Volcanic Earthquake Swarms

火山地震群

• 批准号: 1044930
• 负责人: Michael West
• 金额: $ 26.85万
• 依托单位: University of Alaska Fairbanks Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-01 至 2015-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1044930&HistoricalAwards=false
• 关键词: Volcanic; Earthquake; Swarms

This project is motivated by one simple, but inconvenient, reality: Almost all volcanic eruptions are preceded by earthquake swarms, but most earthquake swarms at volcanoes are not followed by eruptions. Though seismology remains one of the primary tools for tracking and understanding volcanic behavior, this fact is responsible for more false eruption forecasts than any other. Non-eruptive earthquake swarms at volcanoes have caused countless false alarms, economic impacts, and community responses. By addressing eruptive and non-eruptive earthquake swarm characteristics, this project attacks one of the fundamental challenges in volcano science. We will improve capabilities for interpreting the numerous sources of volcanic earthquake swarms by characterizing them with simple, but quantitatively repeatable, parameters. Funds will be used almost exclusively to support a post doctoral researcher.Objective 1: Quantify the defining characteristics of volcanic earthquake swarm mechanisms. Comparisons between volcanic swarms have historically been challenging because each swarm has been studied with a custom technique. We plan to reanalyze swarms from a wide suite of volcanoes using a uniform methodology. Beginning with the original continuous seismic records, automated techniques will be used to create new earthquake catalogs that span the swarms of interest. Using the new catalogs, a suite of quantitative parameters will be derived based on rates, magnitudes, and waveform characteristics. Principal component analysis of the parameter space, paired with traditional and Bayesian hypothesis testing, will be used to identify the defining characteristics of each swarm mechanism. As a byproduct of this research, earthquake swarm catalogs will be made openly available on the web as they are produced. For most of the swarms proposed here, the new catalogs will contain vastly more earthquakes than anything currently available.Objective 2: Assess the eruption forecasting potential of multiplet, or repeating, earthquakes. Because multiplets imply a long-lived non-destructive source, they are particularly promising for forecasting eruptive behavior. Building on swarm characteristics derived in objective 1, swarms with significant multiplet sequences will be identified. From these multiplets many of the same parameters derived for the swarms will be calculated. Additional measures are available for multiplets that exploit their waveform similarity for source migration inferred from high-precision travel times, coda wave interferometry, and precise relative magnitudes. By distilling these phenomena to simple parameters the same parametric techniques will be applied as in objective 1. By examining sequences from numerous volcanic settings, the defining characteristics of each source type will be isolated. While this analysis will span many types of multiplets, the motivation is to assess the features that most frequently portend eruption.

这个项目的动机是一个简单但不方便的现实：几乎所有的火山爆发之前都有地震群，但大多数火山地震群之后并没有爆发。虽然地震学仍然是追踪和了解火山活动的主要工具之一，但这一事实比其他任何方法都要对更多的错误喷发预测负责。火山的非爆发性地震群已经造成了无数的错误警报、经济影响和社区反应。通过解决喷发和非喷发地震群的特点，这个项目攻击火山科学的基本挑战之一。我们将提高解释火山地震群的众多来源的能力，用简单但可重复的定量参数来描述它们。资金将几乎完全用于支持一名博士后研究员。目标1：量化火山震群机制的定义特征。火山群之间的比较历来具有挑战性，因为每个群都是用定制技术研究的。我们计划使用统一的方法重新分析来自一系列火山的火山群。从最初的连续地震记录开始，自动化技术将被用来创建跨越感兴趣的地震群的新地震目录。使用新的目录，一套定量参数将推导出基于速率，幅度和波形特征。参数空间的主成分分析，与传统和贝叶斯假设检验配对，将用于确定每个群机制的定义特征。作为这项研究的副产品，震群目录将在产生时在网络上公开提供。对于这里提出的大多数震群，新目录将包含比目前可用的任何地震都多得多的地震。目标2：评估多重或重复地震的爆发预测潜力。由于多重意味着一个长期的非破坏性的来源，他们是特别有前途的预测喷发行为。在目标1中导出的群特征的基础上，将识别具有显著多重态序列的群。从这些多重态中，可以计算出许多与蜂群相同的参数。额外的措施可用于多重峰，利用它们的波形相似性，从高精度的旅行时间，尾波干涉测量和精确的相对幅度推断源迁移。通过将这些现象提炼为简单的参数，将应用与目标1相同的参数技术。通过检查来自众多火山背景的层序，将分离出每种源类型的定义特征。虽然这种分析将涵盖许多类型的多胞胎，但其动机是评估最经常预示喷发的特征。