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

利用改进的气溶胶光学厚度 (AOT) 和云凝结核 (CCN) 关系以及气溶胶成分来研究气溶胶对云微物理的影响

• 批准号: 1534670
• 负责人: Zhanqing Li
• 金额: $ 50万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1534670&HistoricalAwards=false
• 关键词: Using; Improved; Aerosol; Optical; Thickness

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.

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最终取决于云性质对云凝结核（CCN）变化的响应，因此了解CCN是理解ACI的关键。由于大规模连续观测CCN的不可行性，更容易测量的气溶胶光学量，如气溶胶光学深度（AOD），在ACI研究中被广泛用作CCN的代理，尽管这两种性质代表了气溶胶的不同方面。另一方面，这两种性质受气溶胶粒径分布和化学成分的影响，有一定的联系。在由美国国家科学基金会资助的第一阶段，研究AOD与CCN之间的关系，重点研究气溶胶物理性质和环境气象的影响。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最终取决于云性质对云凝结核（CCN）变化的响应，因此了解CCN是理解ACI的关键。由于大规模连续观测CCN的不可行性，更容易测量的气溶胶光学量，如气溶胶光学深度（AOD），在ACI研究中被广泛用作CCN的代理，尽管这两种性质代表了气溶胶的不同方面。另一方面，这两种性质受气溶胶粒径分布和化学成分的影响，有一定的联系。在由美国国家科学基金会资助的第一阶段，研究AOD与CCN之间的关系，重点研究气溶胶物理性质和环境气象的影响。这项研究将继续进行，但重点是调查气溶胶成分和吸湿性对ACI估计的影响，通过观测和建模来估计和减少由于使用这种关系而产生的不确定性。学术价值:1。对云微物理特性对气溶胶光学、化学和吸湿特性的响应的全面分析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识别和量化传统方法在气溶胶间接影响估计中的偏差，这种方法使用地面或卫星测量的AOD作为CCN的代理，从而更好地估计不同气象条件下不同类型气溶胶的ACI。通过计算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提高，气溶胶间接效应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（IPCC）报告所确定的大量不确定性。该研究将为本科生、研究生和博士后提供跨学科的培训机会，包括测量气溶胶、检索云特性、数据分析和建模。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。