Collaborative Research: EAGER--Improved Detection and Quantification of Wind Gusts

合作研究：EAGER——改进阵风的检测和量化

• 批准号: 1540393
• 负责人: Sara Pryor
• 金额: $ 18.75万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1540393&HistoricalAwards=false
• 关键词: Collaborative; Research; EAGER; Improved; Detection

Extreme winds events can have substantial impacts on structures and transportation. The main methods for observing winds are ground-based weather stations and weather radar. Weather stations are highly accurate, but they are widely spaced and miss many small-scale wind events. Weather radars are able to view large areas at once, but are only looking at winds well above the surface of the earth. A group of researchers is testing a novel method to use seismic data to sense wind gusts. Wind is known to have a seismic signal, and in fact solid earth scientists regard these measurements as noise. This research grant will help to determine whether the noise seen in seismic data is actually useful for determining the intensity and location of wind gusts. If the signal proves to be useful, it could have a large impact on the atmospheric science community because seismic arrays are relatively inexpensive and are always collecting data. Improved wind data has potential implications for weather and climate models, structural codes, and wind energy. An early career postdoctoral researcher will also be supported by this award.The researchers plan a study to determine the degree to which seismic arrays can be used to quantify the occurrence, intensity and directional orientation of wind gusts and intense sustained wind speeds. This research will make use of the Transportable Array (TA) of the NSF EarthScope program and a number of meteorological stations to perform the analysis. The following research questions are posed: a) Under what conditions do high surface winds produce a signal in the seismometers? b) At what frequencies does this occur? c) Is there a consistent relationship between wind gust magnitude and seismic response? d) Are the forms of b) and c) spatially consistent? e) How many false positives are identified? f) Are gust signatures differentiable across range of background sustained winds? g) To what degree are periods of high wind speeds not associated with large magnitude gusts quantifiable using seismic data? h) Can the two horizontal components recorded by the USArray seismometers be used to give the "angle of attack"?

极端风事件可能对建筑物和运输产生重大影响。 观测风的主要方法是地面气象站和天气雷达。 气象站是高度准确的，但它们分布广泛，错过了许多小规模的风事件。 气象雷达能够同时观测大面积的区域，但只能观测地球表面以上的风。 一组研究人员正在测试一种新的方法，利用地震数据来感知阵风。 众所周知，风具有地震信号，实际上，固体地球科学家将这些测量结果视为噪音。 这项研究资助将有助于确定地震数据中看到的噪音是否真的有助于确定阵风的强度和位置。 如果该信号被证明是有用的，它可能会对大气科学界产生重大影响，因为地震阵列相对便宜，而且总是在收集数据。 改进的风数据对天气和气候模型、结构规范和风能有潜在的影响。 该奖项还将资助一位早期的博士后研究人员。研究人员计划进行一项研究，以确定地震阵列在多大程度上可用于量化阵风和强烈持续风速的发生、强度和方向。 这项研究将利用NSF EarthScope计划的可移动阵列（TA）和许多气象站来进行分析。 提出了以下研究问题：a）在什么条件下地面大风会在地震仪中产生信号？ B）这种情况发生在什么频率？ c）阵风强度与地震反应之间是否存在一致的关系？d）B）和c）的形式在空间上是否一致？（1）有多少假阳性被发现？ f）阵风信号在背景持续风范围内是否可区分？ g）在多大程度上，高风速的周期与使用地震数据可量化的大幅度阵风无关？ h）USAray地震仪记录的两个水平分量能否用来给出“迎角”？