Collaborative Research: Detecting Glacier Calving Events from Ocean Waves and Underwater Acoustics

合作研究：从海浪和水下声学检测冰川崩解事件

• 批准号: 1743693
• 负责人: Fiammetta Straneo
• 金额: $ 16.32万
• 依托单位: University of California-San Diego Scripps Inst of Oceanography
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-15 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1743693&HistoricalAwards=false
• 关键词: Collaborative; Research; Detecting; Glacier; Calving

Predictions of future sea level rise depend on accurate estimates of the rate at which ice sheets deliver fresh water and ice to the oceans. These estimates are provided by models, which, in turn, depend on our understanding of iceberg calving, among other processes. Due to a lack of observations, our ability to project rates of iceberg calving needs improvement. This project will provide an inexpensive means of detecting and, potentially, characterizing such events.The project will contribute to workforce development through provision of support for the training of a graduate student and a post-doctoral associate. It will enhance community resources by releasing the open source calving detection software, written in the R statistical language, on a variety of web sites.The principal investigators of this project will develop a method for detecting and characterizing glacier calving events by measuring the surface waves generated during the process. Development of the method will make use of data already collected in Sarqardleq fjord in West Greenland. Following the project both the data and the method will be made publicly available. In addition, they will characterize the noise generated by calving events using underwater acoustic data that was collected simultaneously with the wave data. The comparison of the acoustic and surface pressure data, in conjunction with high temporal resolution time-lapse imagery, will be used to improve understanding of the details of acoustic signatures of glacier calving.

对未来海平面上升的预测取决于对冰盖向海洋输送淡水和冰的速度的准确估计。 这些估计是由模型提供的，而模型又取决于我们对冰山崩解等过程的理解。 由于缺乏观测，我们预测冰山崩解率的能力需要提高。 该项目将提供一种廉价的手段来检测并可能描述此类事件的特征。该项目将通过为研究生和博士后助理的培训提供支持，促进劳动力发展。 它将通过在各种网站上发布用 R 统计语言编写的开源崩解检测软件来增强社区资源。该项目的主要研究人员将开发一种通过测量表面波来检测和表征冰川崩解事件的方法过程中产生的。 该方法的开发将利用在格陵兰岛西部的萨卡德莱克峡湾已经收集的数据。 该项目完成后，数据和方法都将公开。 此外，他们将使用与波浪数据同时收集的水声数据来表征产犊事件产生的噪声。 声学和表面压力数据的比较，结合高时间分辨率延时图像，将用于增进对冰川崩解声学特征细节的理解。