CAREER: Mechanistic Modeling of Turbulent Bubbly Flows in the Ocean Surface Boundary Layer

职业：海洋表面边界层湍流气泡流的机理建模

• 批准号: 1945502
• 负责人: Junhong Liang
• 金额: $ 47.22万
• 依托单位: Louisiana State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1945502&HistoricalAwards=false
• 关键词: CAREER; Mechanistic; Modeling; Turbulent; Bubbly

Oceanic bubbles play important roles in upper ocean dynamics and in air-sea gas exchange. This project will study their distribution near the ocean surface and their interaction with turbulence, and improve the representation in numerical models of their impact on the exchange of gases between the ocean and atmosphere. Randomly-distributed breaking waves and small- scale currents are two ubiquitous processes in the upper ocean. Their roles on bubble dynamics and bubble-mediated air-sea gas transfer have never been studied due likely to the challenges in observing and modeling of gas bubbles in those two dynamical processes. Utilizing state-of-the-art computer models that simulate the co-evolution of the two dynamical processes, gas bubbles, and dissolved gases based on first principles, this study will advance our fundamental understanding of bubble dynamics in the upper ocean and its coupling with upper ocean dynamics. It will also improve representation of bubble-mediated gas fluxes in computer models. This research improves our understanding of the earth system in terms of both upper ocean dynamics and ocean biogeochemical cycling. It will reduce uncertainties in the modeling and budget estimate of climatically and environmentally important soluble gases such as oxygen and carbon dioxide. It will also improve our ability to use dissolved gases such as oxygen, nitrogen and argon, whose dissolved concentrations are affected by bubbles, as tracers for biogeochemical processes. The anticipated results can also be applied to the understanding and prediction of buoyant marine pollutants including spilled oil and marine plastics. Therefore, the study will improve our capability to predict marine environment and climatic changes, and will provide better scientific basis for decision makers in politics and industry on a range of issues including climate, environment, fisheries, energy and marine pollution mitigation. The educational component of the CAREER project includes developing a two-day mini-workshop for K-12 teachers, and creating an interactive webpage for hand-on ocean modelling activities that will be used in a summer camp and a general education class for non-STEM students that the PI has been teaching. The purposes of the educational activities are to attract local middle and high school students to the field of oceanography, to raise the awareness of the importance of the ocean among students and the general public, and to further enrich the curriculum for physical oceanography at LSU.The primary research objectives of this project are to better understand the distribution of gas bubbles and the coupling between bubbles and oceanic turbulence in the ocean surface boundary layer, and to more accurately parameterize bubble-mediated air-sea gas flux. Two hypotheses, identified based on previous studies and preliminary results, will be tested: (1) Stochastic breaking waves affect bubble trajectories and bubble-mediated gas flux through altering ocean boundary layer turbulence and generating bubbles at downwelling currents; and (2) Submesoscale currents alter bubble trajectories and bubble-mediated gas flux via interaction with ocean boundary layer turbulence. These hypotheses will be tested using a state-of-the-art large eddy simulation modeling framework. The coupled modeling framework consists of a Large Eddy Simulation (LES) model that simulates the ocean surface boundary layer turbulence with the impact of stochastically distributed breaking waves, a Lagrangian particle model that tracks bubbles and bubble properties, and an Eulerian concentration model for dissolved gases.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.

