10M-BIN run and the pair of the Figure 11(c), aerosol-induced differences are much smaller control-BULK run and 10M-BULK run. Associated with Height (km) Height (km) Advances in Meteorology 25 −2 −1 this, a difference in the mean peak value between the pair of by 4% from 0.25 kg·m ·s in the 10M-BULK run to −2 −1 the control-BIN-sat-only run and the 10M-BIN-sat-only run 0.24 kg·m ·s in the 10M-BULK-2 mt run. Also, there is an and the pair of the control-BULK run and the 10M-BULK increase in updraft mass fluxes above 4 km in the control- run is 33% greater than that between the pair of the control- BULK-2 mt run, as compared to the control-BULK run, and BIN run and the 10M-BIN run and the pair of the control- in the 10M-BULK-2 mt run, as compared to the 10M-BULK BULK run and 10M-BULK run. -e altitude of the peak in run. -is is because the use of the two-moment scheme the control-BIN-sat-only run and the 10M-BIN-sat-only run induces increases in the mass or loading of snow and graupel is 3.9 km as in the control-BIN run and the 10M-BIN run. at low altitudes around 4 km and decreases in the mass at Remember that the mean peak value between the control- high altitudes above 4 km, which is similar to findings by −2 −1 BULK run and the 10M-BULK run is 0.26 kg·m ·s , while Wacker and Seifert [41]. the mean value between the control-BIN run and the 10M- Figure 10 shows the final comparison between BIN and −2 −1 BIN run is 0.32 kg·m ·s . -e mean peak value between the BULK. Hence, as another good example of how the two- control-BIN-sat-only run and the 10M-BIN-sat-only run is moment prediction affects results here, Figures 10 and 12(b) −2 −1 0.34 kg·m ·s . -is confirms that the different treatment of are compared. In Figure 12(b), results from the repeated saturation is not able to explain the cause of the discrepancy control-BULK-no-cld-evp run and the 10M-BULK-no-cld- between the BIN simulations and the BULK simulations. As evp run with two-moment prediction for snow and graupel seen in Figures 11(e) and 11(f), differences between the pair are shown together with some of simulations that are depicted of the control-BIN-col-only run (the control-BIN-sed-only in Figure 10 and are the control-BIN-sed run, the 10M-BIN- run) and the 10M-BIN-col-only run (the 10M-BIN-sed-only sed run, the control-BIN-no-cld-evp run, and the 10M-BIN- run) and the pair of the control-BULK run and 10M-BULK no-cld-evp run; these sensitivity runs with two-moment run are smaller than those between the pair of the control-BIN prediction are the control-BULK-no-cld-evp-2 mt run and run and the 10M-BIN run and the pair of the control-BULK the 10M-BULK-no-cld-evp-2 mt run. Comparisons between run and 10M-BULK run. Associated with this, a difference in Figures 10 and 12(b) demonstrate that whether graupel and the mean peak value between the pair of the control-BIN-col- snow adopt the two-moment prediction in BULK does not only run (the control-BIN-sed-only run) and the 10M-BIN- affect the very small differences in updraft mass fluxes be- col-only run (the 10M-BIN-sed-only run) and the pair of the tween the pair of the control-BIN-sed run and the 10M-BIN- control-BULK run and 10M-BULK run is 50 (33)% smaller sed run and the pair of “BULK-no-cld-evp” runs. than that between the pair of the control-BIN run and the 10M-BIN run and the pair of the control-BULK run and 10M- 5. Summary and Conclusions BULK run. -e mean peak value between the control-BIN- col-only run (the control-BIN-sed-only run) and the 10M- -is study mainly focuses on and examines key micro- BIN-col-only run (the 10M-BIN-sed-only run) is 0.23 (0.22) physical processes that cause differences in the simulations −2 −1 kg·m ·s . -e altitude of the peak in the control-BIN-col- of clouds and aerosol-cloud interactions between two mi- only run, the control-BIN-sed-only run, the 10M-BIN-col- crophysical schemes, i.e., BIN and BULK. For this exami- only run, and the 10M-BIN-sed-only run is 3.9 km as in the nation, this study focuses on differences in updrafts, which control-BIN run and the 10M-BIN run. -is confirms that are represented by updraft mass fluxes, and their response to different autoconversion and accretion (sedimentation) increasing aerosol concentration between BIN and BULK. treatment play an important role in explaining differences Aerosol-induced invigoration of convection is simulated between the BIN simulations and the BULK simulations as with BIN, but not simulated with BULK. Stated differently, shown in the control-BIN-col run and the 10M-BIN-col run there are aerosol-induced increases in updraft mass fluxes (the control-BIN-sed run and the 10M-BIN-sed run). with BIN, while there are no aerosol-induced those increases with BULK. -e profile or pattern of the vertical distribution of updraft mass fluxes with BULK is substantially different 4.13. Two-Moment Prediction for Snow and Graupel. As from that with BIN in terms of the altitude and magnitude of exemplified by Figure 12(a), comparisons among the con- the updraft-mass-flux peak and the vertical variation of trol-BULK-2 mt run and the 10M-BULK-2 mt run with the updraft mass fluxes around it. Results here indicate that two-moment prediction for snow and graupel and the whether the invigoration is present or not is strongly de- previous runs with the one-moment prediction for snow and pendent on how CDNC is predicted. -e different pattern of graupel as in the control-BULK run and the 10M-BULK run the updraft-mass-flux distribution between the schemes is demonstrate that the qualitative nature of results does not due to much larger snow mass and associated loading vary with the varying prediction method for snow and around the freezing level in the simulations with BULK than graupel. However, as seen in Figure 12(a), with the use of the those with BIN. -e much greater loading of snow mass two-moment prediction, the altitude of the distribution peak hinders the growth of updraft mass fluxes around the and the peak value is lowered. -e altitude of peak lowers by freezing level. -is lowers the altitude and magnitude of the 32% from 2.8 km in the control-BULK run and the 10M- updraft-mass-flux peak and causes much larger vertical BULK run to 1.9 km in the control-BULK-2 mt run and the variation of updraft mass fluxes around the altitude where 10M-BULK-2 mt run, while the peak value lowers by 3% the peak occurs in the BULK simulations. It is notable that −2 −1 from 0.27 kg·m ·s in the control-BULK run to the latent heating or cooling associated with ice processes −2 −1 0.26 kg·m ·s in the control-BULK-2 mt run, and it lowers does not affect the vertical pattern of updraft mass fluxes in 26 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK-no-cld-evp-2mt Control-BULK Control-BULK Control-BULK-2mt 10M-BULK 10M-BULK-2mt 10M-BULK-no-cld-evp-2mt 10M-BULK Control-BIN Control-BIN-no-cld-evp Control-BIN 10M-BIN-no-cld-evp 10M-BIN 10M-BIN Control-BIN-sed 10M-BIN-sed (a) (b) Figure 12: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-2 mt run, and the 10M-BULK-2 mt run. (b) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the simulations in Figure 10 except for the fact that the control-BULK-no-cld-evp run and the 10M-BULK-no-cld-evp run are replaced with the control- BULK-no-cld-evp-2 mt run and the 10M-BULK-no-cld-evp-2 mt run. the simulations with BULK much as compared to the With the fixed CDNC, removed ice processes, and loading of snow. evaporative cooling, the vertical pattern of updraft mass Although differences in the CDNC prediction and ice fluxes shows negligible differences between simulations with BIN and those with BULK and the variation in updraft mass processes (including the snow process) are removed, thus, the differences in the invigoration are removed and those in fluxes from the high-aerosol case to the low-aerosol case for each of BIN and BULK is nearly removed. However, there the pattern of the vertical distribution of updraft mass fluxes are nearly removed between the simulations with BIN and are still remaining differences in the magnitude of updraft those with BULK, there are still remaining differences. mass fluxes between the simulations with BULK and those Among these remaining differences, differences between the with BIN. -ese remaining differences are explained by high-aerosol case and the low-aerosol case for each of BIN different treatments of collection and sedimentation pro- and BULK are controlled by aerosol-induced changes in cesses; however, the impact of the different treatments of evaporation-related cooling and the associated gust front saturation on the remaining differences is negligible. -is intensity. While the differences in updraft mass fluxes are qualitative nature of roles by collection, sedimentation, and explained by different rain evaporative cooling between the saturation processes in explaining differences between the BULK simulations and the BIN simulations is also produced high-aerosol case and the low-aerosol case with BULK, those differences in cooling, due to rain evaporation, do not ex- in the repeated standard runs where only each of these plain those differences in updraft mass fluxes with BIN. processes is tested. -ose differences in updraft mass fluxes with BIN are -ere are around dozens or more of microphysical explained by the differences in cloud-liquid evaporative schemes that have been created. Also, each scheme has its cooling. -is qualitative nature of roles by each of rain and own different versions. It would be the best strategy to cloud-liquid evaporative cooling in explaining differences compare all of those present schemes and their different between the high-aerosol case and the low-aerosol case for versions for obtaining perfectly general conclusions. How- each of BIN and BULK is also produced in the repeated ever, performing process-level research as shown in this paper by modifying each microphysical process in the model standard simulations where only rain or cloud-liquid evaporative cooling is turned off. code requires a large amount of time and computer Height (km) Height (km) Advances in Meteorology 27 processes not tested in this study. Despite this, it is believed resources even for the comparison between the selected two schemes. Unfortunately, the funding, associated time, and that the fact that processes tested in this study explain most of differences between the schemes should be considered as computer resources given are not enough to perform process-level research for all of present microphysical an important finding based on which we can gain a pre- schemes and their different versions. Maybe, comparing all liminary understanding of key processes, and thus, this study of those present schemes for one or two specific processes achieves its main goal. such as autoconversion and/or sedimentation may be pos- sible. -ere are studies such as Liu and Daum [44] and Lee Data Availability and Baik [45] that compare more than two microphysical schemes for a specific process; however, these studies also do -e data used are currently private and stored in our private not deal with all of present schemes due to limit on time and computer system. Opening the data to the public requires computer resources. Considering the limit on time and approval from the funding source. Since the funding project resources, we have to make a compromise between process- associated with this work is still going on, the source does not level research which tests numerous microphysical processes allow the data to be open to the public, and 2-3 years after the individually and the number of microphysical schemes that project ends, the data can be open to the public. However, if are tested. In the process of making the compromise, this there is any inquiry about the data, contact the corresponding study leans toward process-level research by sacrificing the author Seoung Soo Lee (cumulss@gmail.com). number of microphysical schemes tested and associated generality of results. -is is motivated by the fact that, as Disclosure stated in introduction, the identification of key processes, which create the discrepancy in the simulation of the Seoung Soo Lee is now at Department of Meteorology, San feedbacks between increasing aerosol concentration, mi- Jose State University, San Jose, CA, USA. crophysics, and dynamics among models, has been rarely performed, and the community does not have even a pre- Conflicts of Interest liminary and basic understanding of those key processes themselves; note that the identification of key processes -e authors declare that they have no conflicts of interest. requires process-level research as shown in this study. Hence, through process-level research, this study provides Acknowledgments preliminary, though not general, information on those key processes, by comparing the limited number of schemes, as a -is study was supported by NOAA (NOAA-NWS-NWSPO- stepping stone to the general information which can be 2015-2004117), NASA/MUREP Cooperative Agreement pursued in the future studies. Considering that the in- (NNX15AQ02A), the Ministry of Education (NRF-2018R1D formation on those key processes has been near absent, it is 1A1A09083227), and the National Strategic Project-Fine believed that this preliminary information itself is valuable Particle of the National Research Foundation of Korea by providing a preliminary clue to how to approach the (NRF) funded by the Ministry of Science and ICT (MSIT), the discrepancy among models, despite the fact that compari- Ministry of Environment (MOE), and the Ministry of Health sons for the limited number of schemes are not as perfect as and Welfare (MOHW) (NRF-2017M3D8A1092022). It was those between all of the present schemes. also supported by the National Institute of Environment Re- It should be reiterated that the main goal of this study is search (NIER), funded by the MOE (NIER-2018-01-02-033), to identify “key” processes, but not all processes, which and via Public Technology Program Based on Environmental contribute to differences in updrafts and their responses to Policy (2017000160003). increasing aerosol concentration between the schemes. -e first reason for not focusing on all those processes is that we References even do not know what those key processes are to say nothing of all those processes and thus identifying those key [1] M. Bollasina and S. 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Comparison of Simulations of Updraft Mass Fluxes and Their Response to Increasing Aerosol Concentration between a Bin Scheme and a Bulk Scheme in a Deep-Convective Cloud System

