Collaborative Research: Resolving Spatial and Temporal Variations in Near Shore Wind Stress via Advances in High Frequency Radar

风是海洋沃茨的一个至关重要的驱动力，因此，随着时间和位置的变化，对表面风的观测对我们了解海洋环流非常重要。水在大陆附近地区的流动方式可能会影响商业鱼类种群的流动，搜索和救援工作以及近岸地区的许多其他人类活动。然而，现有的浮标或基于卫星的风观测缺乏充分捕捉风驱动沿海沃茨所需的时间和空间分辨率。 今天，海洋学雷达系统的分布式网络已经存在，可以从陆基台站远程测量洋流。 该项目还将使用这些雷达在捕获风对沿海海洋的全部影响所需的范围和分辨率上远程观测风。 它将扩大最近的努力，从马萨诸塞州、罗得岛和加州的海洋雷达收集的观测数据中提取风的信号。该团队还将部署波浪浮标和自主水面车辆，以收集地面真实数据，并改进用于将雷达回波转换为风速和风向的模型。 这些观测将有助于天气预报，并提高我们对沿海海洋的了解。现有的浮标或卫星观测海面风的方法要么提供高的时间覆盖范围，要么提供高的空间覆盖范围，但从来没有两者兼而有之。陆基高频雷达有可能填补这一观测空白。这项工作将结合最近的理论结果，高质量的雷达观测，独立的风和波浪观测，以进一步开发基于高频雷达的风提取模型。 使用新的和现有的数据集从新英格兰大陆架和圣巴巴拉通道，这项工作旨在提高我们的理解表面风和高频雷达系统观察到的信号之间的复杂关系。验证研究将在由多种类型的雷达系统观测到的、表面风场具有显著空间结构的地区进行，使用固定浮标和基于移动的自主式水面航行器的风传感器。 这些观测结果将用于完善我们对表面风应力与高频雷达观测信号之间关系的理解，从而实现对整个沿海地区风强迫的准确和空间密集观测。 拟议的努力将推进最近开发的风提取模型，并加强雷达后向散射功率与风速和风向之间的参数化联系。 应用最新发展的方向发现方法和开发改进的校准技术，该方法将被推广到任意的雷达系统。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

Wind is a critically important driver of ocean waters, so observations of surface winds as they vary in time and location are important to our understanding of ocean circulation. How water moves in the regions near continents can affect the movement of commercial fish stocks, search and rescue efforts, and many other human endeavors in the nearshore region. Yet available buoy or satellite-based wind observations lack the resolution in time and space needed to fully capture the wind as it drives coastal waters. Today, a distributed network of oceanographic radar systems exists which measure ocean currents remotely from land-based stations. This project will use these radars to also observe winds remotely over the range and resolution needed to capture the wind's full effects on the coastal ocean. It will expand on recent efforts to extract the wind's signal from the observations collected by oceanographic radars in Massachusetts, Rhode Island, and California. The team will also deploy wave buoys and autonomous surface vehicles to ground-truth the data collected and refine the models used to translate radar returns into wind speed and direction. These observations will aid weather forecasts, and improve our understanding of the coastal ocean.Existing observations of the surface winds from buoys or satellites provide either high temporal coverage or high spatial coverage of the nearshore, but never both. Land-based high frequency (HF) radars have the potential to fill this observational gap. This work will couple recent theoretical results, high quality radar observations, and independent wind and wave observations to further develop HF radar-based wind extraction models. Using new and existing datasets from both the New England Shelf and Santa Barbara Channel, this effort seeks to improve our understanding of the complex relationship between surface winds and the signals observed by HF radar systems. Validation studies will be carried out in areas observed by multiple types of radar systems and with significant spatial structure in the surface wind field, using both fixed buoy and mobile, Autonomous Surface Vehicle (ASV)-based wind sensors. These observations will be used to refine our understanding of the relationship between surface wind stress and the signal observed by HF radars, enabling accurate and spatially dense observations of wind forcing throughout the coastal zone. The proposed effort will advance recently developed wind extraction models and strengthen parameterized links between radar backscattered power and wind speed and direction. Applying recent developments in direction finding methods and developing improved calibration techniques, the method will be generalized to arbitrary radar systems.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.