Impacts of Enhanced Cloud Condensation Nuclei (CCN) on the Organization of Convection for Monsoon Depressions

这个项目试图了解气溶胶污染对季风低气压的影响。季风低压是具有斜压(或倾斜)垂直结构的天气尺度系统(2000公里至3000公里)，向西传播，形成于孟加拉湾，在经过任何地点时产生多达150至200毫米的降雨量。它们发生在季风季，此时纬向风的垂直切变足够强，足以抑制飓风强度的热带气旋的形成，它们与被称为“季风低”的较弱但相似的系统截然不同，后者具有正压(或垂直)垂直结构。首席调查员认为，在印度地区发现的严重气溶胶污染导致季风低气压的发生频率减少。这一论断基于几条证据：首先，季风低气压的发生急剧减少，从历史上每年平均7到8次减少到2009、2010和2011年的1、0和2次。其次，近年来，印度地区的气溶胶污染急剧增加。第三，全球预测模型可能没有考虑到气溶胶污染的变化，它们对近年来季风低气压的预测过高，几乎没有预测到季风低气压。第四，天气研究和预报(WRF)模式的初步实验表明，通过将气溶胶负荷从相对原始的(5x10^8粒子/立方米)增加到重度污染(5x10^10/立方米)，季风低压的强度以及其中降水的强度和组织可以显著降低。这项研究基于一种假设，即气溶胶抑制季风低气压是因为它们减缓了降雨的形成，因为更多的气溶胶会导致更多的云凝结核(CCN)，从而产生更多更小的云滴，这些云滴需要更长的时间才能凝结成雨滴。季风低压是由大尺度气流的斜压/正压不稳定和伴随降水的凝结潜热相互作用形成的。这种相互作用可以被过量的气溶胶抑制，它使降水形成所需的时间增加了大约两倍，从而在流体动力不稳定的时间尺度与降水的组织和伴随的潜热释放之间产生了不匹配。在该奖项下开展的工作使用更复杂和现实的模拟来测试气溶胶污染对季风低气压的假设抑制，并基于卫星数据对季风低气压形成期间和没有季风低气压时的气溶胶强迫进行分析。鉴于受季风低气压影响的人口众多，本研究涉及的抑制季风低压具有科学和社会意义。如果成功，这项工作的结果可以直接应用于用于预报这些天气系统的业务预报系统。此外，该项目还为博士后和研究生提供支持和培训，从而为这一研究领域的下一代科学家提供支持。

This project seeks to understand the effect of aerosol pollution on monsoon depressions. Monsoon depressions are synoptic-scale systems (2,000km to 3,000km) with baroclinic (or tilted) vertical structure which propagate westward, forming in the Bay of Bengal and producing as much as 150 to 200 mm of rainfall during their passage over any location. They occur during the monsoon season, when the vertical shear of the zonal wind is strong enough to inhibit the formation of hurricane-strength tropical cyclones, and they are distinct from weaker but similar systems called "monsoon lows", which have a barotropic (or upright) vertical structure. The Principal Investigator argues that the heavy aerosol pollution found over the Indian sector causes a reduction in the frequency of occurrence of monsoon depressions. This claim is based on several lines of evidence: first, there has been a dramatic reduction in the occurrence of monsoon depressions, from an annual average of 7 to 8 historically to 1, 0, and 2 in the years 2009, 2010, and 2011. Second, aerosol pollution has increased dramatically over the Indian sector in recent years. Third, global forecast models, which presumably do not account for the change in aerosol pollution, have overpredicted monsoon depressions in the recent years with few depressions. Fourth, preliminary experiments with the Weather Research and Forecasting (WRF) model show that the strength of monsoon depressions, and the intensity and organization of precipitation within them, can be dramatically reduced by increasing the aerosol burden from relatively pristine (5x10^8 particles per cubic meter) to heavily polluted (5x10^10 per cubic meter) values. The research is based on the hypothesis that aerosols suppress monsoon depressions because they slow the formation of rainfall, as more aerosols lead to more cloud condensation nuclei (CCN), which produce a greater number of smaller cloud droplets, which take longer to coalesce into raindrops. Monsoon depressions form through a mutual interaction between the baroclinic/barotropic instability of the large-scale flow and the latent heat of condensation accompanying precipitation within the depression. This mutual interaction can be suppressed by the excess aerosols, which increase time required for the development of precipitation by roughly a factor of two, and thus produce a mismatch between the timescales of the hydrodynamic instability and the organization of precipitation and accompanying latent heat release. Work performed under this award tests the hypothesized suppression of monsoon depressions by aerosol pollution using more sophisticated and realistic simulations, and also performs analysis of aerosol forcing, based on satellite data, during periods when monsoon depressions form and when they are absent.The suppression of monsoon depressions addressed in this research is of both scientific and societal interest, given the large population that is affected by them. If successful, the results of this work could be directly applied to operational forecasting systems used to predict these weather systems. In addition, the project provides support and training for a postdoc and a graduate student, thereby providing for the next generation of scientists in this research area.