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Hindawi Advances in Meteorology Volume 2019, Article ID 9292535, 29 pages https://doi.org/10.1155/2019/9292535 Research Article Comparison of Simulations of Updraft Mass Fluxes and Their Response to Increasing Aerosol Concentration between a Bin Scheme and a Bulk Scheme in a Deep-Convective Cloud System 1 2 3 4 Seoung Soo Lee , Chang-Hoon Jung, Sen Chiao , Junshik Um , 5 6 Yong-Sang Choi, and Won Jun Choi Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, Maryland, USA Department of Health Management, Kyungin Women’s University, Incheon, Republic of Korea Center for Applied Atmospheric Research and Education, San Jose State University, San Jose, California, USA Department of Atmospheric Sciences, Pusan National University, Busan, Republic of Korea Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea National Institute of Environmental Research, Incheon, Republic of Korea Correspondence should be addressed to Seoung Soo Lee; cumulss@gmail.com Received 21 December 2018; Revised 19 February 2019; Accepted 12 March 2019; Published 12 June 2019 Academic Editor: Pedro Jime´nez-Guerrero Copyright © 2019 Seoung Soo Lee et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Key microphysical processes whose parameterizations have substantial impacts on the simulation of updraft mass fluxes and their response to aerosol are investigated in this study. For this investigation, comparisons of these parameterizations are made between a bin scheme and a bulk scheme. -ese comparisons show that the differences in the prediction of cloud droplet number concentration (CDNC) between the two schemes determine whether aerosol-induced invigoration of updrafts or convection occurs. While the CDNC prediction leads to aerosol-induced invigoration of updrafts and an associated 20% increase in the peak value of the updraft-mass-flux vertical profile in the bin scheme, it leads to aerosol-induced suppression of updrafts and an associated 7% decrease in the peak value in the bulk scheme. -e comparison also shows that the differences in ice processes, in particular, in the snow loading lead to the different vertical patterns of the updraft-mass-flux profile, which is represented by the peak value and its altitude, between the schemes. Higher loading of snow leads to around 20–30% higher mean peak value and its around 40% higher altitude in the bin scheme than in the bulk scheme. When differences in the CDNC prediction and ice processes are removed, differences in the invigoration and the vertical pattern disappear between the schemes. However, despite this removal, differences in the magnitude of updraft mass fluxes still remain between the schemes. Associated with this, the peak value is around 10% different between the schemes. Also, after the removal, there are differences in the magnitude between cases with different aerosol concentrations for each scheme. Associated with this, the peak value is also around 10% different between those cases for each scheme. -e differences between the cases with different aerosol concentrations for each scheme are generated by different evaporative cooling and different intensity of gust fronts between those cases. -e remaining differences between the schemes are generated by different treatments of collection and sedimentation processes. tropopause and are well-known modulators of global 1. Introduction dynamic, hydrological, and energy circulations since Recent studies have shown that convective clouds, which these clouds form (1) the cloud regime that regulates a include deep convective clouds, are substantially affected significant portion of global momentum and shortwave by aerosol-cloud interactions and associated feedbacks and longwave radiation and (2) generates the largest between increasing aerosol concentration, microphysics, portion of the global precipitation [8–10]. Hence, the and dynamics [1–7]. -ese deep clouds grow to reach the interactions between aerosol and clouds and associated 2 Advances in Meteorology comparison, it is well accepted that there are two types of feedbacks in deep clouds are essential for understanding climate change. microphysics schemes, which are bin schemes and bulk schemes [21]. It is believed that there are more substantial or -e invigoration of convection is a well-known repre- sentation of the feedbacks between increasing aerosol greater differences in the representation of microphysics concentration, microphysics, and dynamics in deep clouds between these schemes than among bin schemes themselves [11, 12]. It has been suggested that an aerosol perturbation or bulk schemes themselves since bin schemes and bulk (or increasing aerosol concentration) enhances freezing and schemes have fundamental differences between them cloud buoyancy, which leads to the invigoration of con- [21, 25–27]. A good example of these fundamental differ- vection that accompanies increases in the intensity of up- ences is that, in bin schemes, hydrometeor size distributions are explicitly predicted, while in bulk schemes, assumed drafts and cloud top heights [11] Figure 1). However, there is a wide variety of reported responses of deep convective forms of the distributions are used. -is motivates this study to focus on comparisons between a bin scheme and a bulk clouds to aerosol perturbations in simulations [3, 6, 12, 15–17]. For example, some studies have shown scheme but not on those between bin schemes or between bulk schemes. For these comparisons, we try to select a strong aerosol-induced invigoration for both cloud systems and single clouds, while others have not even for identical representative bin scheme and a representative bulk scheme cases [3, 12, 17]. Aerosol-induced invigoration is well known to draw representative and preliminary, though not general, to be dependent on environmental and aerosol conditions conclusions from the comparisons. -e reality is that [14, 18–20]. However, each of these identical cases has comparisons between bin schemes themselves or between identical environmental and aerosol conditions. -is in- bulk schemes themselves or between bin schemes and bulk dicates that the differences in invigoration among simula- schemes, in terms of numerous individual microphysical processes, are not established adequately well [21]. Hence, tions are not caused by environmental and aerosol conditions and demonstrates that some modeling frame- we do not have general statistical information on which bin scheme or which bulk scheme is representative in terms of works appear to have a propensity to manifest invigoration while others do not [3, 12, 17]. -is exemplifies that the representation of numerous individual microphysical pro- cesses [21]. We also do not have general information on simulated feedbacks between increasing aerosol concen- tration, microphysics, and dynamics are strongly dependent which pair of a bin scheme and a bulk scheme shows on modeling frameworks and has been raising questions representative differences between bin schemes and bulk about the credibility of the simulated feedbacks including schemes regarding those representations [21]. Based on this, aerosol-induced invigoration. instead of trying to select perfectly representative schemes, As a first step to deal with this credibility issue, we have this study relies on rather subjective criteria for the selection to identify key cloud processes that create the discrepancy in of the schemes. -e subjective criteria indicate that a selected scheme for bin approach, which is the scheme of Khain and the simulation of the feedbacks among models. -e iden- tification of key processes in turn enables us to identify key Lynn [28], and a selected scheme for bulk approach, which is the scheme of -ompson and Eidhammer [29], for this study quantified causes of the discrepancy and thus acts as a valuable stepping stone to resolve the credibility issue. have been implemented into widely used models such as the Motivated by this, as a first step to resolve the credibility Advanced Research Weather Research and Forecasting issue, this paper focuses on microphysics representations (ARW) model and thus frequently used. Stated differently, and aims to identify and gain a preliminary understanding of the subjective criteria indicate that conclusions from com- key represented microphysical processes whose different parisons between these two selected schemes can have some representations play a key role in the discrepancy in the level of broad implications though not perfectly general simulation of the feedbacks among models. Note that the implications. -ese subjective criteria follow that in other identification of the key processes has been rarely performed representative studies, which compare schemes and select two schemes for the comparison, such as the study of and the community does not have a clear understanding of those processes themselves [21–24]. -e identification of Dawson et al. and Morrison et al. [30, 31]. -e comparison between the selected schemes enables those key processes provides the community with focal processes that the community should pay more attention to the isolation of the influences of the representation (or and thus enables it to resolve the credibility issue efficiently. parameterization) of microphysical processes on the dis- Based on this, the identification itself can be considered a crepancy, which acts as a basis on which the isolation of the valuable effort [21–24]. Hence, this study primarily aims to key microphysical processes can be performed. A series of achieve the identification itself. -is means that this study numerical simulations is performed in which the impact of does not take interest in understanding detailed mechanisms the representations of microphysical processes on the dis- crepancy in the simulations of the feedbacks between in- through which those identified processes affect the dis- crepancy in the simulation of the feedbacks. creasing aerosol concentration, microphysics, and dynamics is examined. -e goal of this study is to identify a set of key To fulfill the primary aim, this study compares aerosol influences on tropical deep convection between two fre- microphysical processes whose differences account for most of the discrepancy between the schemes. Note that the quently used microphysical schemes within a common dynamical framework and common model setup (grid representation of the feedbacks in climate models is the resolution, domain configuration, initial conditions, and primary cause of uncertainties in the prediction of climate forcing). Regarding the selection of the two schemes for the changes [32]. -e different feedbacks among different Advances in Meteorology 3 With no pollution (clean) With aerosol pollution (polluted) 0°C Initial Mature Initial Mature Cloud-generated airflow Small cloud droplets Cloud-generated airflow Small cloud droplets Aerosol Large ice crystals Aerosol Large ice crystals Large cloud droplets Large cloud droplets Small ice crystals Small ice crystals (a) (b) Figure 1: (a) Airflow generated by convective clouds carries water droplets upwards, leading to the formation of ice crystals in the upper cloud layers. (b) Aerosol pollution (or perturbation) leads to formation of more ice crystals and latent-heat release upon ice crystal formation, which stimulates the updrafts and the vertical growth of clouds (adapted from Lee [13]). microphysical schemes contribute substantially to those Fouquart and Bonnel [35], is utilized to represent radiation uncertainties by producing a large variation of the feedbacks processes. and their impacts on climate changes among different cli- -e microphysical processes are represented by two mate models that are coupled to different microphysical microphysical schemes (or representations). -ey are the bin scheme of Khain and Lynn [28] and the double-moment schemes [12, 21, 32]. As a way of reducing this variation as a process of reducing the uncertainties, we need to identify the bulk microphysics scheme of -ompson and Eidhammer key microphysical processes whose differences explain most [29]. Here, it should be noted that, in the scheme of of the variation and develop the schemes in a way that -ompson and Eidhammer [29], cloud liquid, snow, and reduces the variation associated with the representation of graupel adopt the one-moment prediction of mass-mixing the key processes. By concentrating on development efforts ratio, while cloud ice and rain adopt the two-moment on these key processes, but not all numerous microphysical prediction of mass-mixing ratio and number concentra- processes, the development of the schemes can be performed tion. Henceforth, the former scheme is referred to as “BIN,” efficiently. while the latter scheme is referred to as “BULK.” In both of Accordingly, we aim to find key microphysical processes the two microphysics schemes, aerosol mass is prognosed by that collectively remove most of the discrepancy when considering advection, diffusion, and activation-induced differences in these processes between the schemes are re- removal of the aerosol mass-mixing ratio. moved collectively. Hence, in a large portion of simulations In both microphysics schemes, Ko¨hler theory is applied to in this study, differences in the processes between the droplet activation. When the predicted parcel supersaturation schemes are collectively removed. In other words, in a large for BIN and the diagnosed parcel supersaturation for BULK portion of simulations, differences in two or more potential are higher than critical supersaturation of aerosol particles, key processes between the schemes are removed together they are assumed to be activated. -e aerosol size distribution rather than differences in each of processes removed in- is assumed to follow the lognormal distributions, and it is dividually. We do not try to cover the huge parameter space assumed that ammonium sulfate comprises aerosol in both of that might need to be explored. Instead, we focus on up- the schemes. -e size distribution, which is at the initial time drafts, which are represented by updraft mass fluxes, and one step and for background aerosol, at the altitude of 0.5 km is of the important indicators of the feedbacks and associated depicted in Figure 2. At the other altitudes, background invigoration [11, 12, 18]. aerosol follows this initial size distribution as well although the initial total concentration of background aerosol varies with altitudes, as exemplified in Figure 3. Figure 3 shows the 2. Cloud-System Resolving Model (CSRM) vertical variation of the initial total concentration of back- -e ARW model is employed for this study. -e ARW ground aerosol which is adopted by this study and