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

• 批准号: 1734156
• 负责人: Pierre Gentine
• 金额: $ 42.04万
• 依托单位: Columbia University
• 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 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734156&HistoricalAwards=false
• 关键词: Collaborative; Research; Role; Cloud; Albedo

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相互作用强烈，因为大气以雨水和能量的形式向地表提供水，包括阳光和向下的红外辐射。反过来，土地通过蒸发和蒸腾作用提供水蒸气，释放感热和上涌的红外辐射，以及用树木和其他障碍物阻挡风等影响大气。因此，陆地-大气相互作用是气候科学的一个重要课题，该领域研究的一个关键目标是了解陆地表面过程影响大气的反馈机制，通过这种机制对陆地产生进一步的影响，反之亦然。这一领域的大部分工作集中在降水和土壤水分，特别是蒸发在多大程度上作为后期降水的来源，而后期降水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，考虑了将地表特征与云量以及随后的地表云层遮阳效应联系起来的机制。其中一种是反馈，阳光照射在潮湿的土壤上产生蒸发，从而导致云或雾的形成，云或雾遮蔽了土壤，限制了进一步的蒸发。pi先前的工作表明，这种负反馈机制在限制雨季亚马逊流域的蒸发方面起着重要作用。本研究所追求的另一个问题是，地表覆盖的小范围差异，例如亚马逊河附近森林和森林砍伐地区之间存在的小范围差异，在近地表空气聚集并上升到干燥和温暖的地区时，会在多大程度上产生云量差异。研究这种影响的一个关键问题是，气候模型表示它们的能力有限。气候模式依赖于参数化来表示云和降水，而参数化难以捕获云的日循环。这对研究云层遮阳对蒸发的影响是一个严重的限制，因为这种影响取决于云层是在太阳处于高空还是接近或低于地平线时形成的。在气候模式中模拟的云也不太可能对地表覆盖的小尺度斑块做出反应，因为模式只代表在每个方向上至少延伸数十公里的网格盒上的总云量和地表条件。pi使用两种独立的建模策略来规避这些困难，其中第一种是有限域云解析模型（天气研究和预报模型，或WRF），该模型被限制为放松到指定的背景温度剖面。这种配置基于弱温度梯度（WTG）近似，它假设由于科氏力在亚马逊河等热带地区的弱，地表以上的温度在水平方向上是均匀的。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性表示。第二种方法使用一种称为超参数化的技术，在气候模型的每个网格列中放置一个稍微简化的云解析模型，创建一个混合模型，该模型既代表云尺度，也代表大尺度（见AGS-0425247）。利用这两种模式策略，pi进行了许多模式实验，以确定所提出的机制的影响，包括规定陆地表面湍流热通量的实验和通过施加非常大的土壤热容来减少陆地表面通量日循环的模拟。模式试验还辅以对亚马逊地区若干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，有些则代表从湿润到干燥的过渡。这项研究具有社会价值和科学价值，因为它寻求提高对亚马逊地区气候变化和变化的理解，亚马逊是一个生物多样性高的地区，在全球水和碳循环中起着重要作用。此外，围绕这项工作还组织了各种教育和外展活动，包括与哈莱姆区的高中生合作，与加州州立大学洛杉矶分校的STEM中心合作，以及通过罗格斯大学科学与工程研究（RiSE）项目招募本科生。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

Probing the Response of Tropical Deep Convection to Aerosol Perturbations Using Idealized Cloud-Resolving Simulations with Parameterized Large-Scale Dynamics

• DOI: 10.1175/jas-d-18-0351.1
• 发表时间: 2019-09
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: U. Anber;Shuguang Wang;P. Gentine;M. Jensen