Collaborative Research: Role of Cloud Albedo and Land-Atmosphere Interactions on Continental Tropical Climates
合作研究:云反照率和陆地-大气相互作用对大陆热带气候的作用
基本信息
- 批准号:1734164
- 负责人:
- 金额:$ 26.11万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-09-01 至 2021-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The land surface interacts strongly with the atmosphere above it, as the atmosphere supplies water to the surface in the form of rain and energy, including sunlight and downwelling infrared radiation. The land in turn affects the atmosphere by providing water vapor through evaporation and transpiration, giving off sensible heat and upwelling infrared radiation, and blocking the wind with trees and other obstacles, among other effects. Land-atmosphere interactions are thus an important topic in climate science, and a key goal research in this area is to understand the feedback mechanisms through which land-surface processes influence the atmosphere in ways that produce further effects on the land and vice versa. Much of the work in this area is focused on precipitation and soil moisture, particularly the extent to which evaporation serves as a source for later precipitation which further controls the amount and distribution of soil moisture.Here the PIs go beyond soil moisture-precipitation feedback to consider mechanisms that link land surface characteristics to cloudiness and the subsequent shading effect of cloud cover on the surface. One of these is a feedback in which sunlight falling on moist soil produces evaporation, which leads to the formation of clouds or fog, which shades the soil and limits further evaporation. Previous work by the PIs suggests that this negative feedback mechanism plays an important role in limiting evaporation in the Amazon during the rainy season. An additional question pursued in this research is the extent to which small-scale differences in surface cover, such as exist between adjacent forested and deforested patches of the Amazon, produce differences in cloudiness as near-surface air converges into and rises above drier and hence warmer patches.A key concern in studying such effects is that climate models have limited ability to represent them. Climate models rely on parameterizations to represent clouds and precipitation, and parameterizations have difficulty capturing the diurnal cycle of cloudiness. This is a severe limitation for studying the effect of cloud shading on evaporation, as the effect depends on whether clouds develop when the sun is high in the sky or near or below the horizon. Clouds simulated in climate models are also unlikely to respond to small-scales patchiness in surface cover, as models only represent aggregate cloud cover and surface conditions over grid boxes which extend at least tens of kilometers in each direction.The PIs use two separate modeling strategies to circumvent these difficulties, the first of which is a limited domain cloud resolving model (the Weather Research and Forecasting model, or WRF) constrained to relax back to a specified background temperature profile. This configuration is based on the weak temperature gradient (WTG) approximation, which assumes that temperatures well above the surface are horizontally uniform due to the weakness of the Coriolis force over tropical regions such as the Amazon. The WRF-WTG framework allows for very high resolution simulations (grid spacing of one or two kilometers) over limited domains on which the processes of interest can be represented with some realism. The second approach uses a technique known as superparameterization, in which a somewhat simplified cloud resolving model is placed in each grid column of a climate model, creating a hybrid model which represents both the cloud scale and the large scale (see AGS-0425247).Using these two modeling strategies the PIs perform a number of model experiments to determine the effects of the proposed mechanisms, including experiments in which the land surface turbulent heat flux is prescribed and simulations in which the diurnal cycle of land surface fluxes is reduced by imposing a very large soil heat capacity. The model experiments are complemented with analysis of relevant observations from a number of observing stations in the Amazon, some in deforested regions and some representing the transition from wetter to drier conditions.The research has societal value as well as scientific interest, as it seeks to improve understanding of climate variability and change in the Amazon, a region of high biodiversity which plays a substantial role in the global water and carbon cycles. In addition, a variety of education and outreach activities are organized around the work, including work with high school students in Harlem, work with a STEM center housed at Cal State Los Angeles, and an undergraduate recruitment effort through the Research in Science and Engineering (RiSE) program at Rutgers. The project also provides support and training for a graduate student and a postdoc.