for the model functions as a CSRM, and this model is not only accumulation mode only. Note that a largest portion of cloud nonhydrostatic but also compressible. A higher-order condensation nuclei (CCN) is well known to be included in scheme, which is developed by Wang et al. [33], is used the accumulation mode when it comes to a general super- for the advection of variables, which are particularly related saturation regime. In the accumulation mode, the initial to microphysics. -e rapid radiation transfer model background aerosol number concentration in the planetary −3 (RRTMG), which is described by Mlawer et al. [34] and boundary layer is around 100 cm and it reduces to around 4 Advances in Meteorology Aerosol size distribution supersaturation in BIN. In contrast to this, a saturation adjustment in BULK diagnoses the diffusion by taking water vapor and temperature in the environment into account. While BIN does not assume a specific type of the size distribution of hydrometeors and does make explicit pre- diction of the distribution, BULK uses basis functions (gamma) with fixed breadth parameters for the size distri- bution of hydrometeors. In BIN, the size distribution of each –2 –1 0 1 10 10 10 10 hydrometeor class is discretized into 33 size bins and hy- D (diameter, micron) drometeor number and mass in each size bin is explicitly Figure 2: Initial aerosol size distribution at the altitude of 0.5 km. predicted. When hydrometeors collide with and collect each N represents the aerosol number concentration per unit volume of other, at each grid point, to represent the collection, col- air and D the aerosol diameter. lection efficiency for each combination of a size of collecting hydrometeor and that of collected hydrometeor is obtained in BIN. Note that there are 33 times 33 combinations of sizes Aerosol vertical distribution in BIN, for example, when it comes to collection between two different classes of hydrometeors in BIN. Hence, the- oretically, 33 times 33 different collection efficiency values are used for the representation of the collection processes between two different classes of hydrometeors at each grid point in BIN. In BIN, for the representation of sedimen- tation processes, at each grid point, each terminal velocity, which varies with varying size bin, in each size bin is ob- tained and hydrometeors in each size bin fall down based on terminal velocity in each bin. Hence, for the representation of sedimentation processes, there are 33 different terminal velocities for each hydrometeor class at each grid point. BULK uses a one-value mass (number) weighted terminal velocity for the sedimentation of hydrometeor mass (number) at each grid point. BULK uses a one-value col- lection efficiency that is calculated by using the mean volume sizes of collecting and collected hydrometeors at each grid point. In this study, the effect of aerosol on radiation via 50 100 –3 Aerosol concentration (cm ) reflection, scattering, and absorption of radiation by aerosol before its activation is not considered. Figure 3: Initial vertical distribution of total aerosol concentration in the accumulation mode. 3. Simulation Design −3 −3 70 cm at the altitude of 2 km and then to 20 cm at the 3.1. Case. An adopted case for this study is an observed altitude of 10 km (Figure 3). It is assumed that the distribution mesoscale system. -is system involved deep convective parameters such as modal diameter and standard deviation of clouds. -is system was observed between 12 : 00 LST (local the distribution are fixed over all grid points and the whole solar time) on January 23th and 12 : 00 LST on January 25th simulation period for each mode of the distribution. -is in 2006. -is observation was performed by the TWP-ICE means that the form of the distribution in Figure 2 is taken by campaign which occurred in Darwin, Australia. -e latitude aerosol over all grid points and the whole period. However, and longitude of the campaign site were 12.47 S and aerosol total number concentration is subject to the spatio- ° 130.85 W, respectively [36]. temporal variation since clouds affect aerosol mass as men- tioned above. -e assumed fixed form of size distribution may overmeasure CCN for nucleation in clouds, which is referred 3.2. Model Setup. A two-day simulation is performed for the to as secondary nucleation. However, in strong convection in adopted case with BULK, which is named the control-BULK deep clouds here, primary nucleation, which occurs in cloud- run. For the simulation, the length of the domain in the free condition, depletes most of CCN; thus, the secondary horizontal direction is set at 120 km whether it is the east- nucleation plays a negligible role in nucleation, other related west or north-south direction and this length enables the microphysical processes, and cloud dynamics (e.g., updraft). simulation of the mesoscale structure of the system. -e -is indicates that the weakness from the assumption of the length over the vertical direction is 20 km, and this enables fixed form is not likely to play an important role in results us to capture deep convective clouds a portion of which can here. grow to the tropopause. 1 km grid spacing in the horizontal Note that the diffusion of water vapor onto hydrome- direction and a varying grid spacing from approximately teors is explicitly calculated by using the predicted 50 m around the surface to approximately 500 m around the –3 dN/d lnD (cm ) Height (km) Advances in Meteorology 5 simulation period. -ese additional sensitivity simulations model top in the vertical direction are used to resolve convective cores. are named the control-BIN-noice-cdnc run, the 10M-BIN- noice-cdnc run, the control-BULK-noice-cdnc run, and the Horizontal boundary conditions are periodic conditions, as described in Fridlind et al. [37]. Observed surface sensible 10M-BULK-noice-cdnc run. Effects of the loading of graupel and latent heat fluxes are imposed at the surface. Large-scale and snow, which explains a large portion of the total loading, forcings of potential temperature and specific humidity as are tested by repeating the standard simulations by removing advective tendencies are provided by the TWP-ICE obser- the loading of each of graupel and snow. -ese sensitivity vations. -ese forcings dictate the net energy and water simulations are named the control-BIN-s run, the 10M-BIN- budget in the domain but not cloud-scale processes. -e s run, the control-BIN-g run, the 10M-BIN-g run, the control-BULK-g run, the 10M-BULK-g run, the control- process of relaxing the horizontal momentum to observed counterpart is applied. BULK-s run, and the 10M-BULK-s run. We test effects of latent-heat processes related to ice hydrometeors or processes, those to rain evaporation, and 3.3. Additional Runs. -e control-BULK run is repeated to those to cloud-liquid evaporation based on recent studies that look into how aerosol affects updrafts. -is sensitivity run is show importance of those processes (e.g., [11, 17, 39, 40]). To performed by escalating the initial aerosol concentration in test effects of latent-heat processes related to ice hydrome- the background by a factor of 10. -is run is named “the teors, the standard runs with BULK are repeated by turning 10M-BULK run.” -en, to examine the sensitivity of up- off ice-related latent-heat processes and these sensitivity runs drafts and the effect of aerosol on them to microphysics are named control-BULK-no-ice-lt run and the 10M-BULK- representations via comparisons between BULK and BIN, no-ice-lt run. To test those effects related to rain evaporation, we repeat the control-BULK run and the 10M-BULK run by the control-BIN-noice-cdnc run, the 10M-BIN-noice-cdnc replacing BULK with BIN. -ese sensitivity runs are named run, the control-BULK-noice-cdnc run, and the 10M- “the control-BIN run” and “the 10M-BIN run.” -ese four BULK-noice-cdnc run are repeated by turning off rain simulations constitute “the standard simulations” in this evaporative cooling. -ese sensitivity simulations are named study. the control-BIN-no-rain-evp run, the 10M-BIN-no-rain-evp Updrafts are strongly controlled by the buoyancy of a run, the control-BULK-no-rain-evp run, and the 10M-BULK- rising air parcel [9, 38]. -e buoyancy is in turn controlled by no-rain-evp run. To test those effects related to cloud-liquid the loading of hydrometeors, latent-heat processes, and evaporation, the sensitivity simulations with rain evaporative associated microphysical processes [9, 38]. Based on recent cooling turned off are repeated by turning off cloud-liquid studies such as Rosenfeld et al. [11] and Lee et al. (2013), this evaporative cooling, and these additional sensitivity simula- paper focuses on latent-heat processes which are associated tions are named the control-BIN-no-cld-evp run, the 10M- with not only solid or ice hydrometeors but also liquid BIN-no-cld-evp run, the control-BULK-no-cld-evp run, and hydrometeors. Here, we deal with microphysical processes the 10M-BULK-no-cld-evp run. that are related to overall life cycle of cloud particles: the To understand the role played by microphysical pro- formation of cloud particles, their growth, interactions cesses related to the particle growth in the simulation of between solid particles and liquid particles, which are as- updrafts and aerosol effects on them, we test effects of sociated with the invigoration of convection, and their saturation and collection processes (i.e., autoconversion and sedimentation to the ground. -e classic theory in cloud accretion) on the simulation. To test effects of saturation physics indicates that the formation of cloud particles is (collection processes), the control-BIN-no-cld-evp run and affected by water vapor saturation, and byproduct of the the 10M-BIN-no-cld-evp run are repeated by adopting formation, which is a starting point of effects of formation saturation adjustment (collection scheme) in BULK, and on clouds, is cloud particle number concentration such as these sensitivity simulations are named the control-BIN-sat cloud droplet number concentration (CDNC). -e theory run and the 10M-BIN-sat run (the control-BIN-col run and also indicates that condensation and deposition, which are a the 10M-BIN-col run). To see effects of sedimentation on the function of water vapor saturation, and autoconversion and simulation of updrafts and aerosol effects on them, the accretion between cloud particles govern the growth of cloud control-BIN-col run and the 10M-BIN-col run are repeated particles. As a way of identifying “key cloud processes” with the sedimentation scheme in BULK, and these sensi- which create the discrepancy in the simulations of updrafts tivity simulations are named the control-BIN-sed run and and aerosol effects on them between BULK and BIN, we the 10M-BIN-sed run. primarily take into account those latent-heat processes, Some of the simulations that are described above are loading of hydrometeors, and microphysical processes. performed with multiple microphysical processes which are To see effects of interactions between solid particles and modified together. For example, in the control-BIN-noice- liquid particles on the simulation of updrafts and aerosol cdnc run, the 10M-BIN-noice-cdnc run, the control-BULK- effects on them, the standard simulations are repeated with noice-cdnc run, and the 10M-BULK-noice-cdnc run, both ice processes turned off. -ese sensitivity runs are named the ice processes and CDNC are modified. -is disables us from control-BULK-noice run, the 10M-BULK-noice run, the the perfect isolation of effects of ice processes from those of control-BIN-noice run, and the 10M-BIN-noice run. To see CDNC, or vice versa. Motivated by this, for better isolation effects of CDNC, these sensitivity simulations are repeated of effects of individual microphysical processes, the standard with CDNC fixed at one value over the domain and the simulations are repeated by modifying a process of interest 6 Advances in Meteorology this study is given. For the sake of brevity of Table 1 and only. -ese repeated simulations are named by including “only” in their name. based on the fact that simulations whose name include “only” and “2 mt” are a simple extension of the basic sim- For the isolation of effects of CDNC, the standard simulations are repeated by fixing CDNC, following the ulations, these simulations are not included in Table 1. -e method in the “noice-cdnc” runs, yet with ice processes that description of the simulations in this section and Table 1 is are turned on. -ese repeated simulations are the control- supposed to give their brief outline, and their details are BIN-cdnc-only run, the 10M-BIN-cdnc-only run, the given below in Section 4. control-BULK-cdnc-only run and the 10M-BULK-cdnc- only run. In addition to the “noice-cdnc” runs, it is nota- 4. Results ble that the above-described simulations to test each of effects of rain and cloud-liquid evaporative cooling, satu- In figures below that depict results from the simulations, the ration, collection, and sedimentation processes involve other simulations with prefixes “control-BULK,” “10M-BULK,” processes which are modified together. For better isolation “control-BIN,” and “10M-BIN” in their names are repre- of each of these processes, the standard simulations are sented by yellow, blue, black, and red lines, respectively. In repeated only by turning off rain evaporative cooling, fol- case, there are two or more simulations whose name is with lowing the same method as in the “no-rain-evp” runs, and an identical prefix in a figure, and these simulations use then they are repeated again only by turning off cloud-liquid different line types (i.e., solid, dashed, and dotted lines) with evaporative cooling, following the same method as in the an identical line color. -e updraft mass fluxes, which are “no-cld-evp” runs. -ese repeated simulations with rain described below, are obtained simply by multiplying the evaporative cooling off are named the control-BIN-no-rain- updraft speed with air density. For all the simulations, the evp-only run, the 10M-BIN-no-rain-evp-only run, the updraft speed is predicted. Air density varies negligibly as control-BULK-no-rain-evp-only run, and the 10M-BULK- compared to the variation of updraft speed at each altitude no-rain-evp-only run. -ese repeated simulations with among the simulations; hence, differences in updraft mass cloud-liquid evaporative cooling off are named the control- fluxes are mostly caused by differences in updraft speed, and BIN-no-cld-evp-only run, the 10M-BIN-no-cld-evp-only contributions by differences in air density to those in updraft run, the