Collaborative Research: Inhibition of Snowfall by Pollution Aerosols

这是一个合作项目，研究空气污染对降雪率和降雪量的影响。其中两名研究人员(Borys和Lowenthal)之前的工作发现，有证据表明，污染空气中的颗粒物会降低降雪率和降雪量。其机制没有完全被记录下来，但在早期的工作中清楚地表明，与空气污染相关的更高的颗粒浓度包含了更多的云凝结核(CCN)，云滴在这些颗粒上形成。因此，污染增加了云滴的浓度，但减少了它们的平均尺寸，从而降低了下落的冰晶与过冷的液滴碰撞而生长的效率。因此，污染减少了从云中收集并在降雪中沉积的过冷水的数量，从而减少了降水。这项研究将采取更多步骤，以确定沙漠研究所风暴峰实验室观察到的冬季地形云层的降雪量如何因与污染有关的高浓度气溶胶颗粒而减少。这项先前工作的扩展将包括直接测量CCN，继续观测降雪和降水，以及建立模型以建立污染和降雪量之间的物理联系。该项目将使用一个中尺度模式，该模式已经展示了预测降雨率和降水量的技能。主要目标是：*确定污染气溶胶负荷与降雪率之间的关系；*确定结冰、雪晶大小、结晶习性和大尺度气象特征在确定降雪率方面的相对重要性；*使用Rams中尺度模式和模拟Bin的微物理对上述影响进行敏感性研究；以及*通过使用中尺度模式估计污染气溶胶对研究区降雪率和降雪量的定量影响。预期结果是一种新的能力，预测空气污染如何影响原始山区的降雪，从而改变水资源至关重要的地区的分水岭。该项目还应有助于更好地理解如何在天气和气候模型中表示空气污染的影响，特别是在它们影响降水的情况下。

This is a collaborative project to study the effect of air pollution on snowfall rates and amounts. Previous work by two of the investigators (Borys and Lowenthal) developed evidence suggesting that the particles in polluted air decrease snowfall rates and amounts. The mechanism, not fully documented but clearly suggested by earlier work, is that the higher particle concentrations associated with air pollution contain increased numbers of cloud condensation nuclei (CCN), the particles on which cloud droplets form. Pollution thus increases the concentration of cloud droplets but decreases their average size, and so decreases the efficiency with which falling ice crystals grow by collision with the supercooled droplets. Pollution therefore reduces precipitation by reducing the amount of supercooled water collected from clouds and deposited in snowfall. The study will take additional steps toward determining how snowfall from winter orographic clouds, observed at the Desert Research Institute's Storm Peak Laboratory, is reduced by the high concentration of aerosol particles associated with pollution. This extension of previous work will include direct measurement of the CCN, continued observations of snowfall and precipitation, and modeling to establish the physical links between pollution and snowfall amount. The project will use a mesoscale model that has demonstrated skill in predicting precipitation rates and amounts. Key objectives are these:* To determine the relationship between pollution-aerosol loading and snowfall rate;* To determine the relative importance of riming, snow crystal size, crystal habit, and large-scale meteorological features in determining the snowfall rate;* To conduct sensitivity studies of effects including the above using the RAMS mesoscale model with bin-emulating microphysics; and* To estimate the quantitative effect of pollution aerosol on snowfall rate and amount in the study region through use of the mesoscale model.The anticipated result is a new ability to predict how air pollution affects snowfall in pristine mountainous areas and so changes the watershed in areas where water resources are critically important. The project should also lead to improved understanding of how to represent the effects of air pollution in models of weather and climate, especially as they influence precipitation.