Collaborative Research: Global Observational Constraints on Oceanic Response to Wind Forcing

点击翻译按钮获取中文摘要

The physical processes responsible for distributing momentum throughout the ocean surface boundary layer are the subject of active concern in the oceanographic community. This interest is motivated to a large degree by the central importance of correctly parameterizing upper-ocean processes in coupled climate models. At the same time, there is a tradition in oceanography of seeking physical information by examining the nature of the relationship between wind stress and observed surface currents. This study will contribute to a better understanding of the mixing processes that are needed to accurately parameterize the ocean surface boundary layer in global climate models, an important societal benefit. Any improvement in the ability to estimate surface currents given the wind forcing is expected to be of interest for oil spill response and other practical applications. A key output for the community will be an improved estimate of the locally wind-driven currents, which will be distributed from the Global Drifter Program's website as a supplementary data product. This project will also support an early-career scientist.The goal of this project is to better understand the dynamics of the ocean surface boundary layer through the first global study of the wind/current transfer function. This is to be accomplished by analyzing in detail the response to wind forcing in the global array of surface drifters, which sample the ocean currents in the vicinity of their 15 m drogue depth. The global analysis is to be informed and tested by (i) a prototype study from the Salinity Processes in the Upper Ocean Regional Study region, near a well-instrumented air-sea flux mooring, and (ii) analysis of synthetic data generated with a recently improved turbulence closure model that explicitly includes Langmuir turbulence. The hypotheses that wind, wave, and stratification state substantially modify near-surface mixing will be tested by examining dependencies of the transfer function on various environmental parameters, such as Langmuir number. Observed patterns will then be interpreted and scrutinized by deriving new theoretical approximations to the expected transfer functions characterizing different mixing processes.