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

风是海水的一个至关重要的驱动因素，因此观测地表风在时间和位置上的变化对我们理解海洋环流非常重要。靠近大陆地区的水如何流动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，现有的浮标或卫星风观测在时间和空间上缺乏足够的分辨率，无法完全捕捉到风驱动沿海水域的过程。今天，存在一个分布式的海洋雷达系统网络，可以从陆基站远程测量洋流。该项目还将使用这些雷达远程观测风，其范围和分辨率需要捕捉风对沿海海洋的全部影响。它将扩展最近的努力，从马萨诸塞州、罗德岛州和加利福尼亚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动水面车辆，对收集到的数据进行地面验证，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。现有的浮标或卫星对地面风的观测要么提供了近岸的高时间覆盖范围，要么提供了高空间覆盖范围，但从来没有两者兼而有之。陆基高频（HF）雷达有可能填补这一观测空白。这项工作将结合最新的理论结果、高质量的雷达观测和独立的风浪观测，进一步发展基于高频雷达的风提取模型。利用来自新英格兰大陆架和圣巴巴拉海峡的新数据集和现有数据集，这项工作旨在提高我们对地面风与高频雷达系统观测到的信号之间复杂关系的理解。验证研究将在多种雷达系统观测到的区域进行，并且在地面风场中具有重要的空间结构，使用固定浮标和基于自主地面车辆（ASV）的移动风传感器。这些观测结果将用于完善我们对地面风应力与高频雷达观测信号之间关系的理解，从而对整个沿海地区的风强迫进行精确和空间密集的观测。所提出的努力将推进最近开发的风提取模型，并加强雷达反向散射功率与风速和风向之间的参数化联系。应用最新发展的测向方法和改进的校准技术，该方法将推广到任意雷达系统。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.