HNO3gHNO3all

Figure 18. Partition of sulfuric acid and nitric acid between the gas phase and the liquid phase as a function of atmospheric liquid water content and droplet pH. The vertical axis is the fraction of these acids that exists in the gas phase.

type aerosols, from which sulfate was produced in particles but outside of the light-scattering size range.

In the above we discussed the modification of aerosol composition and size distribution through the combination of cloud chemistry and two microphysical processes — activation and condensation. Other cloud-microphysical processes may modify aerosols without the involvement of chemistry, such as droplet collision, riming or sedimentation. When droplets collide and coalesce, they not only combine water mass but also solute mass, as shown previously in Fig. 12. When these coalesced droplets evaporate, they leave behind much larger aerosols, but with lower number concentration. This mechanism is a possible reason why some marine stratiform clouds suddenly develop drizzle. It is thought that the slow collision-coalescence occurring in these clouds gradually modifies the CCN size distribution and produces more and more giant CCNs. After a few cloud cycles, there might be enough giant CCNs to initiate strong drizzle (Feingold, 1999). To the extreme, this may lead to a sudden breakdown of marine stratiform clouds (see Subsecs. 2.1.1 and 2.1.2). Mixed-phase collision (e.g. riming) may have similar effects, and this often leads to precipitation — hence the removal of the potential aerosols. Note that traditional spectral (bin) microphysical models such as those of Feingold et al. (1999) or Lynn et al. (2005), although very detailed in resolving the size spectrum of cloud particles, cannot accurately simulate aerosol recycling through clouds as discussed above, because they do not resolve the additional solute component shown in Fig. 12.

3.2. Precipitation scavenging

Cloud and precipitation scavenging is an important factor in determining the lifetimes of many atmospheric trace chemicals, including aerosols. Aerosols may be incorporated into cloud drops and ice crystals either by activation/nucleation or by collections (gravitational collection, Brownian collection and pho-retic collection), then removed along with the precipitation — a process often referred to as in-cloud scavenging or rainout. The collection process may also occur below the cloud base, which is referred to as below-cloud scavenging or washout. The fraction of aerosols (as well as trace gases) being scavenged depends on the microphysical processes through which they are incorporated into cloud particles. In other words, the scavenging of aerosols by clouds is essentially determined by how the precipitation is formed and cannot be easily estimated by the amount of the precipitation fall on the surface. This is in fact one of the most difficult issues in the modeling of aerosols in regional and global models, which often lacks detailed description of cloud microphysics. The interaction between microphysics and chemistry which was discussed earlier further complicates the problem.

Recognizing the importance of cloud micro-physics for the removal of atmospheric trace chemicals, Chen and Lamb (1994, 1999) developed a mixed phase cloud-microphysical model coupled with aqueous phase and ice phase chemistry to investigate the complex scavenging mechanisms. This multicomponent model allows simultaneous and independent changes of various physical and chemical properties of the cloud particles. For the results given below, they applied two bin components (water mass and major solute mass) for the liquid phase framework (see Subsec. 2.1.4) and three bin components (water mass, major solute mass, and aspect ratio — defined as the ratio of the c-axis length to the a-axis length of crystals) for the ice-phase framework. The simultaneous consideration of water and solute mass contents allows this model to resolve truthfully the aerosol-cloud interactive processes, such as the size-dependent aqueous chemistry and the recycling of aerosols after cloud dissipation. The liquid phase microphysical processes considered in the model are the activation of condensation nuclei into cloud drops, the subsequent condensational growth, and collision-coalescence and breakup. The ice phase processes included are heterogeneous deposition/condensation nucleation, heterogeneous freezing, contact freezing, homogeneous freezing, diffusional growth, accretional growth, rime-splintering, melting, shedding due to melting and wet riming, and the aggregation of snow crystals. Besides the acquisition of water and solute, the change of shape (aspect ratio) due to all these processes is calculated explicitly following the adaptive crystal shape scheme of Chen and Lamb (1994a). To facilitate discussions, ice particles in the three-dimensional (water mass, solute mass, shape) ice framework are classified, following conventional terms, into cloud ice, planner ice, columnar ice, rimed crystals (i.e. graupel) and crystal aggregates according to their shape, chemical content and density. The aqueous phase chemistry considered includes the absorption/desorption of NH3, H2SO4, HNO3, SO2, O3, H2O2, CO2, their ionic dissociations, and the oxidation of sulfite by O3 and H2O2. The ice phase chemical processes included are the sorption/desorption of SO2 and H2O2 onto the ice surface, as well as the entrapment of SO2 inside the ice during riming.

