Volcanic Earthquake Swarms

这个项目的动机是一个简单但不方便的事实：几乎所有的火山爆发之前都有地震群，但大多数火山的地震群之后都没有爆发。虽然地震学仍然是追踪和了解火山活动的主要工具之一，但这一事实导致了比其他任何方法都更多的错误喷发预测。火山上的非爆发地震群造成了无数的假警报、经济影响和社区反应。通过研究喷发性和非喷发性地震群的特征，该项目解决了火山科学的一个基本挑战。我们将通过简单、定量可重复的参数来描述火山地震群的特征，从而提高解释火山地震群众多来源的能力。资金将几乎全部用于支持博士后研究人员。目标1：量化火山地震群机制的定义特征。火山群之间的比较历来具有挑战性，因为每个火山群都是用一种定制的技术进行研究的。我们计划用统一的方法重新分析大量火山群。从原始的连续地震记录开始，自动化技术将用于创建新的地震目录，涵盖感兴趣的群体。使用新的星表，将根据速率、震级和波形特征推导出一套定量参数。参数空间的主成分分析，结合传统和贝叶斯假设检验，将用于识别每个群体机制的定义特征。作为这项研究的副产品，地震群目录将在其产生时在网络上公开提供。对于这里提出的大多数地震群来说，新的地震目录将比现有的任何数据都要多得多。目标2：评估多次或重复地震的喷发预测潜力。因为多胞胎意味着一个长期存在的非破坏性源，它们在预测喷发行为方面特别有希望。基于目标1中导出的群体特征，将识别具有显著多序列的群体。从这些多胞胎中，将计算出许多为群体导出的相同参数。对于多重波，可以利用它们的波形相似性来进行震源迁移，从高精度旅行时间、尾波干涉测量和精确的相对震级推断。通过将这些现象提炼成简单的参数，将应用与目标1中相同的参数技术。通过研究来自众多火山背景的序列，将分离出每种源类型的定义特征。虽然这一分析将涵盖许多类型的多胞胎，但其动机是评估最常预示喷发的特征。

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.