control-BULK-no-cld-evp-only run, and the mass fluxes are negligible at each altitude among the sim- 10M-BULK-no-cld-evp-only run. For better isolation of ulations. -is indicates that conclusions drawn based on roles by the saturation process, the control-BIN run and the updraft mass fluxes below are not qualitatively different 10M-BIN run are repeated by adopting saturation adjust- from those based on updraft speed. ment in BULK as in “sat” runs. -ese simulations are the control-BIN-sat-only run and the 10M-BIN-sat-only run. For better isolation of roles by the collection process, the 4.1. Evaluation of the Control-BIN Run and the Control-BULK control-BIN run and the 10M-BIN run are repeated by Run. To evaluate the control-BIN run and control-BULK adopting the collection scheme in BULK as in “col” runs. run, cloud and precipitation variables that are simulated by -ese simulations are the control-BIN-col-only run and the the runs are compared to observed counterparts. -e cloud 10M-BIN-col-only run. Finally, for better isolation of roles fraction, cloud-top height, the liquid-water path (LWP), the by the sedimentation process, the control-BIN run and the ice-water path (IWP), and cumulative precipitation are 10M-BIN run are repeated by adopting the sedimentation selected to be those variables. -is is based on the fact that scheme in BULK as in “sed” runs. -ese simulations are the the selected variables are well known to be representative control-BIN-sed-only run and the 10M-BIN-sed-only run. variables that are able to give us information on the overall It should be remembered that, in BULK, among pre- structure of a system of interest [9, 12, 14]. Hence, by cipitable hydrometeors, snow, and graupel adopt the one- selecting the variables, we are able to evaluate how the moment prediction, while rain adopts the two-moment overall simulation of a system of interest is performed. prediction. As indicated by Wacker and Seifert [41], Mil- -e cloud fractions are 0.45 (0.48) for clouds below 5 km brandt and Yau [42], and Milbrandt and McTaggart-Cowan in altitude, 0.55 (0.49) for clouds between 5 and 10 km in [43], whether the one-moment or the two-moment pre- altitude, and 0.85 (0.78) for clouds between 10 and 15 km in diction is used for precipitable hydrometeors affects how the altitude in the control-BIN (control-BULK) run. -e observed mass of precipitable hydrometeors is distributed in the fractions are 0.49 for clouds below 5 km in altitude, 0.51 for vertical domain. -is can have impacts on results here by clouds between 5 and 10 km in altitude, and 0.82 for clouds altering microphysical factors such as the vertical distri- between 10 and 15 km in altitude. -e simulated fractions butions of loading and latent-heat processes. Motivated by deviate from observation by less than around 10%. -e cloud- this, the standard simulations with BULK are repeated by top height, averaged over the simulation period, is 8.1 km for replacing the one-moment prediction with the two-moment the control-BIN run and 7.4 km for the control-BULK run, prediction for snow and graupel. -ese sensitivity runs are and those simulated heights show around 3–5% discrepancy named the control-BULK-2 mt run and the 10M-BULK- against an observed height that is 7.8 km. -e LWP, averaged −2 2 mt runs. Also, the other BULK simulations are repeated over the domain and the simulation period, is 920 (734) g·m , −2 with the two-moment prediction, and these simulations are while the averaged IWP is 85 (70) g·m for the control-BIN named by including “2 mt” in their name. In Table 1, the (control-BULK) run. -e observed LWP and IWP are 819 and −2 description of basic standard and repeated simulations in 77 g·m , respectively, and thus, the differences in LWP and Advances in Meteorology 7 Table 1: Summary of simulations. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Use of the mean Use of constant Control- Saturation terminal velocity BULK 100 Present Predicted Present Present Present Present Present collection BULK adjustment and the flux efficiencies approach Use of the mean Use of constant Saturation terminal velocity 10M-BULK BULK 1000 Present Predicted Present Present Present Present Present collection adjustment and the flux efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Present Predicted Present Present Present Present Present hydrometeor BIN prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Supersaturation of collection 10M-BIN BIN 1000 Present Predicted Present Present Present Present Present hydrometeor prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Control- Use of constant Saturation terminal velocity BULK- BULK 100 Absent Predicted Absent Absent Absent Present Present collection adjustment and the flux noice efficiencies approach Use of the mean 10M- Use of constant Saturation terminal velocity BULK- BULK 1000 Absent Predicted Absent Absent Absent Present Present collection adjustment and the flux noice efficiencies approach 8 Advances in Meteorology Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Absent Predicted Absent Absent Absent Present Present hydrometeor BIN-noice prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Supersaturation of collection BIN 1000 Absent Predicted Absent Absent Absent Present Present hydrometeor noice prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Control- Use of constant Fixed at Saturation terminal velocity BULK- BULK 100 Absent Absent Absent Absent Present Present collection 55 adjustment and the flux noice-cdnc efficiencies approach Use of the mean 10M- Use of constant Fixed at Saturation terminal velocity BULK- BULK 1000 Absent Absent Absent Absent Present Present collection 451 adjustment and the flux noice-cdnc efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence Control- velocity on the Fixed at Supersaturation of collection BIN-noice- BIN 100 Absent Absent Absent Absent Present Present hydrometeor 55 prediction efficiencies on cdnc size and the use the hydrometeor of a semi- size Lagrangian method Advances in Meteorology 9 Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Fixed at Supersaturation of collection BIN 1000 Absent Absent Absent Absent Present Present hydrometeor noice-cdnc 451 prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Present Predicted Absent Present Present Present Present hydrometeor BIN-g prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Supersaturation of collection 10M-BIN-g BIN 1000 Present Predicted Absent Present Present Present Present hydrometeor prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Supersaturation of collection BIN 100 Present Predicted Present Absent Present Present Present hydrometeor BIN-s prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method 10 Advances in Meteorology Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the Supersaturation of collection 10M-BIN-s BIN 1000 Present Predicted Present Absent Present Present Present hydrometeor prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Use of constant Control- Saturation terminal velocity BULK 100 Present Predicted Absent Present Present Present Present collection BULK-g adjustment and the flux efficiencies approach Use of the mean Use of constant 10M- Saturation terminal velocity BULK 1000 Present Predicted Absent Present Present Present Present collection BULK-g adjustment and the flux efficiencies approach Use of the mean Use of constant Control- Saturation terminal velocity BULK 100 Present Predicted Present Absent Present Present Present collection BULK-s adjustment and the flux efficiencies approach Use of the mean Use of constant 10M- Saturation terminal velocity BULK 1000 Present Predicted Present Absent Present Present Present collection BULK-s adjustment and the flux efficiencies approach Use of the mean Control- Use of constant Saturation terminal velocity BULK-no- BULK 100 Present Predicted Present Present Absent Present Present collection adjustment and the flux ice-lt efficiencies approach Use of the mean 10M- Use of constant Saturation terminal velocity BULK-no- BULK 1000 Present Predicted Present Present Absent Present Present collection adjustment and the flux ice-lt efficiencies approach Use of the mean Control- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 100 Absent Absent Absent Absent Absent Present collection 55 adjustment and the flux rain-evp efficiencies approach Advances in Meteorology 11 Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Use of the mean 10M- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 1000 Absent Absent Absent Absent Absent Present collection 451 adjustment and the flux rain-evp efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence Control- velocity on the Fixed at Supersaturation of collection BIN-no- BIN 100 Absent Absent Absent Absent Absent Present hydrometeor efficiencies on 55 prediction rain-evp size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence 10M-BIN- velocity on the Fixed at Supersaturation of collection no-rain- BIN 1000 Absent Absent Absent Absent Absent Present hydrometeor 451 prediction efficiencies on evp size and the use the hydrometeor of a semi- size Lagrangian method Use of the mean Control- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 100 Absent Absent Absent Absent Absent Absent collection 55 adjustment and the flux cld-evp efficiencies approach Use of the mean 10M- Use of constant Fixed at Saturation terminal velocity BULK-no- BULK 1000 Absent Absent Absent Absent Absent Absent collection 451 adjustment and the flux cld-evp efficiencies approach Consideration of the dependence Consideration of of the terminal the dependence Control- velocity on the Fixed at Supersaturation of collection BIN-no- BIN 100 Absent Absent Absent Absent Absent Absent hydrometeor 55 prediction efficiencies on cld-evp size and the use the hydrometeor of a semi- size Lagrangian method 12 Advances in Meteorology Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Fixed at Supersaturation of collection BIN 1000 Absent Absent Absent Absent Absent Absent hydrometeor no-cld-evp 451 prediction efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the Control- Fixed at Saturation of collection hydrometeor BIN 100 Absent Absent Absent Absent Absent Absent BIN-sat 55 adjustment efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence Consideration of of the terminal the dependence velocity on the 10M-BIN- Fixed at Saturation of collection BIN 1000 Absent Absent Absent Absent Absent Absent hydrometeor sat 451 adjustment efficiencies on size and the use the hydrometeor of a semi- size Lagrangian method Consideration of the dependence of the terminal Use of constant velocity on the Control- Fixed at Supersaturation BIN 100 Absent Absent Absent Absent Absent Absent collection hydrometeor BIN-col 55 prediction efficiencies size and the use of a semi- Lagrangian method Advances in Meteorology 13 Table 1: Continued. Aerosol Latent Cloud- concentration in Rain Ice CDNC Graupel Snow heating liquid Saturation Collection Sedimentation Simulations Microphysics accumulation evaporative −3 physics (cm ) loading loading involving ice evaporative process process process mode over the cooling hydrometeors cooling −3 PBL (cm ) Consideration of the dependence of the terminal Use of constant velocity on the 10M-BIN- Fixed at Supersaturation BIN 1000 Absent Absent Absent Absent Absent Absent collection hydrometeor col 451 prediction efficiencies size and the use of a semi- Lagrangian method Use of the mean Use of constant Control- Fixed at Supersaturation terminal velocity BIN 100 Absent Absent Absent Absent Absent Absent collection BIN-sed 55 prediction and the flux efficiencies approach Use of the mean Use of constant 10M-BIN- Fixed at Supersaturation terminal velocity BIN 1000 Absent Absent Absent Absent Absent Absent collection sed 451 prediction and the flux efficiencies approach 14 Advances in Meteorology IWP between the control-BIN (control-BULK) run and ob- servation are around 12 (10)% and 10 (9)%. -e cumulative precipitation, averaged over the horizontal domain at the last time step, in the control-BIN run (the control-BULK run) is 97.3 (98.5) mm, which is around 3 (4)% greater than that for observation that is 94.7 mm. -ese comparisons provide a fairly good confidence that the simulation of the overall system structure is performed reasonably well. -ey also show that the averaged fields vary insignificantly from the control-BIN run to the control-BULK. 4.2. Standard Runs with Complete Physics. -e control- BULK run, the 10M-BULK run, the control-BIN run, and the 10M-BIN run, as the standard runs, using standard, “complete” physics are compared in Figure 4. -e profiles of updraft mass fluxes vary significantly between simulations with BIN and those with BULK despite the above shown small variation in the averaged fields of cloud fraction, top height, LWP, IWP, and precipitation from the control-BIN run to the control-BULK run. 0 0.1 0.2 0.3 0.4 –2 –1 Profiles of updraft mass fluxes in the control-BULK run Updraft mass f lux (kg·m ·s ) show rapid increases up to 2.8 km and peak at 2.8 km, which Control-BULK Control-BIN are followed by rapid decreases in the fluxes above 2.8 km. 10M-BULK 10M-BIN -e similar rapid increases and decreases are shown in the Figure 4: Vertical distributions of the time- and domain-averaged 10M-BULK run (Figure 4). However, the control-BIN run updraft mass fluxes for the standard runs (e.g., the control-BULK and the 10M-BIN run show less rapid increases in the fluxes run, the 10M-BULK run, the control-BIN run, and the 10M-BIN to the peak at 3.9 km and less rapid decreases after the peak, run). as compared to the simulations with BULK (Figure 4). -e magnitude or the value of the peak is from 0.28 to −2 −1 −2 −1 0.35 kg·m ·s with its mean value of 0.32 kg·m ·s in the 4.3. Ice Processes. Rosenfeld et al. [11] have shown that the −2 −1 simulations with BIN, while it is from 0.25 to 0.27 kg·m ·s suppressed conversion of cloud liquid to rain, which is −2 −1 with its mean value of 0.26 kg·m ·s in the simulations caused by increasing aerosol concentration, induces in- with BULK. Hence, the altitude of the peak is 39% higher, creases in cloud liquid and its transportation to places where and the mean peak value is 23% higher in the standard BIN freezing occurs. -is enhances freezing, associated latent runs than in the standard BULK runs (Figure 4). heat and buoyancy, and invigorates updrafts and convection. Another point to make is that the control-BIN run and In this invigoration hypothesis, aerosol-induced changes in the 10M-BIN run exhibit an increase in updraft mass fluxes freezing and buoyancy are a