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

破浪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；污染物迁移和扩散；仅举几例，气溶胶的产生和海洋声学。这项合作研究的目标是建立表面波浪破碎的随机拉格朗日参数化，随后可应用于波浪和海洋建模。该项目雇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。这里开发的数据和突破性参数化随后将直接应用于大气和海洋建模。海洋模型的保真度和分辨率的提高，特别是那些专注于亚中尺度的模型，需要改进表面波过程的表示。除了波破碎在波流相互作用动力学中的重要性之外，它还在质量传输中发挥着超出经典斯托克斯漂移理论所代表的重要作用。朗缪尔湍流的动力学和运动学；更一般地说，是示踪剂和污染物的运输和扩散。这项研究涉及实验室实验来测量破碎波中流体粒子的拉格朗日位移和速度。然后，这些数据将用于开发和参数化朗之万方程类中的随机常微分方程，以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，这些函数相对更容易获得并且与随机常（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裂的动力学表示。

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.