Aerosol-Cloud Interactions - A Directed Programme to Reduce Uncertainty in Forcing through a Targeted Laboratory and Modelling Programme

气溶胶-云相互作用 - 通过有针对性的实验室和建模程序减少强迫不确定性的定向程序

• 批准号: NE/I020121/1
• 负责人: Gordon McFiggans
• 金额: $ 110.1万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI020121%2F1
• 关键词: Aerosol; Cloud; Interactions; Directed; Programme

Aerosol particles act as sites for cloud droplet and ice particle formation. Cloud properties can be perturbed through the addition of aerosol particles into the atmosphere from anthropogenic and natural processes. This addition influences cloud microphysical properties, and subsequently affects cloud dynamics and thermodynamics, and the way the cloud interacts with radiation. The Earth's radiation budget is very greatly affected by clouds, and human-induced changes to the particle loading affecting them, known as indirect effects, are large and highly uncertain. A large part of this uncertainty is the result of poor knowledge of the fundamental aerosol and cloud properties and processes, leading to their poor representation in models. A programme of research is proposed here to i) directly investigate these processes in the laboratory, ii) evaluate the sensitivity of climate relevant parameters to the studied processes, iii) interpret the laboratory studies with detailed model investigations and iv) to incorporate and test new descriptions of the studied processes in cloud-scale and, where possible, global scale models. The programme will thereby reduce the uncertainty in estimates of radiative forcing and climate feedbacks relating to aerosol and cloud processes. The studies are split into those affecting warm clouds (those containing only liquid droplets) and those affecting clouds containing ice particles. The programme brings together an interdisciplinary team of researchers with expertise in 'warm' and 'cold' cloud and aerosol processes combining laboratory and multiscale modelling activities to deliver the improved predictive capability. The 'warm' laboratory work focuses on two major aspects i) the rate at which water is taken up by growing aerosol particles as they become cloud droplets (or 'activate) and ii) the ability of aerosol particles of various compositions to act as seeds for cloud droplets. These studies use a number of techniques including single particle optical levitation and investigations in a large photochemical chamber coupled to a large number of chemical and physical probes of ensembles of particles formed in simulated atmospheric chemical processes. The 'cold' work uses a similar coupling of a large, well-instrumented cloud chamber experiments and single particle levitation studies. The chambers used in both aspects will be coupled to investigate the impacts of aerosol transformation conditions on warm and cold cloud formation, using the instrumental payload from both chambers. A range of detailed models will be used to explicitly describe the processes by which aerosol particles interact with increasing relative humidity and reducing temperature to form cloud droplet and ice crystals and to their properties. The processes and properties will be represented in dynamical frameworks to predict the interactions between aerosols and clouds and their radiative effects at cloud resolving scales and radiative forcing of some of the investigated properties on global radiative forcing and feedbacks. The sensitivity of climate relevant parameters to the fundamental parameters investigated in the laboratory programme and their improved quantification will be evaluated using a simplified model 'emulator'.

气溶胶粒子是形成云滴和冰粒子的场所。由于人为和自然过程向大气中加入气溶胶粒子，云的性质会受到干扰。这种添加影响云的微物理特性，并随后影响云动力学和热力学，以及云与辐射相互作用的方式。地球的辐射收支很大程度上受到云的影响，而人类引起的粒子负荷变化对云的影响被称为间接影响，这种变化很大，而且高度不确定。这种不确定性在很大程度上是由于对气溶胶和云的基本特性和过程缺乏了解，导致它们在模式中表现不佳。在此提出一个研究方案：1)在实验室中直接调查这些过程；2)评估气候相关参数对所研究过程的敏感性；3)用详细的模式调查来解释实验室研究；4)在云尺度和可能的情况下，在全球尺度模式中合并和测试对所研究过程的新描述。因此，该方案将减少与气溶胶和云过程有关的辐射强迫和气候反馈估计的不确定性。这些研究分为影响暖云（只包含液滴）的研究和影响含有冰粒的云的研究。该计划汇集了一个跨学科的研究团队，他们具有“暖”和“冷”云和气溶胶过程的专业知识，结合实验室和多尺度建模活动，以提供改进的预测能力。“温暖”的实验室工作集中在两个主要方面：1)成长中的气溶胶颗粒在成为云滴（或“激活”）时吸收水分的速度；2)不同成分的气溶胶颗粒作为云滴种子的能力。这些研究使用了许多技术，包括单粒子光学悬浮和在大型光化学室中对模拟大气化学过程中形成的粒子群进行大量化学和物理探针的研究。“冷”工作使用了类似的大型，设备齐全的云室实验和单粒子悬浮研究的耦合。在这两个方面使用的腔室将被耦合，以研究气溶胶转化条件对冷热云形成的影响，使用两个腔室的仪器有效载荷。一系列详细的模型将用于明确地描述气溶胶粒子与增加的相对湿度和降低的温度相互作用形成云滴和冰晶的过程及其性质。这些过程和性质将在动力学框架中表示，以预测气溶胶和云之间的相互作用及其在云解析尺度上的辐射效应，以及所研究的一些性质对全球辐射强迫和反馈的辐射强迫。气候相关参数对实验室项目中研究的基本参数的敏感性及其改进的量化将使用简化的模型“模拟器”进行评估。

项目成果

Size-resolved simulations of the aerosol inorganic composition with the new hybrid dissolution solver HyDiS-1.0: description, evaluation and first global modelling results

• DOI: 10.5194/gmd-9-3875-2016
• 发表时间: 2016-11-01
• 期刊: GEOSCIENTIFIC MODEL DEVELOPMENT
• 影响因子: 5.1
• 作者: Benduhn, Francois;Mann, Graham W.;Carslaw, Kenneth S.
• 通讯作者: Carslaw, Kenneth S.

A parameterisation for the activation of cloud drops including the effects of semi-volatile organics

云滴激活的参数化，包括半挥发性有机物的影响

• DOI: 10.5194/acp-14-2289-2014
• 发表时间: 2014
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: Connolly P

Factors determining the most efficient spray distribution for marine cloud brightening

• DOI: 10.1098/rsta.2014.0056
• 发表时间: 2014-12-28
• 期刊: PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
• 影响因子: 5
• 作者: Connolly, P. J.;McFiggans, G. B.;Tsiamis, A.
• 通讯作者: Tsiamis, A.

Critical assessment of liquid density estimation methods for multifunctional organic compounds and their use in atmospheric science.

• DOI: 10.1021/jp304547r
• 发表时间: 2013-04
• 期刊: The journal of physical chemistry. A
• 作者: M. Barley;D. Topping;G. Mcfiggans

Using in situ estimates of ice water content, volume extinction coefficient, and the total solar optical depth obtained during the tropical ACTIVE campaign to test an ensemble model of cirrus ice crystals

利用热带 ACTIVE 活动期间获得的冰水含量、体积消光系数和总太阳光学深度的原位估计来测试卷云冰晶的集合模型

• DOI: 10.1002/qj.731
• 发表时间: 2011
• 期刊: Quarterly Journal of the Royal Meteorological Society
• 影响因子: 8.9
• 作者: Baran A