main source of the invigoration- as aerosol concentration increases. Associated with this, the related changes in updrafts with increasing aerosol con- −2 −1 peak value increases by 20% from 0.28 to 0.35 kg·m ·s centration. Hence, the different ice processes (involving with increasing aerosol concentration between the control- freezing) may be the main cause of the different responses of BIN run and the 10M-BIN run. However, the control-BULK updraft mass fluxes to increasing aerosol concentration run and the 10M-BULK run exhibit slight decreases in the between the simulations with BULK and those with BIN. flux with increasing aerosol concentration (Figure 4). As- Hence, to isolate the effect of ice processes on the different sociated with this, the peak value decreases by 7% from 0.27 responses among the four standard simulations (i.e., the −2 −1 to 0.25 kg·m ·s with increasing aerosol concentration control-BULK run, the 10M-BULK run, the control-BIN between the control-BULK run and the 10M-BULK run. In run, and the 10M-BIN run), the four standard simulations other words, simulations with BIN show aerosol-induced are repeated with ice processes turned off completely. In invigoration of convection, while simulations with BULK these sensitivity runs, which are the control-BULK-noice show aerosol-induced suppression of convection to the run, the 10M-BULK-noice run, the control-BIN-noice run, contrary. Two frequently used microphysical schemes ex- and the 10M-BIN-noice run, precipitation is formed entirely hibit different responses to a large aerosol perturbation. To by warm rain processes (collision and collection of cloud fulfill the aim of this study, instead of trying to understand liquid by rain and autoconversion of cloud liquid to rain). In which microphysics scheme performs better, we focus on the BIN, drops whose size is smaller than 80 μm in diameter are identification of key cloud processes that create the dis- classified to be droplets (or cloud liquid), while drops whose crepancy among the simulations. In each of the following size is greater than 80 µm in diameter are classified to be rain figures from Figure 5 to Figure 12 which show the profiles of drops (or rain). Here, autoconversion is a process where updraft mass fluxes, fluxes in the standard runs are also droplets collide with and collect each other to form rain. -e shown as a reference. control-BIN-noice run, the 10M-BIN-noice run, the Height (km) Advances in Meteorology 15 control-BULK-noice run, and the 10M-BULK-noice run BULK runs as a process of removing the differences in the show that the differences in the pattern of the vertical CDNC distributions between the control-BIN-noice run and the control-BULK-noice run or between the 10M-BIN-noice variation of updraft mass fluxes (as shown between the standard runs in Figures 4 and 5(a)) nearly disappear run and the 10M-BULK-noice run. For the control-BIN- (Figures 4 and 5(a)). In this paper, the pattern of the vertical noice run and control-BULK-noice run with the CDNC −3 variation of updraft mass fluxes means the altitude of the fixed, CDNC is fixed at 55 cm , while for the 10M-BIN- updraft-mass-flux peak, the peak value, and the rate of noice run and 10M-BULK-noice run with the CDNC fixed, −3 changes in updraft mass fluxes with altitudes around the CDNC is fixed at 451 cm . Here, it is seen that about peak. -e altitude of the peak is 4.3 km in the “noice” runs, 40–50% of aerosol particles in the accumulation mode are which is 54% higher than that in the control-BULK run and activated in the “noice” runs. -is activation ratio is also the 10M-BULK run and 10% higher than that in the control- applicable to the standard runs whose results are depicted in BIN run and the 10M-BIN run. -e peak value is similar Figure 4. CDNC is averaged over time and places with non- between the “noice” runs since it varies slightly from 0.26 to zero CDNC for each of the runs with ice processes turned −2 −1 −2 −1 0.28 kg·m ·s with the mean peak value of 0.27 kg·m ·s off. -en, two averaged CDNCs in the control-BIN-noice between the runs. -is mean peak value is 4 (16)% higher (10M-BIN-noice) run and the control-BULK-noice (10M- BULK-noice) run are summed and divided by two to obtain (lower) than that in the standard simulations with BULK (BIN). the CDNC value that is input to the control-BIN-noice run -ese sensitivity simulations (as compared to the and the control-BULK-noice run with CDNC fixed (the standard runs in Figures 4 and 5(a)) also show that the fact 10M-BIN-noice run and the 10M-BULK-noice run with that simulations with BIN only show aerosol-induced in- CDNC fixed). In each of these sensitivity runs with CDNC vigoration of convection is robust to whether ice processes fixed, which are the control-BIN-noice-cdnc run, the 10M- are turned off or not although the control-BIN-noice run BIN-noice-cdnc run, the control-BULK-noice-cdnc run, and the 10M-BIN-noice run show much less aerosol- and the 10M-BULK-noice-cdnc run, the obtained CDNC induced increases in updraft mass fluxes as compared to value replaces a predicted CDNC value at each grid point those in the control-BIN run and in the 10M-BIN run with none-zero predicted CDNC value at each time step. (Figures 4 and 5(a)). -ese increases are 4% from 0.27 to Comparisons among the simulations with CDNC fixed −2 −1 0.28 kg·m and ice processes off show that the differences in the pattern ·s , which is smaller than 20% in the control- BIN run and the 10M-BIN run. -is demonstrates that of the vertical variation of updraft mass fluxes reduce different ice processes are responsible for the different substantially, as shown in Figure 5(b) in comparisons with shapes of the updraft-mass-flux profile but not for the ab- those differences between the standard simulations in Fig- sence of aerosol-induced invigoration with BULK and the ures 4 and 5(b). -is is similar to the situation among the presence of the invigoration with BIN. control-BIN-noice run, the 10M-BIN-noice run, the control-BULK-noice run, and the 10M-BULK-noice run, as seen in comparisons between Figures 4, 5(a), and 5(b). -e 4.4. CDNC. In addition, it is very likely that there are the altitude of the peak of the updraft-mass-flux vertical profile different spatiotemporal distributions of CDNCs for an is similar and at 3.7 km in the simulations with CDNC fixed identical background aerosol condition between the control- and ice processes off, which is 5% lower than that in the BIN-noice run and the control-BULK-noice run or between control-BIN run and the 10M-BIN run, 32% higher than the 10M-BIN-noice run and the 10M-BULK-noice run that in the control-BULK run and the 10M-BULK run, and whose results are depicted in Figure 5(a). With the droplet 14% lower than that in the “noice” runs. However, as seen in nucleation, droplets are formed, and CDNC, one of the comparisons between Figures 4 and 5(b), there are still droplet properties, affects subsequent cloud microphysical significant differences in the magnitude of updraft mass and dynamic processes. Since aerosol properties determine fluxes among the simulations with CDNC fixed and ice CDNC during the nucleation, it is generally considered that processes off as in the standard runs. Associated with this, −2 −1 CDNC acts as a proxy for aerosol in subsequent cloud the peak value increases by 6% from 0.32 kg·m ·s in the −2 −1 processes after the nucleation. Hence, if we want to apply an control-BULK-noice-cdnc run to 0.34 kg·m ·s in the identical aerosol condition to cloud processes (i.e., both 10M-BULK-noice-cdnc run, while it increases by 6% from −2 −1 nucleation and subsequent processes after it) in a rigorous 0.36 kg·m ·s in the control-BIN-noice-cdnc run to −2 −1 manner among different simulations, it is better that not 0.38 kg·m ·s in the 10M-BIN-noice-cdnc run. -e mean −2 −1 only aerosol condition (before nucleation) but also CDNC peak value is 0.33 kg·m ·s between the control-BULK- distributions are identical between those simulations. noice-cdnc run and the 10M-BULK-noice-cdnc run, while it −2 −1 To make sure that the pair of the control-BIN-noice run is 0.37 kg·m ·s between the control-BIN-noice-cdnc run and the control-BULK-noice run or the pair of the 10M- and the 10M-BIN-noice-cdnc run. Hence, when it comes to BIN-noice run and the 10M-BULK-noice run is in an the mean peak value, the “BIN-noice-cdnc” runs show a 12% identical aerosol condition for all of cloud processes in a higher value than the “BULK-noice-cdnc” runs. Of interest rigorous way, the four sensitivity runs with ice processes is that, in “noice-cdnc” runs, both BULK and BIN show the turned off are repeated. In these runs, in addition to ice enhancement of updraft mass fluxes as aerosol concentra- processes turned off, CDNC is fixed at one value for each of tion increases contrary to the situation in the standard aerosol conditions (before nucleation) for the BIN and simulations (Figures 4 and 5(b)). -is demonstrates that 16 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK-noice Control-BULK Control-BULK-noice-cdnc Control-BULK 10M-BULK-noice 10M-BULK 10M-BULK-noice-cdnc 10M-BULK Control-BIN-noice Control-BIN Control-BIN-noice-cdnc Control-BIN 10M-BIN-noice 10M-BIN 10M-BIN-noice-cdnc 10M-BIN (a) (b) Figure 5: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-noice run, the 10M-BULK-noice run, the control-BIN-noice run, and the 10M-BIN-noice run. (b) Vertical distributions of the time- and domain- averaged updraft mass fluxes for the standard runs, the control-BULK-noice-cdnc run, the 10M-BULK-noice-cdnc run, the control-BIN- noice-cdnc run, and the 10M-BIN-noice-cdnc run. different distributions of CDNC, after nucleation due to runs are the control-BULK run, the 10M-BULK run, the different microphysical schemes, for the identical aerosol control-BIN run, and the 10M-BIN run. Henceforth, the condition before nucleation between the control-BIN-noice freezing level indicates an altitude where freezing starts to run and the control-BULK-noice run and/or between the occur in a rising air parcel, and this altitude is located around 4 km in this study. -e much larger loading or mass of ice 10M-BIN-noice run and the 10M-BULK-noice run are the main cause of the different signs of responses of updraft hydrometeors around 4 km can curb the growth of updraft mass fluxes to increasing aerosol concentration between the mass fluxes more by inducing greater gravity on the mass two different microphysical schemes. -is also demonstrates that tends to pull down a rising air parcel to the ground or that how CDNC is predicted after nucleation for an identical decelerate the parcel more in the standard simulations with aerosol condition before nucleation has a substantial impact BULK than in the standard simulations with BIN. -is can on how updraft mass fluxes respond to increasing aerosol lower the peak value in the standard BULK simulations in concentration. comparison with the standard BIN simulations. -e much larger loading can also “squash” down the vertical profile of updraft mass fluxes around the freezing level in the standard 4.5. Loading of Ice Hydrometeors. -e rapid increases and BULK simulations. Note that the profile around the peak decreases in updraft mass fluxes in the lower atmosphere in between approximately 3 km and approximately 4 km in the the standard simulations with BULK, as shown in Figure 4, standard simulations with BULK in Figure 4 appears to be may be related to loading effects that are exerted by ice pushed (or squashed) down compared to the profile in the hydrometeors. -is is based on the finding that ice processes standard simulations with BIN in Figure 4. -e squashed have an impact on the vertical profile of updraft mass fluxes, profile accompanies the rapid increases and decreases in as discussed in Section 4.3. We can easily envision that there updraft mass fluxes around the peak in the standard BULK are much greater loading effects of solid hydrometeors in the simulations in Figure 4. standard simulations with BULK which are depicted in To understand the rapid increases and decreases in Figure 4 than in the standard simulations with BIN which updraft mass fluxes in the lower atmosphere in the standard are depicted in Figure 4, particularly around the freezing BULK simulations, based on abovementioned conjecture level that is around 4 km. Remember that these four standard which is related to loading effects, the control-BULK run Height (km) Height (km) Advances in Meteorology 17 together with the 10M-BULK run is repeated by turning off To see effects of the loading of snow and graupel for BIN, the loading effect of the graupel mass. -is is based on the the control-BIN run and the 10M-BIN run are repeated by well-known fact that the graupel mass accounts for a sig- removing snow loading and graupel loading, respectively. nificant portion of loading effects particularly in deep clouds. -ese sensitivity runs are the control-BIN-s run, the 10M- In these sensitivity runs, which are the control-BULK-g run BIN-s run, the control-BIN-g run, and the 10M-BIN-g run. and the 10M-BULK-g run, despite the absence of the loading As seen in Figure 6(c), whether snow loading or graupel effect of the graupel mass, graupel particles experience the loading is turned off, both the response of updraft mass dynamic, thermodynamic, and microphysical processes as in fluxes to increasing aerosol concentration and the pattern of the standard runs. Comparisons between the control-BULK the vertical variation of updraft mass fluxes do not change run, the 10M-BULK run, the control-BULK-g run, and the significantly in the simulations with BIN. Associated with 10M-BULK-g run indicate that the vertical shape or pattern of this, the altitude and magnitude of the peak varies less than the updraft-mass-flux profile does not vary much with the 6% from the standard BIN runs to the BIN runs with either presence or absence of the loading effect of graupel mass snow loading removed or graupel loading removed. (Figure 6(a)). -e altitude of the peak value of the profile is 2.8 km in the control-BULK-g run and the 10M-BULK-g run, which is identical to that in the control-BULK run and the 4.6. Latent Heating and Cooling of Ice Hydrometeors. To test −2 −1 roles played by latent heating and cooling related to ice 10M-BULK run. -e peak value is 0.26 and 0.24 kg·m ·s in the control-BULK-g run and the 10M-BULK-g run, re- processes and aerosol effects on them in the shapes of the updraft-mass-flux vertical profile in the control-BULK run spectively, which shows a slightly 4% lower value than that in the control-BULK run and the 10M-BULK run, respectively. and the 10M-BULK