The example given here is a case of wintertime orographic cloud formation over the Sierra Nevada Crest and Carson Range in the western US on 18 December 1986. Figure 19 shows the simulated liquid phase and ice-phase cloud fields over the mountains. The LWCs in both clouds are mostly below 0.2 gm-3, which is typical of such orographic clouds. The aerosol type applied in this simulation is of remote continental conditions with a total aerosol concentration of about 6,000cm-3. This relatively clean condition plus a low updraft speed of the upslope wind result in a low CDNC, which has the highest value near the cloud base, ranging from 106 to 274 cm-3, then gradually decreases toward the upslope because of collision-coalescence and collection by ice crystals. Light rains develop near and below the base of the first cloud, and these raindrops are not formed by warm cloud processes, but by melted ice falling from aloft. In Figs. 19(d) and 19(f) one may observe two zones of planner ice and two zones of columnar ice that are in accordance with the growth habit regimes reported by Nakaya (1954) and Hallet and Mason (1958). Some of the earliest-formed plates and columns grow big enough to commence accretion of cloud drops and turn into rimed crystals [Figs. 19(g) and 19(h)], which are the main source of raindrops at the lower levels. After the depletion of larger cloud drops by the riming process, ice crystals grew mainly by vapor deposition. Some of these pristine crystals collide and coagulate into snow aggregates [Figs. 19(i) and 19(j)], becoming the main form of precipitation at the latter stage of cloud development. Note that all liquid droplets evaporate over the downslope region between the two mountain peaks, but ample ice crystals survive and re-enter the second cloud.

The types of precipitation falling on the ground are shown in Fig. 20(a). One can see that rainfall first develops between about 30 and 70 km. Beyond about 70 km, there is still a minor amount of "rainfall", but it is actually a deposition of cloud droplets because by then the cloud is in contact with the ground. As mentioned earlier, the rain forms mainly from melted graupel. Since the temperature becomes lower while going uphill, the portion of graupel that remains unmelted becomes greater, and reaches a peak at about the 70 km distance. After that, snow aggregates started to appear and become the main precipitation type for a short while before columnar ice emerges. Such a sequential change of precipitation types is commonly observed in cold orographic or stratiform clouds. In the second cloud (over the second mountain peak), because there are remnant ice crystals from the first cloud to feed in, aggregates form rather early as compared to the first cloud. In addition, the early presence of ice crystals prohibits (due to the Bergeron-Findeison process) cloud drops to grow large enough

50 1

distance [km)

50 100

distance (km)

Figure 19. Simulated distribution of various cloud condensates over the Sierra Nevada Crest and Carson Range. The left and the right panel show are mixing ratios of condensed water and their number concentrations, respectively. From the top down are different condensate types of droplets including cloud drops (light shading) and raindrops (dark shading), planner ice (plates), columnar ice (columns), rimed ice (graupel) and snow aggregates. The mixing ratios are in g m-3, while the number concentrations are in cm-3 for cloud drops and in L-1 for raindrops and ice crystals. The minimum contour of the mixing ratio (number concentration) is 0.01(0.1) and increases by a half-decade for each additional interval except for the 0.032 (0.32) contours that are omitted; shadings indicate values > 0.1 (> 1) for cloud drops and ice crystals, and > 0.01(> 1) for raindrops. (From Chen and Lamb, 1999.)

50 1

distance [km)

50 100

distance (km)

Figure 19. Simulated distribution of various cloud condensates over the Sierra Nevada Crest and Carson Range. The left and the right panel show are mixing ratios of condensed water and their number concentrations, respectively. From the top down are different condensate types of droplets including cloud drops (light shading) and raindrops (dark shading), planner ice (plates), columnar ice (columns), rimed ice (graupel) and snow aggregates. The mixing ratios are in g m-3, while the number concentrations are in cm-3 for cloud drops and in L-1 for raindrops and ice crystals. The minimum contour of the mixing ratio (number concentration) is 0.01(0.1) and increases by a half-decade for each additional interval except for the 0.032 (0.32) contours that are omitted; shadings indicate values > 0.1 (> 1) for cloud drops and ice crystals, and > 0.01(> 1) for raindrops. (From Chen and Lamb, 1999.)

Figure 20. Simulated surface precipitation (top) and column-integrated relative removal efficiencies of various trace chemicals by liquid precipitation (middle) and ice precipitation (bottom) from the clouds shown in Fig. 19.

to be accreted by rimed ice. That is why not much graupel-type precipitation develops from the second cloud.

The types of precipitation (and the formation mechanisms) strongly influence the removal of trace chemicals. As the "precipitation rate of water" is quite a common scientific notion, we shall express the strength of chemical scavenging (i.e. precipitation rate of chemicals)

using a relative concept. We define the relative removal efficiency, Er, which represents the proportion of chemicals in the air being removed by precipitation compared to that of water in the air, with the following formulation (Lamb and Chen, 1990):

Er ki

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