海洋气泡在上层海洋动力学和海气交换中起着重要作用。该项目将研究它们在海洋表面附近的分布及其与湍流的相互作用，并改进它们对海洋与大气之间气体交换影响的数值模型的表述。随机分布的破碎波和小尺度流是海洋上层普遍存在的两种过程。它们在气泡动力学和气泡介导的海气传输中的作用从未被研究过，这可能是因为在这两个动力学过程中观察和模拟气泡的挑战。利用国家的最先进的计算机模型，模拟两个动力学过程，气泡，溶解气体的基础上的第一性原理的共同演变，这项研究将推进我们的基本理解气泡动力学在上层海洋及其耦合与上层海洋动力学。它还将改善计算机模型中气泡介导的气体通量的表示。这项研究提高了我们对地球系统的理解，无论是上层海洋动力学和海洋地球化学循环。它将减少氧气和二氧化碳等对气候和环境具有重要意义的可溶性气体的建模和预算估计中的不确定性。它还将提高我们利用溶解气体，如氧气、氮气和氩气的能力，这些气体的溶解浓度受气泡的影响，作为地球化学过程的示踪剂。预期的结果也可以应用于对包括溢油和海洋塑料在内的漂浮海洋污染物的理解和预测。因此，这项研究将提高我们预测海洋环境和气候变化的能力，并将为政治和工业决策者在气候、环境、渔业、能源和减轻海洋污染等一系列问题上提供更好的科学依据。CAREER项目的教育部分包括为K-12教师开发一个为期两天的小型研讨会，并为动手海洋建模活动创建一个交互式网页，该活动将用于PI一直教授的非STEM学生的夏令营和通识教育课程。教育活动的目的是吸引当地初高中生进入海洋学领域，提高学生和公众对海洋重要性的认识，该项目的主要研究目标是更好地了解气泡的分布以及气泡与海洋湍流之间的耦合，海洋表面边界层，并更准确地参数化气泡介导的海气通量。基于先前的研究和初步结果确定的两个假设将被检验：（1）随机破碎波通过改变海洋边界层湍流并在下降流中产生气泡来影响气泡轨迹和气泡介导的气体通量;以及（2）亚中尺度流通过与海洋边界层湍流的相互作用来改变气泡轨迹和气泡介导的气体通量。这些假设将使用最先进的大涡模拟建模框架进行测试。耦合建模框架由模拟具有随机分布破碎波影响的海洋表面边界层湍流的大涡模拟（LES）模型、跟踪气泡和气泡特性的拉格朗日粒子模型、该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识产权进行评估来支持。优点和更广泛的影响审查标准。

项目成果

Influence of sea surface wave-dependent roughness on summer precipitation over the Southeastern United States

• DOI: 10.1016/j.dsr2.2022.105209
• 发表时间: 2022-10
• 期刊: Deep Sea Research Part II: Topical Studies in Oceanography
• 作者: H. Shan;C. Dong;Jun‐Hong Liang

An evaluation of vertical mixing parameterization of ocean boundary layer turbulence for cohesive sediments

粘性沉积物海洋边界层湍流垂直混合参数化的评估

• DOI: 10.1016/j.dsr2.2022.105168
• 发表时间: 2022
• 期刊: Deep Sea Research Part II: Topical Studies in Oceanography
• 作者: Liu, Jinliang;Yuan, Jianguo;Liang, Jun-Hong
• 通讯作者: Liang, Jun-Hong

Including the effects of subsurface currents on buoyant particles in Lagrangian particle tracking models: Model development and its application to the study of riverborne plastics over the Louisiana/Texas shelf

• DOI: 10.1016/j.ocemod.2021.101879
• 发表时间: 2021-11
• 期刊: Ocean Modelling
• 影响因子: 3.2
• 作者: Jun‐Hong Liang;Jinliang Liu;M. Benfield;D. Justić;D. Holstein;Bingqing Liu;R. Hetland;D. Kobashi;C. Dong;Weiyuan Dong

Exploring the use of machine learning to parameterize vertical mixing in the ocean surface boundary layer

• DOI: 10.1016/j.ocemod.2022.102059
• 发表时间: 2022-06
• 期刊: Ocean Modelling
• 影响因子: 3.2
• 作者: Jun‐Hong Liang;Jian Yuan;X. Wan;Jinliang Liu;Bingqing Liu;H. Jang;M. Tyagi

Wind- and Wave-driven Ocean Surface Boundary Layer in a Frontal Zone: Roles of Submesoscale Eddies and Ekman-Stokes Transport

锋区风和波浪驱动的海洋表面边界层：次中尺度涡流和埃克曼-斯托克斯输运的作用

• DOI: 10.1175/jpo-d-20-0270.1
• 发表时间: 2021
• 期刊: Journal of Physical Oceanography
• 影响因子: 3.5
• 作者: Yuan, Jianguo;Liang, Jun-Hong
• 通讯作者: Liang, Jun-Hong