run, relative to those played by the loading effect of snow and aerosol influences on it, the -en, the control-BULK run and the 10M-BULK run are repeated with the absence of the snow loading, based on the control-BULK run and the 10M-BULK run are repeated by turning off the effect of latent heating and cooling from fact that snow and graupel accounts for a significant portion of the loading effect. In these sensitivity runs, which are the freezing, melting, deposition, and sublimation. -ese sen- sitivity simulations are the control-BULK-no-ice-lt run and control-BULK-s run and the 10M-BULK-s run, despite the the 10M-BULK-no-ice-lt run. Note that in the control- absence of the loading effect of the snow mass, snow particles experience the dynamic, thermodynamic, and microphysical BULK-noice run and the 10M-BULK-noice run, as depic- ted in Figure 5(a), ice hydrometeors are absent or the mass of processes as in the standard runs. -e control-BULK run, the 10M-BULK run, the control-BULK-s run, and the 10M- ice hydrometeors is zero; thus, both loading and latent heating or cooling related to ice hydrometeors are absent. BULK-s run are compared, and this comparison shows sig- nificant changes in the vertical shape of updraft mass fluxes However, in the control-BULK-no-ice-lt run and the 10M- BULK-no-ice-lt run, the effect of latent heating related to ice due to the presence or the absence of the snow loading in the simulations with BULK, although the qualitative nature of hydrometeors on temperature is only turned off and ice processes are allowed to generate ice hydrometeors. responses of updraft mass fluxes to increases in aerosol -erefore, the loading of ice hydrometeors is present in these concentration does not vary with whether the snow loading is runs. -ey show results whose qualitative nature is similar to considered or not (Figure 6(a)). By removing the snow that in the control-BULK run and the 10M-BULK run when loading in the control-BULK-s run and the 10M-BULK-s run, the altitude and magnitude of the updraft-mass-flux peak and it comes to the shape of the vertical profile of updraft mass fluxes and updraft-mass-flux responses to increasing aerosol the increases and decreases of the fluxes around the peak in these sensitivity runs become similar to those in the control- concentration, as shown in Figure 6(d). Associated with this, the altitude of the updraft-mass-flux peak increase slightly BIN run and the 10M-BIN run (Figure 6(a)). Associated with this, the altitude of the peak value increases by 39% from only by 7 (4)% from 2.8 km in the control-BULK (10M- BULK) run to 3.0 (2.9) km in the control-BULK-no-ice-lt 2.8 km in the control-BULK run and the 10M-BULK run to 3.9 km in the control-BULK-s run and the 10M-BULK-s run, (10M-BULK-no-ice-lt) run. -e peak value also increases −2 −1 slightly only by 4% from 0.27 (0.25) kg·m ·s in the while the peak value increases by 22 (28)% from 0.27 (0.25) −2 −1 −2 −1 kg·m ·s in the control-BULK (10M-BULK) run to 0.33 control-BULK (10M-BULK) run to 0.28 (0.26) kg·m ·s in −2 −1 the control-BULK-no-ice-lt (10M-BULK-no-ice-lt) run. (0.32) kg·m ·s in the control-BULK-s (10M-BULK-s) run. -e vertical distribution of the mass density of snow for Hence, the effect of latent heating and cooling (related to ice processes) on the shapes of the updraft-mass-flux vertical the 10M-BULK run and the 10M-BIN run is shown in Figure 6(b). -ere is much higher mass density of snow in profile in the simulations with BULK is negligible in the 10M-BULK run than in the 10M-BIN run, in particular, comparison with the effect of the snow loading. Of interest is that, as seen in Figure 6(d), there is a slight around the freezing level. -is explains the much larger loading of snow in the standard simulations with BULK than increase in updraft mass flux in the control-BULK-no-ice-lt run, as compared to the control-BULK run, and in the 10M- in the standard simulations with BIN, which lowers the value of the updraft-mass-flux peak and pushes down the updraft- BULK-no-ice-lt run, as compared to the 10M-BULK run. -is is despite ice-process-related latent heating which mass-flux profile around 3 km and around 4 km in the standard simulations with BULK as demonstrated by the enhances buoyancy in updrafts and is turned off in the control-BULK-no-ice-lt run and the 10M-BULK-no-ice-lt sensitivity simulations with the loading of snow turned off in Figure 6(a). run. Increases in ice-process-related latent heating enhance 18 Advances in Meteorology 18 18 10 10 8 8 2 2 0 0.05 0.1 0.15 0.2 0.25 0 0.1 0.2 0.3 0.4 –3 –2 –1 Mass density (g·m ) Updraft mass flux (kg·m ·s ) 10M-BULK Control-BULK Control-BULK-g 10M-BIN 10M-BULK 10M-BULK-g Control-BIN Control-BULK-s 10M-BIN 10M-BULK-s (a) (b) 12 12 10 10 8 8 6 6 4 4 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK Control-BIN-g Control-BULK Control-BULK-no-ice-lt 10M-BULK 10M-BULK-no-ice-lt 10M-BULK 10M-BIN-g Control-BIN Control-BIN Control-BIN-s 10M-BIN 10M-BIN 10M-BIN-s (c) (d) Figure 6: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-g run, the 10M-BULK-g run, the control-BULK-s run, and the 10M-BULK-s run. (b) Vertical distributions of the time- and domain-averaged snow mass density for the 10M-BULK run and the 10M-BIN run. (c) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-g run, the 10M-BIN-g run, the control-BIN-s run, and the 10M-BIN-s run. (d) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-no-ice-lt run, and the 10M-BULK-no-ice-lt run. Height (km) Height (km) Height (km) Height (km) Advances in Meteorology 19 buoyancy and updraft speed. -ese increases in updraft rain evaporation, which are induced by aerosol, and those in speed in turn increase the mass of ice-phase hydrometeors the gust front intensity. Motivated by this, the control-BIN- and thus the loading of ice-phase hydrometeors by en- noice-cdnc run, the 10M-BIN-noice-cdnc run, the control- hancing supersaturation and deposition. -ese increases in BULK-noice-cdnc run, and the 10M-BULK-noice-cdnc run, loading tend to reduce buoyancy and updraft speed. When as depicted in Figure 5(b), are repeated by additionally ice-process-related latent heating is turned off as in the turning off rain evaporative cooling. In these sensitivity runs, control-BULK-no-ice-lt run and the 10M-BULK-no-ice-lt rain evaporation affects the rain mass but does not affect run, not only ice-process-related latent heating is removed temperature. -ese sensitivity simulations are the control- but also the associated increases in the loading of ice-phase BIN-no-rain-evp run, the 10M-BIN-no-rain-evp run, the hydrometeors are reduced. Effects of reduction in the control-BULK-no-rain-evp run, and the 10M-BULK-no- loading outweighs effects of the removal of ice-process- rain-evp run. By turning off rain evaporative cooling, we related latent heating, resulting in a slight increase in the remove a pathway for the aerosol to influence gust fronts updraft speed as in the control-BULK-no-ice-lt and the through aerosol effects on rain evaporative cooling. -e flux profile shapes are now more consistent amongst simulations 10M-BULK-no-ice-lt (Figure 6(d)). In other words, there is competition between effects of reduction in the loading and with the rain evaporative cooling turned off (Figure 7(a)). effects of the removal of ice-process-related latent heating in -e altitude of the updraft-mass-flux peak is 3.6–3.8 km the control-BULK-no-ice-lt and the 10M-BULK-no-ice-lt among the “no-rain-evp” runs, which is similar to 3.9 km in run. -is competition leads to just the slight change in the the control-BIN run and the 10M-BIN run. -e control- updraft mass flux in the control-BULK-no-ice-lt, as com- BIN-no-rain-evp run and the 10M-BIN-no-rain-evp run in pared to the control-BULK run, and in the 10M-BULK-no- Figure 7(a) still show strong aerosol influences on the up- ice-lt run, as compared to the 10M-BULK run (Figure 6(d)). draft mass fluxes in comparison with those in the control- Here, it is notable that snow gains its mass mainly BIN-noice-cdnc run and the 10M-BIN-noice-cdnc run in through other processes such as the riming of liquid hy- Figure 5(b). However, aerosol-related differences are small drometeors onto snow than deposition. -e time- and in the control-BULK-no-rain-evp run and the 10M-BULK- no-rain-evp run in Figure 7(a) in comparison with those in domain-averaged rate of the riming of liquid hydrometeors −2 −2 −1 onto snow is 8.391, 8.402, 8.261, and 8.333 ×10 g·m ·h , the control-BULK-noice-cdnc run and the 10M-BULK- noice-cdnc run in Figure 5(b). Associated with this, the while that of deposition is 1.011, 1.002, 0.582, and −2 −2 −1 0.551 × 10 g·m ·h in the control-BULK run, the 10M- peak value of the updraft-mass-flux profile varies slightly by −2 −1 BULK run, the control-BULK-no-ice-lt run, and the 10M- 2% from 0.41 kg·m ·s in the control-BULK-no-rain-evp −2 −1 BULK-no-ice-lt run, respectively. Here, we see that the run to 0.42 kg·m ·s in the 10M-BULK-no-rain-evp run, −2 −1 riming rate is around one order of magnitude greater than while the value varies by 9% from 0.44 kg·m ·s in the −2 −1 the deposition rate, and the riming rate shows insignificant control-BIN-no-rain-evp run to 0.48 kg·m ·s in the 10M- change around 1% or less changes between the control- BIN-no-rain-evp run. Comparing the simulations in BULK run and the control-BULK-no-ice-lt run or between Figures 5(b) to those in Figure 7(a), it appears that aerosol the 10M-BULK run and the 10M-BULK-no-ice-lt run. Due responses in BULK are controlled to a large extent by rain to this, despite substantial around 40–45% changes in the evaporative cooling and gust front generation; however, deposition rates between the control-BULK run and the those responses in BIN appear to be less sensitive to aerosol control-BULK-no-ice-lt run or between the 10M-BULK run influences on rain evaporation. and the 10M-BULK-no-ice-lt run, the snow loading does not change significantly in the control-BULK-no-ice-lt run, as 4.8. Cooling from Cloud-Liquid Evaporation. Recent studies compared to the control-BULK run, and in the 10M-BULK- no-ice-lt run, as compared to the 10M-BULK run. -e snow have shown that not only rain evaporative cooling but also cloud-liquid evaporative cooling can affect the intensity of loading, which is defined to be the time- and domain- averaged snow mass density, is 0.147, 0.152, 0.139, and gust fronts and aerosol effects on it. Hence, we hypothesize −3 that different treatments in the cloud-liquid evaporation 0.144 g·m in the control-BULK run, the 10M-BULK run, the control-BULK-no-ice-lt run, and the 10M-BULK-no- may explain some of the remaining differences in Figure 7(a). Based on this hypothesis, we repeat the control- ice-lt run, respectively. -is leads to the negligible changes in the shapes of the updraft-mass-flux vertical profile in the BIN-no-rain-evp run, the 10M-BIN-no-rain-evp run, the control-BULK-no-rain-evp run, and the 10M-BULK-no- control-BULK-no-ice-lt run, as compared to the control- BULK run, and in the 10M-BULK-no-ice-lt run, as com- rain-evp run in Figure 7(a) by additionally turning off pared to the 10M-BULK run (Figure 6(d)). cloud-liquid evaporative cooling. In these sensitivity runs, which are the control-BIN-no-cld-evp run, the 10M-BIN- no-cld-evp run, the control-BULK-no-cld-evp run, and the 4.7. Cooling from Rain Evaporation. It has been known that 10M-BULK-no-cld-evp run, cloud-liquid evaporation af- changes in rain evaporation, which are induced by aerosol, fects the cloud-liquid mass, but temperature is not altered by can cause those in the intensity of gust fronts and subsequent cloud-liquid evaporation. -e control-BIN-no-cld-evp run updrafts (e.g., [6, 15, 16]). Hence, the differences in updraft and the 10M-BIN-no-cld-evp run in Figure 7(b) show that mass fluxes in Figure 5(b) despite the fixed CDNC and the updraft mass fluxes are now much smaller and exhibit little removed ice processes may have been caused by changes in aerosol influences as compared to the control-BIN-no-rain- 20 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 2 2 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK-no-rain-evp Control-BULK Control-BULK-no-cld-evp Control-BULK 10M-BULK-no-rain-evp 10M-BULK 10M-BULK-no-cld-evp 10M-BULK Control-BIN-no-rain-evp Control-BIN Control-BIN-no-cld-evp Control-BIN 10M-BIN-no-rain-evp 10M-BIN 10M-BIN-no-cld-evp 10M-BIN (a) (b) Figure 7: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-rain- evp run, the 10M-BIN-no-rain-evp run, the control-BULK-no-rain-evp run, and the 10M-BULK-no-rain-evp run. (b) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-cld-evp run, the 10M-BIN-no-cld-evp run, the control-BULK-no-cld-evp run, and the 10M-BULK-no-cld-evp run. evp run and the 10M-BIN-no-rain-evp run in Figure 7(a), smaller in the control-BULK-no-cld-evp run as compared to particularly at altitudes below the tropopause where clouds the control-BULK-no-rain-evp run, and it is 40% smaller in form. -e tropopause is located around 12 km. Associated the 10M-BULK-no-cld-evp run as compared to the 10M- with this, below the tropopause, the peak value of the updraft- BULK-no-rain-evp run. −2 −1 mass-flux profile varies slightly by 2% from 0.20 kg·m ·s in While mass flux profile shapes are similar between the −2 −1 the 10M-BIN-no-cld-evp run to 0.21 kg·m ·s in the sensitivity simulations, as seen in Figure 7(b), there are still control-BIN-no-cld-evp run. -e altitude of the peak is significant differences in the magnitudes between the pair of 1.6 km, which is identical between the 10M-BIN-no-cld-evp the control-BIN-no-cld-evp run and the 10M-BIN-no-cld- run and the control-BIN-no-cld-evp run. -e peak value is evp run and that of the control-BULK-no-cld-evp run and 52% smaller in the control-BIN-no-cld-evp run as compared the 10M-BULK-no-cld-evp run below the tropopause (order to the control-BIN-no-rain-evp run, and it is 58% smaller in 30%). Overall, it can be said that both rain evaporative the 10M-BIN-no-cld-evp run as compared to the 10M-BIN- cooling and cloud-liquid evaporative cooling have strong no-rain-evp run. -e mass fluxes in the control-BULK-no- leverage on the mass flux profiles and the aerosol influence thereon. cld-evp run and the 10M-BULK-no-cld-evp run in Figure 7(b) also decrease in magnitude as compared to the control-BULK-no-rain-evp run and the 10M-BULK-no-rain- evp run in Figure 7(a), although to a lesser extent, particularly 4.9. Saturation. We hypothesize that the treatment of sat- at altitudes below the tropopause. Aerosol-related differences uration might explain remaining differences in Figure 7(b). are also small between the control-BULK-no-cld-evp