Event Location with Sparse Data: When Probabilistic Global Search is Important

Arrowsmith Stephen; Park Junghyun; Che Il-Young; Stump Brian; Averbuch Gil

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Event Location with Sparse Data: When Probabilistic Global Search is Important

机译：具有稀疏数据的事件位置：当概率全球搜索很重要时

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Locating events with sparse observations is a challenge for which conventional seismic location techniques are not well suited. In particular, Geiger?s method and its variants do not properly capture the full uncertainty in model parameter estimates, which is char-acterized by the probability density function (PDF). For sparse observations, we show that this PDF can deviate significantly from the ellipsoidal form assumed in conventional methods. Furthermore, we show how combining arrival time and direction-of-arrival constraints?as can be measured by three-component polarization or array methods ?can significantly improve the precision, and in some cases reduce bias, in location solutions. This article explores these issues using various types of synthetic and real data (including single-component seismic, three-component seismic, and infrasound).

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《Seismological research letters》 |2021年第2a期|共10页
作者
Arrowsmith Stephen; Park Junghyun; Che Il-Young; Stump Brian; Averbuch Gil;
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作者单位

Southern Methodist Univ Roy M Huffington Dept Earth Sci Dallas TX 75205 USA;

Southern Methodist Univ Roy M Huffington Dept Earth Sci Dallas TX 75205 USA;

Korea Inst Geosci &

Mineral Resources Earthquake Res Ctr Daejeon South Korea;

Southern Methodist Univ Roy M Huffington Dept Earth Sci Dallas TX 75205 USA;

Southern Methodist Univ Roy M Huffington Dept Earth Sci Dallas TX 75205 USA;

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正文语种 eng
中图分类地震学;
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Event Location with Sparse Data: When Probabilistic Global Search is Important

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