A new method for determining first-motion focal mechanisms

A new method for determining first-motion focal mechanisms
复制标题

DOI:
10.1785/0120010200
复制
发表时间:
2002-08-01
影响因子:
3
通讯作者:
Shearer, PM
Shearer, PM
中科院分区:
地球科学3区
文献类型:
--
作者:
Hardebeck, JL;Shearer, PM

文献摘要

被引文献

相似文献

本文介绍一种由P波初动极性确定震源机制的新方法。我们的技术不同于以往的方法,因为它占可能的错误,在假设的地震位置和地震速度模型,以及在极性的意见。一组可接受的焦点机制,允许在极性和起飞角度的预期误差,发现每个事件。多个试验进行了不同的源位置和速度模型,并与指定的比例的失配极性的机制包括在一组可接受的机制。集合的平均值作为首选机制返回,不确定性由可接受机制的分布表示。只有当可接受的机制集合紧密地聚集在首选机制周围时,解决方案才被认为是足够稳定的。我们验证的方法,证明了集群的紧密间隔的事件具有类似的waveforrns的约束机制确实非常相似。对模拟真实的数据的事件和台站覆盖的噪声合成数据的测试表明,该方法准确地恢复了机制,并且不确定性估计是合理的。我们还研究了震源机制对极性、事件深度和地震速度模型变化的敏感性,发现震源机制对垂直速度梯度的变化最为敏感。
We introduce a new method for determining earthquake focal mechanisms from P-wave first-motion polarities. Our technique differs from previous methods in that it accounts for possible errors in the assumed earthquake location and seismic-velocity model, as well as in the polarity observations. The set of acceptable focal mechanisms, allowing for the expected errors in polarities and takeoff angles, is found for each event. Multiple trials are performed with different source locations and velocity models, and mechanisms with up to a specified fraction of misfit polarities are included in the set of acceptable mechanisms. The average of the set is returned as the preferred mechanism, and the uncertainty is represented by the distribution of acceptable mechanisms. The solution is considered adequately stable only if the set of acceptable mechanisms is tightly clustered around the preferred mechanism. We validate the method by demonstrating that the well-constrained mechanisms found for clusters of closely spaced events with similar waveforrns are indeed very similar. Tests on noisy synthetic data, which mimic the event and station coverage of real data, show that the method accurately recovers the mechanisms and that the uncertainty estimates are reasonable. We also investigate the sensitivity of focal mechanisms to changes in polarities, event depth, and seismic-velocity model, and we find that mechanisms are most sensitive to changes in the vertical velocity gradient.