run and To check this hypothesis, the control-BIN-no-cld-evp run the 10M-BULK-no-cld-evp run below the tropopause and the 10M-BIN-no-cld-evp run in Figure 7(b) are repeated (Figure 7(b)). Related to this, below the tropopause, the peak using the saturation adjustment treatment in BULK. -ese −2 −1 value varies slightly by 2% from 0.24 kg·m ·s in the control- sensitivity simulations are the control-BIN-sat run and the −2 −1 BULK-no-cld-evp run to 0.25 kg·m ·s in the 10M-BULK- 10M-BIN-sat run, and results from these sensitivity simu- no-cld-evp run. -e altitude of the peak is 1.7– 1.8 km, which lations are presented in Figure 8. Differences in the mag- nitude of the updraft mass fluxes between the pair of the is very similar between the control-BULK-no-cld-evp run and the 10M-BULK-no-cld-evp run. -e peak value is 41% control-BIN-sat run and the 10M-BIN-sat run and that of Height (km) Height (km) Advances in Meteorology 21 among the simulations in Figure 7(b). Based on this hy- pothesis, we repeat the simulations with BIN (i.e., the control-BIN-no-cld-evp run and the 10M-BIN-no-cld-evp run) in Figure 7(b) by using the same autoconversion and accretion schemes as in the simulations with BULK (i.e., the control-BULK-no-cld-evp run and the 10M-BULK-no-cld- evp run). -ese sensitivity simulations are the control-BIN- col run and the 10M-BIN-col run. With the identical autoconversion and accretion schemes between the pair of the control-BIN-col run and the 10M-BIN-col run and the pair of the control-BULK-no-cld-evp run and the 10M- BULK-no-cld-evp run, as seen in Figure 9, differences in the updraft-mass-flux profiles between these two pairs of simulations are now smaller as compared to the differences between the pair of the control-BULK-no-cld-evp run and the 10M-BULK-no-cld-evp run and that of the control-BIN- no-cld-evp run and the 10M-BIN-no-cld-evp run below the tropopause; note that the control-BIN-no-cld-evp run and the 10M-BIN-no-cld-evp run in Figure 7(b) are shown with dashed lines in Figure 9 and in Figure 9, and the control- BULK-no-cld-evp run and the con-BULK-no-cld-evp run in 0 0.1 0.2 0.3 0.4 –2 –1 Figure 7(b) are shown with the same lines as in Figure 7(b). Updraft mass flux (kg·m ·s ) Regarding the differences which get smaller, the peak value Control-BULK-no-cld-evp Control-BULK of the updrafts mass fluxes increases by 10% from 10M-BULK 10M-BULK-no-cld-evp −2 −1 0.21 kg·m ·s in the control-BIN-no-cld-evp run to Control-BIN-no-cld-evp Control-BIN −2 −1 0.23 kg·m ·s in the control-BIN-col run, while it increases 10M-BIN-no-cld-evp 10M-BIN −2 −1 by 10% from 0.20 kg·m ·s in the 10M-BIN-no-cld evp run Control-BIN-sat 10M-BIN-sat −2 −1 to 0.22 kg·m ·s in the 10M-BIN-col run although the Figure 8: Vertical distributions of the time- and domain-averaged altitude of the peak value does not change among these runs. updraft mass fluxes for the simulations in Figure 7(b), the control- -is results in around 10% differences between the pair of BIN-sat run, and the 10M-BIN-sat run. the control-BIN-col run and the 10M-BIN-col run and the pair of the control-BULK-no-cld-evp run and the 10M- BULK-no-cld-evp run, which are smaller than around the control-BULK-no-cld-evp run and the 10M-BULK-no- cld-evp run in Figure 8 are now slightly larger than those 30% differences between the pair of the control-BIN-no-cld- evp run and the 10M-BIN-no-cld-evp run and the pair of the between the pair of the control-BIN-no-cld-evp run and the 10M-BIN-no-cld-evp run and the pair of the control-BULK- control-BULK-no-cld-evp run and the 10M-BULK-no-cld- evp run. However, in Figure 9, there are still remaining no-cld-evp run and the 10M-BULK-no-cld-evp run below the tropopause; note that the control-BIN-no-cld-evp run differences in the fluxes among the simulations. Both and the 10M-BIN-no-cld-evp run in Figure 7(b) are shown autoconversion and accretion treatments seem to be of importance but are insufficient in explaining all differences with dashed lines in Figure 8 and in Figure 8, and the control-BULK-no-cld-evp run and the con-BULK-no-cld- in Figure 7(b). evp run in Figure 7(b) are shown with the same lines as in Figure 7(b). Regarding the differences which get larger, the 4.11. Sedimentation. We again hypothesize that one im- peak value of the updrafts mass fluxes reduces from −2 −1 portant remaining process—namely, sedimentation—might 0.21 kg·m ·s in the control-BIN-no-cld-evp run to −2 −1 explain the remaining differences in Figure 7(b). Based on 0.19 kg·m ·s in the control-BIN-sat run, while it reduces −2 −1 this hypothesis, the control-BIN-col run and the 10M-BIN- from 0.20 kg·m ·s in the 10M-BIN-no-cld evp run to −2 −1 col run in Figure 9 are repeated but with the version of 0.18 kg·m ·s in the 10M-BIN-sat run although the altitude sedimentation in BULK. -ese sensitivity simulations are of the peak value does not change among these runs. Here, the control-BIN-sed run and the 10M-BIN-sed run. As we see that the different treatment of saturation does not shown in Figure 10, differences, which are around 1–3%, help figure out the cause of the discrepancy between the BIN between the pair of the control-BIN-sed run and the 10M- simulations and the BULK simulations, as shown in BIN-sed run and the pair of the control-BULK-no-cld-evp Figure 7(b). run and the 10M-BULK-no-cld-evp run are now very small as compared to differences, which are around 30%, between the pair of the control-BIN-no-cld-evp run and the 10M- 4.10. Autoconversion and Accretion. We hypothesize that differences in the treatment of autoconversion and accretion BIN-no-cld-evp run and the pair of the control-BULK-no- cld-evp run and the 10M-BULK-no-cld-evp run below the of cloud ice and cloud liquid by precipitable hydrometeors may play a role in the differences in the updraft mass fluxes tropopause in Figure 7(b); note that the control-BIN-no-cld- Height (km) 22 Advances in Meteorology 16 16 14 14 8 8 6 6 4 4 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK-no-cld-evp Control-BULK Control-BULK-no-cld-evp Control-BULK 10M-BULK-no-cld-evp 10M-BULK 10M-BULK-no-cld-evp 10M-BULK Control-BIN-no-cld-evp Control-BIN Control-BIN-no-cld-evp Control-BIN 10M-BIN-no-cld-evp 10M-BIN 10M-BIN-no-cld-evp 10M-BIN Control-BIN-sed 10M-BIN-sed Control-BIN-col 10M-BIN-col Figure 10: Vertical distributions of the time- and domain-averaged Figure 9: Vertical distributions of the time- and domain-averaged updraft mass fluxes for the simulations in Figure 7(b), the control- updraft mass fluxes for the simulations in Figure 7(b), the control- BIN-sed run, and the 10M-BIN-sed run. BIN-col run, and the 10M-BIN-col run. the 10M-BULK-cdnc-only run in Figure 11(a), both BIN and evp run and the 10M-BIN-no-cld-evp run in Figure 7(b) are shown with dashed lines in Figure 10 and in Figure 10, and BULK show aerosol-induced enhancement of updraft mass fluxes as shown in “noice-cdnc runs.” Associated with this, the control-BULK-no-cld-evp run and the con-BULK-no- cld-evp run in Figure 7(b) are shown with the same lines as the peak value of the updraft-mass-flux profile increases by −2 −1 16% from 0.32 kg·m ·s in the control-BIN-cdnc-only run in Figure 7(b). Regarding this, the peak value in the updraft −2 −1 −2 −1 mass fluxes increases by 9% from 0.23 kg·m ·s in the to 0.37 kg·m ·s in the 10M-BIN-cdnc-only run, while it −2 −1 −2 −1 increases by 11% from 0.27 kg·m ·s in the control-BULK- control-BIN-col run to 0.25 kg·m ·s in the control-BIN- −2 −1 −2 −1 sed run, while it increases by 9% from 0.22 kg·m ·s in the cdnc-only run to 0.30 kg·m ·s in the 10M-BULK-cdnc- −2 −1 10M-BIN-col run to 0.24 kg·m ·s in the 10M-BIN-sed only run. -e altitude of the peak is 3.9 (2.8) km in the control-BIN-cdnc-only run and the 10M-BIN-cdnc-only run. Sedimentation treatment appears to be of significant importance in making differences in updraft mass fluxes run (the control-BULK-cdnc-only run and the 10M- BULK-cdnc-only run) as in the control-BIN run and the between the schemes. 10M-BIN run (the control-BULK run and the 10M-BULK run). -is confirms that different distributions of CDNC are 4.12. Tests for Individual Effects of CDNC, Rain, and Cloud- the main cause of different responses of updraft mass fluxes Liquid Evaporative Cooling, Saturation, Collection, and to increasing aerosol concentration between the micro- Sedimentation Processes. Some of the simulations above physical schemes, in comparison with the standard runs, as involve multiple microphysical processes which are modi- shown in “noice-cdnc” runs. fied together. Hence, as described in Section 3.3, this pre- As seen in the control-BIN-no-rain-evp-only run, the vents the isolation of individual effects of some of processes. 10M-BIN-no-rain-evp-only run, the control-BULK-no- To isolate effects of each of those processes, the standard rain-evp-only run, and the 10M-no-rain-evp-only run in simulations are repeated by modifying a process of interest Figure 11(b), aerosol-induced differences are smaller be- only. -e basic setup and naming of those repeated simu- tween the control-BULK-no-rain-evp-only run and the lations are described in Section 3.3, and here, their results are 10M-BULK-no-rain-evp-only run as compared to a situa- described as follows. tion between the control-BULK run and 10M-BULK run. As seen in the control-BIN-cdnc-only run, the 10M- Associated with this, aerosol-induced difference in the peak BIN-cdnc-only run, the control-BULK-cdnc-only run, and value between the control-BULK-no-rain-evp-only run and Height (km) Height (km) Advances in Meteorology 23 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK-cdnc-only Control-BULK Control-BULK-no-rain- Control-BULK 10M-BULK-cdnc-only 10M-BULK evp-only 10M-BULK 10M-BULK-no-rain-evp-only Control-BIN-cdnc-only Control-BIN Control-BIN 10M-BIN-cdnc-only 10M-BIN Control-BIN-no-rain-evp-only 10M-BIN 10M-BIN-no-rain-evp-only (a) (b) 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK Control-BIN-sat-only Control-BULK-no-cld- Control-BULK evp-only 10M-BULK 10M-BIN-sat-only 10M-BULK 10M-BULK-no-cld-evp-only Control-BIN Control-BIN Control-BIN-no-cld-evp-only 10M-BIN 10M-BIN 10M-BIN-no-cld-evp-only (c) (d) Figure 11: Continued. Height (km) Height (km) Height (km) Height (km) 24 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass f lux (kg·m ·s ) Updraft mass f lux (kg·m ·s ) Control-BULK Control-BIN-col-only Control-BULK Control-BIN-sed-only 10M-BULK 10M-BIN-col-only 10M-BULK 10M-BIN-sed-only Control-BIN Control-BIN 10M-BIN 10M-BIN (e) (f) Figure 11: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-cdnc- only run, the 10M-BIN-cdnc-only run, the control-BULK-cdnc-only run, and the 10M-BULK-cdnc-only run. (b) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-rain-evp-only run, the 10M-BIN-no-rain- evp-only run, the control-BULK-no-rain-evp-only run, and the 10M-BULK-no-rain-evp-only run. (c) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-no-cld-evp-only run, the 10M-BIN-no-cld-evp-only run, the control-BULK-no-cld-evp-only run, and the 10M-BULK-no-cld-evp-only run. (d) Vertical distributions of the time- and domain- averaged updraft mass fluxes for the standard runs, the control-BIN-sat-only run, and the 10M-BIN-sat-only run. (e) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-col-only run, and the 10M-BIN-col-only run. (f) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BIN-sed-only run, and the 10M-BIN-sed-only run. the 10M-BULK-no-rain-evp-only run is less than between the control-BIN-no-cld-evp-only run and the 10M- −2 −1 0.01 kg·m ·s , and this is 80% smaller than that difference BIN-no-cld-evp-only run as compared to a situation be- between the control-BULK run and the 10M-BULK run. -e tween the control-BIN run and 10M-BIN run. Associated altitude of the peak in the control-BULK-no-rain-evp-only with this, the aerosol-induced difference in the peak value run and the 10M-BULK-no-rain-evp-only run is 2.8 km as in between the control-BIN-no-cld-evp-only run and the 10M- −2 −1 the control-BULK run and the 10M-BULK run. However, BIN-no-cld-evp-only run is 0.01 kg·m ·s , and this is 86% aerosol-induced differences are greater between the control- smaller than that difference between the control-BIN run BIN-no-rain-evp-only run and the 10M-BIN-no-rain-evp- and the 10M-BIN run. -e altitude of the peak in the only run than between the control-BIN run and the 10M- control-BIN-no-cld-evp-only run and the 10M-BIN-no-cld- BIN run. Associated with this, the aerosol-induced differ- evp-only run is 3.9 km as in the control-BIN run and the ence in the peak value between the control-BIN-no-rain- 10M-BIN run. However, the aerosol-induced difference evp-only run and the 10M-BIN-no-rain-evp-only run is between the control-BULK-no-cld-evp-only run and the −2 −1 0.09 kg·m ·s , and this is 29% greater than that difference 10M-BULK-no-cld-evp-only run is 18% different from that between the control-BIN run and the 10M-BIN run. -e between the control-BULK run and the 10M-BULK run in altitude of the peak in the control-BIN-no-rain-evp-only run terms of the peak values. -is demonstrates that aerosol and the 10M-BIN-no-rain-evp-only run is 3.9 km as in the responses in BIN, but not BULK, are controlled to a large control-BIN run and the 10M-BIN run. -is confirms that extent by cloud-liquid evaporative cooling, as shown in “no- aerosol responses in BULK, but not BIN, are controlled to a cld-evp” runs. large extent by rain evaporative cooling and gust front As seen in Figure 11(d), differences between the pair of generation, as shown in “no-rain-evp” runs. the control-BIN-sat-only run and the 10M-BIN-sat-only run As seen in the control-BIN-no-cld-evp-only run, the and the pair of the control-BULK run and the 10M-BULK 10M-BIN-no-cld-evp-only run, the control-BULK-no-cld- run are slightly greater than those between the pair of the evp-only run, and the 10M-BULK-no-cld-evp-only run in control-BIN run and the 10M-BIN run and the pair of the Figure 11(c), aerosol-induced differences are much smaller control-BULK run and 10M-BULK run. Associated with Height (km) Height (km) Advances in Meteorology 25 −2 −1 this, a difference in the mean peak value between the pair of by 4% from 0.25 kg·m ·s in the 10M-BULK run to −2 −1 the control-BIN-sat-only run and the 10M-BIN-sat-only run 0.24 kg·m ·s in the 10M-BULK-2 mt run. Also, there is an and the pair of the control-BULK run and the 10M-BULK increase in updraft mass fluxes above 4 km in the control- run is 33% greater than that between the pair of the control- BULK-2 mt run, as compared to the control-BULK run, and BIN run and the 10M-BIN run and the pair of the control- in the 10M-BULK-2 mt run, as compared to