CAREER: Departure from Monin-Obukhov Similarity Theory (MOST) using high-resolution turbulence models
职业生涯:使用高分辨率湍流模型偏离 Monin-Obukhov 相似理论 (MOST)
基本信息
- 批准号:1552304
- 负责人:
- 金额:$ 43.54万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-03-01 至 2022-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Turbulence controls the rate at which heat, moisture, air, and passive chemical tracers such as CO2 flow between the land and the atmosphere. Accurate model representation of such turbulent fluxes from the surface is essential for precise hydrologic, weather, and climate predictions. Our current model representation of turbulent fluxes assumes that most eddies transport can be explained by local observations and parameters in models. Nonetheless variability in the horizontal (e.g. due to variability in the surface characteristics) and in the vertical (due to eddies that span an unusually large vertical extend) directions can invalidate these assumptions. In this proposal we will test the latter effect using a combination of high-resolution turbulence models and observations. Our main objective is to better account for the largest ? most efficient ? eddies in our representation of turbulent exchange at the surface. This should ultimately improve the way we measure surface fluxes and model them. One flux of special interest is evaporation (the flux of moisture), which impacts hydrological forecasts (such as streamflow) along with weather and climate predictions. Along with this research activity, one of the main educational objectives of this proposal is to provide science exposure and encourage under-represented groups in Harlem, NY to choose scientific careers and education through science demonstrations and high-school internships.Most current formulations of the surface turbulent transport laws are based on Monin-Obukhov Similarity Theory (MOST), which is based on local surface layer scaling. This theory has been shown to be deficient in recent years. One of the main causes of this deficiency is due to the presence of coherent turbulent structures, which transport turbulent properties over large distances from the top of the boundary layer down to the surface. These structures cannot readily be observed by time-averaging eddy-covariance technique and may be one of the main reasons of non-closure of the in situ surface energy budget, which are used to validate our land-surface models. To address these issues, the research objectives of this proposal are to: i) Investigate the role of non-local transport related to the entrainment at the boundary layer top and its interaction with surface turbulence using Direct Numerical Simulations (DNS) and Large-Eddy Simulations (LES),ii) Derive new surface turbulent laws and profile similarity accounting for the effect of non-local transport, iii) Define large-eddy corrections for eddy-covariance observations of surface turbulent fluxes. iv) Evaluate the impact of these new formulations in a coupled land-surface and weather model.Consistent with this research activity, the educational objectives of the proposal are to: a) develop international student exchange programs, b) encourage and advise under-represented groups to participate in STEM research and c) develop classes (e.g. land-atmosphere interactions and turbulence) with a broad vision of the problem geared toward multiple scientific communities to facilitate cross-disciplinary collaborations and work.