陆地表面与其上方的大气强烈相互作用,因为大气以雨水和能量的形式向地表提供水,包括阳光和向下流动的红外辐射。 土地反过来又影响大气层,通过蒸发和蒸腾提供水蒸气,释放显热和上升的红外辐射,并用树木和其他障碍物阻挡风,等等。因此,陆气相互作用是气候科学中的一个重要课题,该领域的一个关键目标研究是了解陆表过程影响大气的反馈机制,从而对土地产生进一步的影响,反之亦然。这一领域的大部分工作都集中在降水和土壤水分上,特别是蒸发作为后期降水来源的程度,后者进一步控制了土壤水分的数量和分布。在这里,PI超越了土壤水分-降水反馈,考虑了将陆面特征与云量联系起来的机制,以及随后的云量对地表的遮蔽效应。其中之一是反馈,阳光照射在潮湿的土壤上会产生蒸发,从而导致云或雾的形成,从而遮蔽土壤并限制进一步蒸发。PI以前的工作表明,这种负反馈机制在雨季限制亚马逊地区的蒸发方面发挥了重要作用。这项研究中的另一个问题是,当近地表空气汇聚并上升到干燥和温暖的区域时,地表覆盖的小尺度差异(例如亚马逊森林和森林砍伐区域之间存在的差异)在多大程度上会产生云量的差异。研究这种影响的一个关键问题是,气候模式对它们的表现能力有限。气候模式依赖于参数化来表示云和降水,而参数化很难捕捉云量的日周期。这对于研究云遮蔽对蒸发的影响是一个严重的限制,因为这种影响取决于云是在太阳在天空高处还是在地平线附近或下方形成的。气候模式中模拟的云也不太可能对小尺度的斑块状地表覆盖做出响应,因为模式只代表在每个方向上延伸至少数十公里的网格框上的总云量和地表条件。PI使用两种单独的模拟策略来克服这些困难,第一种是有限域云解析模式(天气研究和预报模型,或WRF)约束放松到指定的背景温度分布。这种配置基于弱温度梯度(WTG)近似,该近似假设由于热带地区(如亚马逊)的科里奥利力较弱,地表以上的温度水平均匀。WRF-WTG框架允许在有限的域上进行非常高分辨率的模拟(网格间距为一公里或两公里),在这些域上,感兴趣的过程可以以一定的现实主义来表示。第二种方法使用一种称为超参数化的技术,在这种技术中,在气候模式的每个网格列中放置一个稍微简化的云解析模式,创建一个既代表云尺度又代表大尺度的混合模式(参见AGS-0425247)。使用这两种建模策略,PI执行许多模型实验以确定所提出的机制的效果,包括实验中,陆面湍流热通量规定和模拟中,陆面通量的昼夜循环减少施加一个非常大的土壤热容量。模型实验还辅以对亚马逊地区一些观测站的相关观测结果的分析,这些观测站有些位于森林砍伐地区,有些代表了从潮湿到干燥的过渡条件。这项研究具有社会价值和科学意义,因为它试图提高对亚马逊地区气候变异和变化的理解,这是一个高度生物多样性的地区,在全球水和碳循环中发挥着重要作用。此外,各种教育和外展活动围绕工作组织,包括与高中学生在哈莱姆的工作,与设在加州州立大学洛杉矶的STEM中心的工作,并通过在罗格斯大学的科学与工程研究(RISE)计划的本科生招聘工作。该项目还为一名研究生和一名博士后提供支持和培训。
项目成果
期刊论文数量(11)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Regional MJO Modulation of Northwest Pacific Tropical Cyclones Driven by Multiple Transient Controls
- DOI:10.1029/2020gl087148
- 发表时间:2020-06
- 期刊:
- 影响因子:5.2
- 作者:M. D. Fowler;Michael S. Pritchard
- 通讯作者:M. D. Fowler;Michael S. Pritchard
The effect of plant physiological responses to rising CO2 on global streamflow
- DOI:10.1038/s41558-019-0602-x
- 发表时间:2019-11-01
- 期刊:
- 影响因子:30.7
- 作者:Fowler, Megan D.;Kooperman, Gabriel J.;Pritchard, Michael S.