the 10M-BULK BULK run and 10M-BULK run. -e altitude of the peak in run. -is is because the use of the two-moment scheme the control-BIN-sat-only run and the 10M-BIN-sat-only run induces increases in the mass or loading of snow and graupel is 3.9 km as in the control-BIN run and the 10M-BIN run. at low altitudes around 4 km and decreases in the mass at Remember that the mean peak value between the control- high altitudes above 4 km, which is similar to findings by −2 −1 BULK run and the 10M-BULK run is 0.26 kg·m ·s , while Wacker and Seifert [41]. the mean value between the control-BIN run and the 10M- Figure 10 shows the final comparison between BIN and −2 −1 BIN run is 0.32 kg·m ·s . -e mean peak value between the BULK. Hence, as another good example of how the two- control-BIN-sat-only run and the 10M-BIN-sat-only run is moment prediction affects results here, Figures 10 and 12(b) −2 −1 0.34 kg·m ·s . -is confirms that the different treatment of are compared. In Figure 12(b), results from the repeated saturation is not able to explain the cause of the discrepancy control-BULK-no-cld-evp run and the 10M-BULK-no-cld- between the BIN simulations and the BULK simulations. As evp run with two-moment prediction for snow and graupel seen in Figures 11(e) and 11(f), differences between the pair are shown together with some of simulations that are depicted of the control-BIN-col-only run (the control-BIN-sed-only in Figure 10 and are the control-BIN-sed run, the 10M-BIN- run) and the 10M-BIN-col-only run (the 10M-BIN-sed-only sed run, the control-BIN-no-cld-evp run, and the 10M-BIN- run) and the pair of the control-BULK run and 10M-BULK no-cld-evp run; these sensitivity runs with two-moment run are smaller than those between the pair of the control-BIN prediction are the control-BULK-no-cld-evp-2 mt run and run and the 10M-BIN run and the pair of the control-BULK the 10M-BULK-no-cld-evp-2 mt run. Comparisons between run and 10M-BULK run. Associated with this, a difference in Figures 10 and 12(b) demonstrate that whether graupel and the mean peak value between the pair of the control-BIN-col- snow adopt the two-moment prediction in BULK does not only run (the control-BIN-sed-only run) and the 10M-BIN- affect the very small differences in updraft mass fluxes be- col-only run (the 10M-BIN-sed-only run) and the pair of the tween the pair of the control-BIN-sed run and the 10M-BIN- control-BULK run and 10M-BULK run is 50 (33)% smaller sed run and the pair of “BULK-no-cld-evp” runs. than that between the pair of the control-BIN run and the 10M-BIN run and the pair of the control-BULK run and 10M- 5. Summary and Conclusions BULK run. -e mean peak value between the control-BIN- col-only run (the control-BIN-sed-only run) and the 10M- -is study mainly focuses on and examines key micro- BIN-col-only run (the 10M-BIN-sed-only run) is 0.23 (0.22) physical processes that cause differences in the simulations −2 −1 kg·m ·s . -e altitude of the peak in the control-BIN-col- of clouds and aerosol-cloud interactions between two mi- only run, the control-BIN-sed-only run, the 10M-BIN-col- crophysical schemes, i.e., BIN and BULK. For this exami- only run, and the 10M-BIN-sed-only run is 3.9 km as in the nation, this study focuses on differences in updrafts, which control-BIN run and the 10M-BIN run. -is confirms that are represented by updraft mass fluxes, and their response to different autoconversion and accretion (sedimentation) increasing aerosol concentration between BIN and BULK. treatment play an important role in explaining differences Aerosol-induced invigoration of convection is simulated between the BIN simulations and the BULK simulations as with BIN, but not simulated with BULK. Stated differently, shown in the control-BIN-col run and the 10M-BIN-col run there are aerosol-induced increases in updraft mass fluxes (the control-BIN-sed run and the 10M-BIN-sed run). with BIN, while there are no aerosol-induced those increases with BULK. -e profile or pattern of the vertical distribution of updraft mass fluxes with BULK is substantially different 4.13. Two-Moment Prediction for Snow and Graupel. As from that with BIN in terms of the altitude and magnitude of exemplified by Figure 12(a), comparisons among the con- the updraft-mass-flux peak and the vertical variation of trol-BULK-2 mt run and the 10M-BULK-2 mt run with the updraft mass fluxes around it. Results here indicate that two-moment prediction for snow and graupel and the whether the invigoration is present or not is strongly de- previous runs with the one-moment prediction for snow and pendent on how CDNC is predicted. -e different pattern of graupel as in the control-BULK run and the 10M-BULK run the updraft-mass-flux distribution between the schemes is demonstrate that the qualitative nature of results does not due to much larger snow mass and associated loading vary with the varying prediction method for snow and around the freezing level in the simulations with BULK than graupel. However, as seen in Figure 12(a), with the use of the those with BIN. -e much greater loading of snow mass two-moment prediction, the altitude of the distribution peak hinders the growth of updraft mass fluxes around the and the peak value is lowered. -e altitude of peak lowers by freezing level. -is lowers the altitude and magnitude of the 32% from 2.8 km in the control-BULK run and the 10M- updraft-mass-flux peak and causes much larger vertical BULK run to 1.9 km in the control-BULK-2 mt run and the variation of updraft mass fluxes around the altitude where 10M-BULK-2 mt run, while the peak value lowers by 3% the peak occurs in the BULK simulations. It is notable that −2 −1 from 0.27 kg·m ·s in the control-BULK run to the latent heating or cooling associated with ice processes −2 −1 0.26 kg·m ·s in the control-BULK-2 mt run, and it lowers does not affect the vertical pattern of updraft mass fluxes in 26 Advances in Meteorology 18 18 16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 –2 –1 –2 –1 Updraft mass flux (kg·m ·s ) Updraft mass flux (kg·m ·s ) Control-BULK-no-cld-evp-2mt Control-BULK Control-BULK Control-BULK-2mt 10M-BULK 10M-BULK-2mt 10M-BULK-no-cld-evp-2mt 10M-BULK Control-BIN Control-BIN-no-cld-evp Control-BIN 10M-BIN-no-cld-evp 10M-BIN 10M-BIN Control-BIN-sed 10M-BIN-sed (a) (b) Figure 12: (a) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the standard runs, the control-BULK-2 mt run, and the 10M-BULK-2 mt run. (b) Vertical distributions of the time- and domain-averaged updraft mass fluxes for the simulations in Figure 10 except for the fact that the control-BULK-no-cld-evp run and the 10M-BULK-no-cld-evp run are replaced with the control- BULK-no-cld-evp-2 mt run and the 10M-BULK-no-cld-evp-2 mt run. the simulations with BULK much as compared to the With the fixed CDNC, removed ice processes, and loading of snow. evaporative cooling, the vertical pattern of updraft mass Although differences in the CDNC prediction and ice fluxes shows negligible differences between simulations with BIN and those with BULK and the variation in updraft mass processes (including the snow process) are removed, thus, the differences in the invigoration are removed and those in fluxes from the high-aerosol case to the low-aerosol case for each of BIN and BULK is nearly removed. However, there the pattern of the vertical distribution of updraft mass fluxes are nearly removed between the simulations with BIN and are still remaining differences in the magnitude of updraft those with BULK, there are still remaining differences. mass fluxes between the simulations with BULK and those Among these remaining differences, differences between the with BIN. -ese remaining differences are explained by high-aerosol case and the low-aerosol case for each of BIN different treatments of collection and sedimentation pro- and BULK are controlled by aerosol-induced changes in cesses; however, the impact of the different treatments of evaporation-related cooling and the associated gust front saturation on the remaining differences is negligible. -is intensity. While the differences in updraft mass fluxes are qualitative nature of roles by collection, sedimentation, and explained by different rain evaporative cooling between the saturation processes in explaining differences between the BULK simulations and the BIN simulations is also produced high-aerosol case and the low-aerosol case with BULK, those differences in cooling, due to rain evaporation, do not ex- in the repeated standard runs where only each of these plain those differences in updraft mass fluxes with BIN. processes is tested. -ose differences in updraft mass fluxes with BIN are -ere are around dozens or more of microphysical explained by the differences in cloud-liquid evaporative schemes that have been created. Also, each scheme has its cooling. -is qualitative nature of roles by each of rain and own different versions. It would be the best strategy to cloud-liquid evaporative cooling in explaining differences compare all of those present schemes and their different between the high-aerosol case and the low-aerosol case for versions for obtaining perfectly general conclusions. How- each of BIN and BULK is also produced in the repeated ever, performing process-level research as shown in this paper by modifying each microphysical process in the model standard simulations where only rain or cloud-liquid evaporative cooling is turned off. code requires a large amount of time and computer Height (km) Height (km) Advances in Meteorology 27 processes not tested in this study. Despite this, it is believed resources even for the comparison between the selected two schemes. Unfortunately, the funding, associated time, and that the fact that processes tested in this study explain most of differences between the schemes should be considered as computer resources given are not enough to perform process-level research for all of present microphysical an important finding based on which we can gain a pre- schemes and their different versions. Maybe, comparing all liminary understanding of key processes, and thus, this study of those present schemes for one or two specific processes achieves its main goal. such as autoconversion and/or sedimentation may be pos- sible. -ere are studies such as Liu and Daum [44] and Lee Data Availability and Baik [45] that compare more than two microphysical schemes for a specific process; however, these studies also do -e data used are currently private and stored in our private not deal with all of present schemes due to limit on time and computer system. Opening the data to the public requires computer resources. Considering the limit on time and approval from the funding source. Since the funding project resources, we have to make a compromise between process- associated with this work is still going on, the source does not level research which tests numerous microphysical processes allow the data to be open to the public, and 2-3 years after the individually and the number of microphysical schemes that project ends, the data can be open to the public. However, if are tested. In the process of making the compromise, this there is any inquiry about the data, contact the corresponding study leans toward process-level research by sacrificing the author Seoung Soo Lee (cumulss@gmail.com). number of microphysical schemes tested and associated generality of results. -is is motivated by the fact that, as Disclosure stated in introduction, the identification of key processes, which create the discrepancy in the simulation of the Seoung Soo Lee is now at Department of Meteorology, San feedbacks between increasing aerosol concentration, mi- Jose State University, San Jose, CA, USA. crophysics, and dynamics among models, has been rarely performed, and the community does not have even a pre- Conflicts of Interest liminary and basic understanding of those key processes themselves; note that the identification of key processes -e authors declare that they have no conflicts of interest. requires process-level research as shown in this study. Hence, through process-level research, this study provides Acknowledgments preliminary, though not general, information on those key processes, by comparing the limited number of schemes, as a -is study was supported by NOAA (NOAA-NWS-NWSPO- stepping stone to the general information which can be 2015-2004117), NASA/MUREP Cooperative Agreement pursued in the future studies. Considering that the in- (NNX15AQ02A), the Ministry of Education (NRF-2018R1D formation on those key processes has been near absent, it is 1A1A09083227), and the National Strategic Project-Fine believed that this preliminary information itself is valuable Particle of the National Research Foundation of Korea by providing a preliminary clue to how to approach the (NRF) funded by the Ministry of Science and ICT (MSIT), the discrepancy among models, despite the fact that compari- Ministry of Environment (MOE), and the Ministry of Health sons for the limited number of schemes are not as perfect as and Welfare (MOHW) (NRF-2017M3D8A1092022). It was those between all of the present schemes. also supported by the National Institute of Environment Re- It should be reiterated that the main goal of this study is search (NIER), funded by the MOE (NIER-2018-01-02-033), to identify “key” processes, but not all processes, which and via Public Technology Program Based on Environmental contribute to differences in updrafts and their responses to Policy (2017000160003). increasing aerosol concentration between the schemes. -e first reason for not focusing on all those processes is that we References even do not know what those key processes are to say nothing of all those processes and thus identifying those key [1] M. Bollasina and S. Nigam, “Indian ocean SST, evaporation, processes itself can be an important key stepping stone to the and precipitation during the South Asian summer monsoon understanding of how differences in updrafts and their in IPCC-AR4 coupled simulations,” Climate Dynamics, responses are created between BIN and BULK. It should be vol. 33, no. 7-8, pp. 1017–1032, 2009. noted that, as seen in Section 4.11 and Figure 10, sensitivity [2] S. S. Lee, B.-G. Kim, C. Lee, S. S. Yum, and D. Posselt, “Effect of aerosol pollution on clouds and its dependence on pre- tests for BULK and BIN show similar results in the tro- cipitation intensity,” Climate Dynamics, vol. 42, no. 3-4, posphere where clouds form, and this indicates that pro- pp. 557–577, 2014. cesses tested in this study are key and main processes that [3] S. S. Lee, B.-G. Kim, S. S. 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