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基于南极两项实验的信号和震源特征的天然地震事件分析。

Natural Seismic Event Analysis Based on Signal and Source Characteristics from two Experiments in Antarctica.

机构信息

Federal University of Rio de Janeiro, LAMEMO-PEC/COPPE, Av. Pedro Calmon, Galeão, 21941-485 Rio de Janeiro, RJ, Brazil.

Federal University of Pará, CPGF, Rua Augusto Corrêa, 01, 66075-110 Belém, PA, Brazil.

出版信息

An Acad Bras Cienc. 2024 Jul 22;96(suppl 2):e20230752. doi: 10.1590/0001-3765202420230752. eCollection 2024.

DOI:10.1590/0001-3765202420230752
PMID:39046074
Abstract

This study presents geophysical data from two passive seismic measurements conducted at two different sites in Antarctica. We analyzed the signals mainly in the frequency domain through the multitaper method to extract some spectral characteristics of the signals that would have been out of reach through the usual FFT approach. The power spectral density of the signals carries information about the processes that generated them, allowing its correlation with their source origin and type, either natural or anthropogenic. We deal with three different source types: calving, wind, and anthropogenic origins. The former is closely related to glacier dynamics, being modulated by the prevailing atmospheric processes. At both locations the wind noise is prevalent, complicating the analysis of other events like calving. We have used data classification, estimation of the source azimuth, and seismic apparent velocity to demonstrate the viability of using geophysical methods to study glacier elastic parameters and dynamics. Moreover, the calving rate can yield a wider and more independent understanding of glacier hydrodynamics and may help to estimate the future response of the polar areas to a changing environment.

摘要

本研究展示了在南极洲两个不同地点进行的两次被动地震测量的地球物理数据。我们主要通过多谱估计方法在频域中分析信号,以提取信号的一些频谱特征,这些特征是通常的 FFT 方法无法获得的。信号的功率谱密度携带有关产生它们的过程的信息,允许将其与它们的源起源和类型(自然或人为)相关联。我们处理三种不同的源类型:崩解、风和人为起源。前者与冰川动力学密切相关,受盛行大气过程的调制。在两个地点,风噪声都很普遍,这使得对其他事件(如崩解)的分析变得复杂。我们使用数据分类、源方位估计和地震视速度来证明使用地球物理方法研究冰川弹性参数和动力学的可行性。此外,崩解率可以更广泛和更独立地了解冰川水力学,并有助于估计极地地区对环境变化的未来反应。

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