Using Improved Aerosol Optical Thickness (AOT) and Cloud Condensation Nuclei (CCN) Relationship and Aerosol Composition to Study the Impact of Aerosol on Cloud Microphysics

气溶胶-云相互作用（ACI）是所有已知气候强迫机制中最大的不确定性之一。 简而言之，ACI 最终由云属性对云凝结核（CCN）变化的响应决定，因此，CCN 的知识是理解 ACI 的关键。 由于对 CCN 进行大规模连续观测不切实际，更容易测量的气溶胶光学量，例如气溶胶光学深度 (AOD)，已在 ACI 研究中广泛用作 CCN 的代理，尽管这两种属性代表了气溶胶的不同方面。 另一方面，这两种特性均受到气溶胶粒径分布和化学成分的影响，因此存在一定程度的相关性。 在 NSF 资助的这项研究的第一阶段，我们利用了 AOD 和 CCN 之间的关系，重点关注气溶胶物理特性和环境气象学的影响。气溶胶-云相互作用 (ACI) 是所有已知气候强迫机制中最大的不确定性之一。 简而言之，ACI 最终由云属性对云凝结核（CCN）变化的响应决定，因此，CCN 的知识是理解 ACI 的关键。 由于对 CCN 进行大规模连续观测不切实际，更容易测量的气溶胶光学量，例如气溶胶光学深度 (AOD)，已在 ACI 研究中广泛用作 CCN 的代理，尽管这两种属性代表了气溶胶的不同方面。 另一方面，这两种特性均受到气溶胶粒径分布和化学成分的影响，因此存在一定程度的相关性。 在 NSF 资助的这项研究的第一阶段，我们利用了 AOD 和 CCN 之间的关系，重点关注气溶胶物理特性和环境气象学的影响。本研究将继续追求，但重点是研究气溶胶成分和吸湿性对 ACI 估计的影响，通过观察和建模来估计和减少由于使用此类关系而产生的不确定性。 智力优点：1。综合分析云微物理特性对气溶胶光学、化学和吸湿特性的响应，有助于深入了解气溶胶间接效应背后的机制。2．考虑这些影响将有助于识别和量化气溶胶间接影响估计中的偏差，而传统方法使用 AOD 的地面或卫星测量作为 CCN 的代理，以便更好地估计不同气象条件下不同类型气溶胶的 ACI。3。通过考虑动态和热力学条件的影响，建模有助于解释云微物理特性如何响应气溶胶成分/吸湿性背后的机制。更广泛的影响：1。随着对气溶胶化学成分和/或吸湿性对云微物理性质影响的认识和理解的加深，将更好地理解气溶胶间接效应的机制。这将有助于缩小政府间气候变化专门委员会 (IPCC) 报告所确定的大范围不确定性。2。该研究将为本科生、研究生以及博士后提供测量气溶胶、检索云特性、数据分析和建模方面的跨学科培训机会。3．该研究将对云物理、大气化学、气候和环境课程的教学产生直接影响。

The aerosol-cloud-interaction (ACI) is one of the largest uncertainties of all known climate forcing mechanisms. In the nutshell, the ACI is ultimately determined by the responses of cloud properties to variations in cloud condensation nuclei (CCN) whose knowledge is thus the key to understanding the ACI. Due to the impracticability of making large-scale continuous observations of CCN, the more readily measured aerosol optical quantities, such as aerosol optical depth (AOD), have been widely used as a proxy for CCN in ACI studies even though both properties represent different aspects of aerosols. On the other hand, the two properties are affected by aerosol size distribution and chemical composition, so are linked to a certain degree. In the first phase of this study funded by the NSF, the relationship between AOD and CCN with a focus on the influences of aerosol physical properties and ambient meteorology has been exploited.The aerosol-cloud-interaction (ACI) is one of the largest uncertainties of all known climate forcing mechanisms. In the nutshell, the ACI is ultimately determined by the responses of cloud properties to variations in cloud condensation nuclei (CCN) whose knowledge is thus the key to understanding the ACI. Due to the impracticability of making large-scale continuous observations of CCN, the more readily measured aerosol optical quantities, such as aerosol optical depth (AOD), have been widely used as a proxy for CCN in ACI studies even though both properties represent different aspects of aerosols. On the other hand, the two properties are affected by aerosol size distribution and chemical composition, so are linked to a certain degree. In the first phase of this study funded by the NSF, the relationship between AOD and CCN with a focus on the influences of aerosol physical properties and ambient meteorology has been exploited. This study will continue the pursuit but focus on investigating the effects of aerosol composition and hygroscopicity on the estimation of the ACI, estimating and reducing uncertainties due to the use of such relationships by means of both observations and modeling. Intellectual Merit:1. A comprehensive analysis on the responses of cloud microphysical properties to aerosol optical, chemical, and hygroscopic properties will help gain deeper insights into the mechanisms behind the aerosol indirect effect.2. Accounting for the effects will help identify and quantify a bias in the estimate of the aerosol indirect effects by the conventional approach using ground or satellite measurements of AOD as a proxy for CCN to obtain better estimate of the ACI for different types of aerosols under diverse meteorological conditions.3. Modeling helps explain the mechanisms behind how cloud microphysical properties respond to aerosol composition/hygroscopicity by accounting for the influence of dynamic and thermodynamic conditions.Broader Impacts:1. With an improved knowledge and understanding of the influence of aerosol chemical composition and/or hygroscopicity on cloud microphysical properties, the mechanism of aerosol indirect effect will be better understood. This will help narrow the large range of uncertainties as identified by the Intergovernmental Panel on Climate Change (IPCC) reports.2. The research will provide interdisciplinary training opportunities for undergraduate and graduate students, and postdoctoral fellows in measuring aerosols, retrieving cloud properties, data analysis, and modeling.3. The study will have an immediate impact on the teaching of cloud physics, atmospheric chemistry, climate, and environmental courses.