Wave Impacts in Upper Ocean Mixing

该奖项是根据2009年美国复苏和再投资法案(公法111-5)资助的。表面波被认为在上层海洋边界层中发挥关键作用，但在海洋环流或气候模式中使用的任何主要边界层参数中都没有明确出现。本项目将通过检验以下假设来评估这种忽略是否重要：(1)在最近和拟议的大涡模拟(LES)预测的情况下，混合层湍流强度和卷吸效率将随着表面波年龄、涌浪的存在和边界层深度的减小而增加。(2)除了通常对表面应力、浮力通量和次表层切变的依赖之外，包括这些海况依赖的边界层模式将比不包含这些依赖关系的边界层模式更准确。OWS Papa的NOAA/PMEL长期系泊的多年数据将被用来检验第二个假设。与海洋和大气层管理局/太平洋气象局的海洋观测卫星小组合作，将在海洋观测卫星站点部署一个专用面波测量浮标。结合现有的海气通量、海洋层结和切变的测量，这些数据将为一维海洋边界层模式的强迫和检验提供完整、高质量的数据。现有的边界层参数，包括KPP和二次矩湍流闭合，将根据海况变化对混合层卷吸的影响进行修改，通过临界总体Richardson数准则或通过湍流动能产生率或平衡水平。这组模型将与三年来增强的OWS-P数据进行比较，以检验第二个假设。在上层海洋边界层运行的跟随水的拉格朗日浮标的数据将被用来检验第一个假设。在过去17年中部署的这些仪器产生的测量结果可以估计垂直动能分布和热、盐和浮力的通量分布。这些数据几乎涵盖了整个海洋风速范围[0-57m/S]和大范围混合层深度[0-250m]，但并不涵盖每个风速下的大范围波动条件。在这些数据中，风速、面波和海洋切变测量的质量也有很大差异。数据集将通过在靠近OWS-P的成熟的大片海域和华盛顿湖上一座浮桥的背风处非常年轻的小海域部署额外的浮标来增强。将使用遥感和业务风/浪产品来补充新的和现有的浮标数据。这些增强的数据，加上用于模型数据比较的理想化和基于观测的大涡模拟案例研究，将被统一分析以检验第一个假设。海洋边界层中的湍流混合是气候系统中的一个关键组成部分，在确定表层温度和二氧化碳通量以及支持上层海洋生产力的过渡层营养通量方面起着至关重要的作用。业务模型现在例行地对面波场进行全球预测。将这些信息整合到模型中可能会在广泛的范围内对物理和生物地球化学模型产生重大影响。这项工作中使用的OWS-P数据将近乎实时地公开，从而为未来的研究提供长期、高质量的数据集。该项目将支持对K-12学生及其教师的持续外展和教育努力。该项目将支持一名工程专业本科生的培训和研究经验，以及一名本科生气象学专业的独特预报经验。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Intellectual Merit. Surface waves are believed to play a key role in the upper ocean boundary layer, yet do not appear explicitly in any of the major boundary layer parameterizations used in ocean circulation or climate models. This project will assess whether this neglect is important by testing the following hypothesis:(1) Mixed layer turbulence intensity and entrainment efficiency, scaled by wind stress, will increase with surface wave age, in the presence of swell, and with decreasing boundary layer depth as predicted by recent and proposed Large Eddy Simulations (LES).(2) A boundary layer model that includes these sea state dependencies, in addition to the usual dependencies on surface stress, buoyancy flux, and subsurface shear, will be significantly more accurate than one which does not.Multi-year data from the NOAA/PMEL long-term mooring at OWS Papa, will be used to test the second hypothesis. In collaboration with the OWS-P team at NOAA/PMEL, a dedicated surface wave measuring buoy will be deployed at the OWS-P site. Combined with existing measurements of air-sea fluxes, ocean stratification and shear, these data will provide complete, high quality data for the forcing and testing of 1-D ocean boundary layer models with waves. Existing boundary layer parameterizations, including KPP and a second moment turbulence closure, will be modified for the effect of variations in sea state on mixed layer entrainment, via critical bulk Richardson numbers criteria or through Turbulence Kinetic Energy (TKE) production rates or equilibrium levels. This ensemble of models will be compared against 3 years of enhanced OWS-P data to test the second hypothesis.Data from water-following Lagrangian floats operated in the upper ocean boundary layer will be used to test the first hypothesis. These instruments, deployed over the last 17 years, have produced measurements from which profiles of vertical kinetic energy and flux profiles of heat, salt and buoyancy can be estimated. These data span almost the entire range of oceanic wind speeds [0-57 m/s] and a wide range of mixed layer depths [0-250m], but do not span a wide range of wave conditions at each wind speed. The quality of wind speed, surface wave and ocean shear measurements also vary greatly among these data. The data set will be enhanced with an additional float deployment in mature, big seas near OWS-P, and on very young, small seas in the lee of a floating bridge over Lake Washington. Remote sensing and operational wind/wave products will be used to supplement both the new and existing float data. This enhanced data, coupled with both idealized and observationally-based LES case studies for model-data comparison, will be analyzed uniformly to test the first hypothesis.Broader Impacts. Turbulent mixing in the oceanic boundary layer is a key component in the climate system, playing a crucial role in setting the surface values and thus fluxes of temperature and CO2 as well as the transition layer nutrient fluxes supporting upper ocean productivity. Operational models now routinely make global predictions of surface wave fields. Incorporation of this information into models could have significant impacts on physical and biogeochemical models on a wide range of scales.The OWS-P data used in this work will be available publicly in near-real time thus providing a long-term, high quality data set for future studies. The project will support continuing outreach and education efforts to K-12 students and their teachers. The project will support training and research experience for one undergraduate engineering major, and a unique forecasting experience for an undergraduate meteorology student.