AGS-FIRP Track 2: Untangling the physics of aerosol activation, turbulence, and drizzle formation: Pi Chamber experiments and numerical simulation
AGS-FIRP 轨道 2:理清气溶胶活化、湍流和毛毛雨形成的物理原理:Pi 室实验和数值模拟
基本信息
- 批准号:2227012
- 负责人:
- 金额:$ 37.29万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Clouds in the atmosphere have a very large effect on weather and climate through effects on solar radiation and the water cycle, and yet many aspects of their formation, lifetime, and behavior remain unclear due to the complexity of these systems. From space, one can see large swaths of clouds spanning hundreds or thousands of kilometers, while at the same time these clouds are composed of droplets and aerosols whose size are less than a few dozen micrometers. This immense gap between the scales of a single, sub-micron aerosol, upon which a cloud droplet grows, to a cloud street that one can see from space, highlights the challenge of developing numerical models that are able to accurately predict the key properties of clouds that govern Earth’s climate and weather. This project is aimed at focusing on the small end of this size spectrum: how do different types of aerosols cause different types of cloud droplets, all while the background air is a churning mixture of moisture? Certain types of aerosols, such as sea salt, act to condense water more easily than others, such as mineral dust. Understanding how turbulence, aerosol type/size, and cloud droplets interact is crucial for representing the growth of clouds in various pollution conditions, and the goals of this project are to provide the small-scale knowledge and model components which will ultimately lead to more accurate weather and climate predictions. The project has two complementary components for studying multiple questions pertaining to cloud-aerosol-turbulence interaction. The first is using extremely high-resolution numerical simulations capable of resolving the turbulent flow, as well as the motion and behavior of large numbers of individual aerosols and droplets. This Lagrangian framework belongs to a new class of cloud models which are ideally suited for studying the intricate details of droplet growth and its coupling with a turbulent flow. To complement these simulations, corresponding experiments at Michigan Technological University’s “Pi Chamber” will be conducted. This chamber is an experimental facility which can create highly controlled clouds that can be monitored and measured in multiple configurations --- including with multiple types/sizes of aerosols. This experimental/numerical combination will target questions related to (1) aerosol hygroscopicity, (2) supersaturation fluctuations, (3) droplet settling/deposition, and (4) drizzle formation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
大气中的云通过对太阳辐射和水循环的影响对天气和气候产生了非常大的影响,但由于这些系统的复杂性,它们的形成、寿命和行为的许多方面仍然不清楚。从太空中可以看到绵延数百或数千公里的大片云层,同时这些云层由不到几十微米的水滴和气溶胶组成。从生长云滴的单个亚微米气溶胶到从太空中可以看到的云街之间的巨大差距,突显了开发能够准确预测支配地球气候和天气的云的关键属性的数值模型的挑战。这个项目的目标是关注这种尺度光谱的一小部分:不同类型的气溶胶如何导致不同类型的云滴,而背景空气是一种搅动的湿气混合物?某些类型的气溶胶,如海盐,比其他类型的气溶胶更容易凝结水,如矿物粉尘。了解湍流、气溶胶类型/大小和云滴如何相互作用对于表示各种污染条件下云的增长至关重要,该项目的目标是提供小规模知识和模式组件,最终将导致更准确的天气和气候预测。该项目有两个互补的组成部分,用于研究与云-气溶胶-湍流相互作用有关的多个问题。第一种是使用极高分辨率的数值模拟,能够解决湍流,以及大量单个气溶胶和液滴的运动和行为。这种拉格朗日框架属于一类新的云模型,它非常适合于研究液滴生长及其与湍流耦合的复杂细节。为了补充这些模拟,将在密歇根理工大学的“圆周率实验室”进行相应的实验。这个小室是一个实验设备,可以创造高度受控的云,可以多种配置进行监测和测量-包括多种类型/大小的气溶胶。这一实验/数值组合将针对与(1)气溶胶吸湿性、(2)过饱和度波动、(3)液滴沉降/沉积和(4)毛毛雨形成相关的问题。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Stochastic model for the residence time of solid particles in turbulent Rayleigh-Bénard flow
瑞利-伯纳德湍流中固体颗粒停留时间的随机模型
- DOI:10.1103/physrevfluids.8.024307
- 发表时间:2023
- 期刊:
- 影响因子:2.7
- 作者:Denzel, Colin J.;Bragg, Andrew D.;Richter, David H.
- 通讯作者:Richter, David H.
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David Richter其他文献
The effect of face-to-face interviewing on personality measurement
- DOI:
10.1016/j.jrp.2016.05.006 - 发表时间:
2016-08-01 - 期刊:
- 影响因子:
- 作者:
Luisa Hilgert;Martin Kroh;David Richter - 通讯作者:
David Richter
Adversarial testing of global neuronal workspace and integrated information theories of consciousness
全球神经元工作空间和意识综合信息理论的对抗性测试
- DOI:
10.1038/s41586-025-08888-1 - 发表时间:
2025-04-30 - 期刊:
- 影响因子:48.500
- 作者:
Oscar Ferrante;Urszula Gorska-Klimowska;Simon Henin;Rony Hirschhorn;Aya Khalaf;Alex Lepauvre;Ling Liu;David Richter;Yamil Vidal;Niccolò Bonacchi;Tanya Brown;Praveen Sripad;Marcelo Armendariz;Katarina Bendtz;Tara Ghafari;Dorottya Hetenyi;Jay Jeschke;Csaba Kozma;David R. Mazumder;Stephanie Montenegro;Alia Seedat;Abdelrahman Sharafeldin;Shujun Yang;Sylvain Baillet;David J. Chalmers;Radoslaw M. Cichy;Francis Fallon;Theofanis I. Panagiotaropoulos;Hal Blumenfeld;Floris P. de Lange;Sasha Devore;Ole Jensen;Gabriel Kreiman;Huan Luo;Melanie Boly;Stanislas Dehaene;Christof Koch;Giulio Tononi;Michael Pitts;Liad Mudrik;Lucia Melloni - 通讯作者:
Lucia Melloni
Conceptual Associations Generate Sensory Predictions
概念关联产生感官预测
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:5.3
- 作者:
Chuyao Yan;F. D. de Lange;David Richter - 通讯作者:
David Richter
Effects of settling on inertial particle slip velocity statistics in wall bounded flows
沉降对壁界流中惯性颗粒滑移速度统计的影响
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Andrew P. Grace;David Richter;Tim Berk;Andrew D. Bragg - 通讯作者:
Andrew D. Bragg
Das Sozio-Oekonomische Panel als Datenbasis für die Arbeits- und Organisationspsychologie
社会经济小组作为劳动和组织心理学的数据基础
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Marco Giesselmann;Mila Staneva;J. Schupp;David Richter - 通讯作者:
David Richter
David Richter的其他文献
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{{ truncateString('David Richter', 18)}}的其他基金
Collaborative Research: Droplet transport in the vicinity of breaking waves: Experiments and simulations
合作研究:破碎波附近的液滴传输:实验和模拟
- 批准号:
1829515 - 财政年份:2018
- 资助金额:
$ 37.29万 - 项目类别:
Standard Grant
Latent and Sensible Heat Flux at the Spray-Laden Air-Sea Interface
充满喷雾的空气-海洋界面处的潜热和显热通量
- 批准号:
1429921 - 财政年份:2015
- 资助金额:
$ 37.29万 - 项目类别:
Continuing Grant
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