湍流控制着热,水分,空气和被动化学示踪剂(例如二氧化碳和大气之间的二氧化碳流动)的速度。从表面进行此类湍流的准确模型表示对于精确的水文,天气和气候预测至关重要。我们当前的湍流模型表示假定,大多数涡流传输都可以通过模型中的局部观测和参数来解释。但是,水平的变异性(例如,由于表面特征的变异性)和垂直(由于跨越异常大的垂直扩展的涡流引起的)方向可能会使这些假设无效。在此提案中,我们将使用高分辨率湍流模型和观测值的组合来测试后一种效果。我们的主要目标是更好地说明最大的?效率最高?在表面湍流交换的表示中涡流。这最终应该改善我们测量表面通量并建模的方式。特殊关注的一种通量是蒸发(水分的通量),它影响了水文预测(例如水流)以及天气和气候预测。与这项研究活动一起,该提案的主要教育目标之一是提供科学曝光,并鼓励纽约州哈林市的人数不足的群体通过科学演示和高中实习来选择科学职业和教育。表面湍流运输法的最新表述基于Monin-Obukhov相似性理论(大多数),基于本地表面层的标准。近年来,该理论已被证明是不足的。这种缺陷的主要原因之一是由于存在相干的湍流结构,该结构在边界层的顶部向下传输到表面上的湍流特性。这些结构无法通过时间平衡的涡流技术来轻松观察,并且可能是原位表面能量预算不关闭的主要原因之一,这些预算用于验证我们的土地表面模型。 To address these issues, the research objectives of this proposal are to: i) Investigate the role of non-local transport related to the entrainment at the boundary layer top and its interaction with surface turbulence using Direct Numerical Simulations (DNS) and Large-Eddy Simulations (LES),ii) Derive new surface turbulent laws and profile similarity accounting for the effect of non-local transport, iii) Define large-eddy corrections for eddy-covariance observations of表面湍流通量。 iv)在耦合的土地表面和天气模型中评估这些新配方的影响。与这项研究活动相吻合,该建议的教育目标是:a)制定国际学生交流计划,b)b)鼓励和建议较低的群体鼓励参与STEM研究和c的跨度互动(例如,与土地互动相互作用)(e.g.土地互动)(e.g.土地互动)(e。跨学科的合作和工作。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Pierre Gentine其他文献
Simulating the Air Quality Impact of Prescribed Fires Using a Graph Neural Network-Based PM2.5 Emissions Forecasting System
使用基于图神经网络的 PM2.5 排放预测系统模拟规定火灾的空气质量影响
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Kyleen Liao;Jatan Buch;Kara Lamb;Pierre Gentine - 通讯作者:
Pierre Gentine
Non-Linear Dimensionality Reduction with a Variational Autoencoder Decoder to Understand Convective Processes in Climate Models
使用变分自动编码器解码器进行非线性降维以了解气候模型中的对流过程
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
G. Behrens;T. Beucler;Pierre Gentine;Fernando;Iglesias;Michael S. Pritchard;Veronika Eyring - 通讯作者:
Veronika Eyring
An observation-driven optimization method for continuous estimation of evaporative fraction over large heterogeneous areas
一种观测驱动的优化方法,用于连续估计大面积异质区域的蒸发分数
- DOI:
10.1016/j.rse.2020.111887 - 发表时间:
2020-09 - 期刊:
- 影响因子:13.5
- 作者:
Wenbin Zhu;Shaofeng Jia;Upmanu Lall;Yu Cheng;Pierre Gentine - 通讯作者:
Pierre Gentine
Peak growing season patterns and climate extremes-driven responses of gross primary production estimated by satellite and process based models over North America
通过卫星和基于过程的模型估算的北美地区初级生产总值的高峰生长季节模式和极端气候驱动的响应
- DOI:
10.1016/j.agrformet.2020.108292 - 发表时间:
2021-03 - 期刊:
- 影响因子:6.2
- 作者:
Wei He;Weimin Ju;Fei Jiang;Nicholas Parazoo;Pierre Gentine;Wu Xiaocui;Zhang Chunhua;Zhu Jiawen;Nicolas Viovy;Atul K. Jain;Stephen Sitch;Pierre Friedlingstein - 通讯作者:
Pierre Friedlingstein
Uncertainties Caused by Resistances in Evapotranspiration Estimation Using High-Density Eddy Covariance Measurements
使用高密度涡协方差测量估计蒸散量时阻力引起的不确定性
- DOI:
10.1175/jhm-d-19-0191.1 - 发表时间:
2020-05 - 期刊:
- 影响因子:3.8
- 作者:
Wen Li Zhao;Guo Yu Qiu;Yu Jiu Xiong;Kyaw Tha Paw U;Pierre Gentine;Bao Yu Chen - 通讯作者:
Bao Yu Chen
Pierre Gentine的其他文献
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{{ truncateString('Pierre Gentine', 18)}}的其他基金
STC: Center for Learning the Earth with Artificial Intelligence and Physics (LEAP)
STC:利用人工智能和物理学习地球中心 (LEAP)
- 批准号:
2019625 - 财政年份:2021
- 资助金额:
$ 43.54万 - 项目类别:
Cooperative Agreement
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:
1835769 - 财政年份:2018
- 资助金额:
$ 43.54万 - 项目类别:
Standard Grant
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 - 财政年份:2017
- 资助金额:
$ 43.54万 - 项目类别:
Standard Grant
Collaborative Research: Dynamics of Unsaturated Downdrafts, Cold Pools, and Their Roles in Convective Initiation and Organization
合作研究:不饱和下降气流、冷池的动力学及其在对流引发和组织中的作用
- 批准号:
1649770 - 财政年份:2017
- 资助金额:
$ 43.54万 - 项目类别:
Continuing Grant
Summer School in Land-atmosphere Interactions
陆地-大气相互作用暑期学校
- 批准号:
1522174 - 财政年份:2015
- 资助金额:
$ 43.54万 - 项目类别:
Standard Grant
Collaborative Research: Quantifying the impacts of atmospheric and land surface heterogeneity and scale on soil moisture-precipitation feedbacks
合作研究:量化大气和地表异质性和规模对土壤湿度-降水反馈的影响
- 批准号:
1035843 - 财政年份:2011
- 资助金额:
$ 43.54万 - 项目类别:
Standard Grant
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