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，云凝结核(CCN)变化对云性质的响应最终决定了ACI，而CCN的知识是理解ACI的关键。由于对CCN进行大规模连续观测是不现实的，更容易测量的气溶胶光学参数，如气溶胶光学厚度(AOD)，在ACI研究中被广泛用作CCN的替代物，尽管这两种性质代表了气溶胶的不同方面。另一方面，这两种性质又受气溶胶的粒度分布和化学成分的影响，具有一定的关联性。在这项由NSF资助的研究的第一阶段，研究了气溶胶物理性质和环境气象因素对气溶胶光学厚度和大气环流的影响。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，云凝结核(CCN)变化对云性质的响应最终决定了ACI，而CCN的知识是理解ACI的关键。由于对CCN进行大规模连续观测是不现实的，更容易测量的气溶胶光学参数，如气溶胶光学厚度(AOD)，在ACI研究中被广泛用作CCN的替代物，尽管这两种性质代表了气溶胶的不同方面。另一方面，这两种性质又受气溶胶的粒度分布和化学成分的影响，具有一定的关联性。在这项由美国国家科学基金会资助的研究的第一阶段，研究了气溶胶物理性质和环境气象的影响，探讨了气溶胶光学厚度和大气环流之间的关系。这项研究将继续努力，但重点是调查气溶胶成分和吸湿性对气溶胶指数估算的影响，通过观测和模拟来估计和减少由于使用这种关系而产生的不确定性。智能优点：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将有助于更深入地了解气溶胶间接效应背后的机制。考虑这些影响将有助于查明和量化传统方法估计气溶胶间接影响的偏差，使用地面或卫星测量AOD作为CCN的替代指标，以便更好地估计不同气象条件下不同类型气溶胶的气溶胶指数。通过考虑动力和热力学条件的影响，模式有助于解释云微物理性质对气溶胶成分/吸湿性的响应机制。主要影响：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，气溶胶间接作用的机制将得到更好的理解。这将有助于缩小政府间气候变化专门委员会(气专委)报告所确定的大范围不确定性。这项研究将为本科生和研究生以及博士后提供测量气溶胶、提取云特性、数据分析和建模的跨学科培训机会。这项研究将对云物理、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.