Characterization of Oceanic Storm Systems using Microseism

利用微震表征海洋风暴系统

• 批准号: 2243407
• 负责人: Miaki Ishii
• 金额: $ 22.56万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243407&HistoricalAwards=false
• 关键词: Characterization; Oceanic; Storm; Systems; using

Due to a warming climate, the typical behaviors of tropical cyclones and other oceanic storms are likely changing. There is great concern that over the coming decades and centuries hurricanes will become more frequent, powerful, and devastating to society, and especially coastal populations. Key information to predict how these storms will evolve comes from the historic storm catalog. These records of past storm behavior have been kept for over a century and are used to help determine the patterns in storms up until today. However, one major drawback to these records is that prior to the satellite era, the observations for most storms were sourced from nearby ships or land-based weather stations; therefore, the data are good for records of storms which were close to the coast or to major shipping lanes, but those out to sea are likely to be poorly reported or completely missed. A potential solution comes from long-running ground motion data recordings. While these records are typically used to study earthquakes, the ground motion during “quiet” times (i.e., without earthquakes) has been shown to register off-shore ocean storm activity. As such, they could fill in the gaps in storm records for the pre-satellite era. The researchers will establish the relationship between the ground motion signals (seismic data) and parameters of tropical cyclones (e.g., windspeed, location). This work will be an essential first step towards utilizing large collections of historical seismic data to develop a seismic-based catalog of storms. Such a catalog will complement existing historical storm data to paint a more comprehensive picture of how hurricanes have changed, and how they might continue to evolve over the coming century.Up to the present, many studies have shown that background seismic noise, or microseisms, are excited when a hurricane is present. This is the case even for inland seismic stations or storms that are out to sea. However, detailed analysis of how different storm parameters, such as strength and location, affect the structure of the microseism observations (i.e., the strength in different frequency bands across time) has yet to be undertaken. This project will combine several comprehensive and modern data sets to look for relationships that can be leveraged in future work to reduce bias introduced by land- or ship-track-based observations in historical storm catalogs. In particular, the HURDAT2 dataset from NOAA which gives the best storm-track and a variety of other relevant storm parameters will be compared to spectral data from seismic stations and wave-buoys. The work will focus on storms in the Atlantic and seismic stations and buoys across the Eastern United States over the last two decades. Once relationships that determine how the response of wave-buoys and seismic observations change for different combinations of storm parameters are found, the models will be used to invert the problem, i.e., constraining storm characteristics using the seismic data. This project will additionally require consideration and study of site-specific effects as well as ways to filter the effects of small local weather systems from the data. In undertaking this work, stronger constraints will also be put on the physical mechanisms which excite microseisms as well as the locations in which they are excited. The end result of this work will be an ability to extract information about oceanic storms (i.e., the presence of a storm, its strength, and its location) from seismic data alone, as well as an overall improved understanding of how energy is transferred from fluid to the solid Earth, paving a way for analyses of historical storms.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.

由于气候变暖，热带气旋和其他海洋风暴的典型行为可能会发生变化。人们非常担心，在未来几十年和几个世纪里，飓风将变得更加频繁，强大，对社会，特别是沿海人口造成破坏。预测这些风暴将如何演变的关键信息来自历史风暴目录。这些过去风暴行为的记录已经保存了一个多世纪，直到今天还被用来帮助确定风暴的模式。然而，这些记录的一个主要缺点是，在卫星时代之前，大多数风暴的观测数据来自附近的船只或陆基气象站;因此，这些数据对于靠近海岸或主要航道的风暴记录是好的，但那些出海的风暴可能报告得很差或完全错过。一个潜在的解决方案来自长期运行的地面运动数据记录。虽然这些记录通常用于研究地震，但在“安静”时间（即，没有地震）已被证明记录了近海海洋风暴活动。因此，它们可以填补前卫星时代风暴记录的空白。研究人员将建立地面运动信号（地震数据）和热带气旋参数（例如，风速、位置）。这项工作将是利用大量历史地震数据编制地震风暴目录的重要的第一步。这样的目录将补充现有的历史风暴数据，描绘一个更全面的画面，飓风如何改变，以及他们如何可能继续演变在未来世纪。到目前为止，许多研究表明，背景地震噪声，或微震，激发当飓风存在。即使是内陆地震台站或海上风暴也是如此。然而，详细分析不同的风暴参数，如强度和位置，如何影响微震观测的结构（即，不同频带中的强度）还有待进行。该项目将联合收割机结合几个全面和现代的数据集，寻找可以在未来的工作中利用的关系，以减少历史风暴目录中基于陆地或船舶跟踪的观测所带来的偏差。特别是，NOAA的HURDAT 2数据集提供了最佳风暴轨迹和各种其他相关风暴参数，将与地震台站和波浪浮标的光谱数据进行比较。这项工作将集中在大西洋的风暴和地震站和浮标在美国东部在过去的二十年。一旦找到确定波浪浮标和地震观测的响应如何随风暴参数的不同组合而变化的关系，模型将用于反演问题，即，使用地震数据约束风暴特征。该项目还需要考虑和研究特定地点的影响，以及从数据中过滤小型当地天气系统影响的方法。在进行这项工作时，还将对激发微震的物理机制以及激发微震的位置进行更严格的限制。这项工作的最终结果将是能够提取有关海洋风暴的信息（即，该奖项反映了NSF的法定使命，并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，被认为值得支持。