Collaborative Research: A Lagrangian Description of Breaking Ocean Surface Waves from Laboratory Measurements and Stochastic Parameterizations.

合作研究：根据实验室测量和随机参数化对破碎海洋表面波浪的拉格朗日描述。

• 批准号: 1524241
• 负责人: Juan Restrepo
• 金额: $ 31.25万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-18 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1524241&HistoricalAwards=false
• 关键词: Collaborative; Research; Lagrangian; Description; Breaking

Wave breaking effects are important in many areas of atmospheric and ocean sciences, including air-sea interaction and momentum, energy and biogeochemical fluxes; hurricane dynamics and thermodynamics; pollutant transport and dispersion; aerosol production and ocean acoustics, to name a few. The goal of this collaborative research is to build a stochastic Lagrangian parameterization of surface wave breaking that can subsequently be applied to wave and ocean modeling. The students and postdoctoral researchers employed in this project will gain experience in the disciplines of science, technology, engineering and mathematics (STEM). The data and breaking parameterization developed here will subsequently find direct application in atmosphere and ocean modeling.Increases in the fidelity and resolution of ocean models, specifically those focused on the sub-mesoscales, require improved representation of surface wave processes. In addition to the importance of wave breaking in the dynamics of wave-current interaction, it also plays an important role in mass transport beyond that represented in classical theories of Stokes drift; in the dynamics and kinematics of Langmuir turbulence; and, more generally, in the transport and dispersion of tracers and pollutants. This research involves laboratory experiments to measure the Lagrangian displacement and velocity of fluid particles in breaking waves. The data will then be used to develop and parameterize a stochastic ordinary differential equation, within the class of Langevin equations, to describe the Lagrangian motion of the fluid elements. The parameterization will be constrained by the n-point structure functions for the experimentally obtained particle paths, which are comparatively easier to obtain and to relate to a stochastic ordinary (Lagrangian) differential equation, when compared to obtaining the n-point structure function of an (Eulerian) stochastic partial differential equation. Given the Lagrangian model, a projection to the Eulerian frame will be used to obtain the dynamical representation of breaking for wave-current interaction and other mixed-layer processes.

破波效应在大气和海洋科学的许多领域都很重要，包括海气相互作用和动量、能量和生物地球化学通量；飓风动力学和热力学；污染物的迁移和扩散；气溶胶产生和海洋声学，举几个例子。这项合作研究的目标是建立一个表面波破碎的随机拉格朗日参数化，该参数化可以随后应用于波浪和海洋建模。本项目聘用的学生和博士后研究人员将获得科学、技术、工程和数学（STEM）学科的经验。这里发展的数据和破碎参数化将随后在大气和海洋模式中得到直接应用。提高海洋模式的保真度和分辨率，特别是那些集中在亚中尺度的模式，需要改进表面波过程的表示。波浪破碎不仅在波流相互作用动力学中具有重要意义，而且在经典斯托克斯漂移理论之外的质量输运中也起着重要作用；Langmuir湍流的动力学和运动学；更普遍的是，在示踪剂和污染物的运输和分散中。本研究包括测量破碎波中流体粒子的拉格朗日位移和速度的实验室实验。然后，这些数据将被用来建立一个随机常微分方程，并将其参数化，该方程属于朗日方程，用于描述流体元素的拉格朗日运动。参数化将受到实验获得的粒子路径的n点结构函数的约束，与获得（欧拉）随机偏微分方程的n点结构函数相比，实验获得的粒子路径相对更容易获得并与随机普通（拉格朗日）微分方程相关。给定拉格朗日模型，将使用欧拉框架的投影来获得波流相互作用和其他混合层过程的破断的动态表示。