- 通讯作者:Pritchard, Michael S.
Generative Modeling of Atmospheric Convection
- DOI:10.1145/3429309.3429324
- 发表时间:2020-07
- 期刊:
- 影响因子:0
- 作者:G. Mooers;Jens Tuyls;S. Mandt;M. Pritchard;T. Beucler
- 通讯作者:G. Mooers;Jens Tuyls;S. Mandt;M. Pritchard;T. Beucler
Could Machine Learning Break the Convection Parameterization Deadlock?
- DOI:10.1029/2018gl078202
- 发表时间:2018-06-16
- 期刊:
- 影响因子:5.2
- 作者:Gentine, P.;Pritchard, M.;Yacalis, G.
- 通讯作者:Yacalis, G.
The Ongoing Need for High-Resolution Regional Climate Models: Process Understanding and Stakeholder Information
- DOI:10.1175/bams-d-19-0113.1
- 发表时间:2020-05-01
- 期刊:
- 影响因子:8
- 作者:Gutowski, W. J., Jr.;Ullrich, P. A.;Zarzycki, C.
- 通讯作者:Zarzycki, C.
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Michael Pritchard其他文献
Applying the service profit chain to analyse retail performance
应用服务利润链分析零售绩效
- DOI:
10.1108/09564230510613997 - 发表时间:
2005 - 期刊:
- 影响因子:0
- 作者:
Michael Pritchard;R. Silvestro - 通讯作者:
R. Silvestro
Electromyography Signal-Based Gesture Recognition for Human-Machine Interaction in Real-Time Through Model Calibration
基于肌电信号的手势识别通过模型校准实现实时人机交互
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Christos Dolopikos;Michael Pritchard;Jordan J. Bird;D. Faria - 通讯作者:
D. Faria
Michael Pritchard的其他文献
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{{ truncateString('Michael Pritchard', 18)}}的其他基金
Collaborative Research: Advancing Understanding of Aerosol-Cloud Feedback Using the World's First Global Climate Model with Explicit Boundary Layer Turbulence
合作研究:利用世界上第一个具有明确边界层湍流的全球气候模型增进对气溶胶云反馈的理解
- 批准号:
1912134 - 财政年份:2019
- 资助金额:
$ 26.11万 - 项目类别:
Standard Grant
Collaborative Research: HDR Elements: Software for a new machine learning based parameterization of moist convection for improved climate and weather prediction using deep learning
合作研究:HDR Elements:基于新机器学习的湿对流参数化软件,利用深度学习改进气候和天气预报
- 批准号:
1835863 - 财政年份:2018
- 资助金额:
$ 26.11万 - 项目类别:
Standard Grant
Collaborative Research: EaSM-3: Understanding the Development of Precipitation Biases in CESM and the Superparameterized CESM on Seasonal to Decadal Timescales
合作研究:EaSM-3:了解CESM和超参数化CESM在季节到十年时间尺度上的降水偏差的发展
- 批准号:
1419518 - 财政年份:2014
- 资助金额:
$ 26.11万 - 项目类别:
Standard Grant
SDEST: Teaching Research Ethics - An Institutional Change Model
SDEST:教学研究伦理——制度变革模型
- 批准号:
0115480 - 财政年份:2001
- 资助金额:
$ 26.11万 - 项目类别:
Continuing Grant
Infusion of Ethics and Values in Pre-College Science Teaching
大学前科学教学中伦理和价值观的注入
- 批准号:
9601546 - 财政年份:1997
- 资助金额:
$ 26.11万 - 项目类别:
Standard Grant
Teaching Engineering Ethics: A Case Study Approach
工程伦理教学:案例研究方法
- 批准号:
8820837 - 财政年份:1989
- 资助金额:
$ 26.11万 - 项目类别:
Standard Grant
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Research on Quantum Field Theory without a Lagrangian Description
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Cell Research
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Cell Research (细胞研究)
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- 批准号:10774081
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