Real-Time High-Rate GNSS Displacements: Performance Demonstration during the 2019 Ridgecrest, California, Earthquakes
Real-Time High-Rate GNSS Displacements: Performance Demonstration during the 2019 Ridgecrest, California, Earthquakes
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DOI：
10.1785/0220190223
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发表时间：
2020-07
影响因子：
3.3
通讯作者：
D. Melgar;T. Melbourne;B. Crowell;J. Geng;W. Szeliga;C. Scrivner;M. Santillan;D. Goldberg
中科院分区：
文献类型：
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作者：
D. Melgar;T. Melbourne;B. Crowell;J. Geng;W. Szeliga;C. Scrivner;M. Santillan;D. Goldberg
Cite this article as Melgar，D.，T. I.墨尔本，B。W. Crowell，J. Geng，W.塞利加角斯克里夫纳，M. Atelllan和D. E. Goldberg（2019）.实时高速率GNSS位移：2019年里奇克雷斯特，加州，地震期间的性能演示。保留信函XX，1-9，doi：10.1785/ 0220190223.传统的实时（RT）地震学依赖于惯性传感器来表征地面运动和地震源，特别是对于危险应用，如预警系统。在过去十年中，高速率、实时全球导航卫星系统（GNSS）位移的革命为增强传统测量设备提供了新的数据来源。2019年加州的里奇克雷斯特地震序列提供了迄今为止最完整的RT-GNSS位移记录之一，有助于在最初几天内进行初步的震源表征。在本文中，我们分析并提供存档的RT位移流，并将其性能与我们提供的后处理结果进行比较。我们发现所有显示出明显信号的站都很一致。这表明，RT中的简单建模，例如峰值地面位移缩放，实际上与后处理结果相同。同样，我们发现在整个频谱范围内，从同震偏移（100 Hz）的奈奎斯特频率很好的协议。我们还发现现场测量采集和数据中心位置计算之间的延迟较低。总的来说，里奇克雷斯特地震期间的表现有力地证明了实时全球导航卫星系统作为一种监测手段的可行性和有用性。
Cite this article as Melgar, D., T. I. Melbourne, B. W. Crowell, J. Geng, W. Szeliga, C. Scrivner, M. Santillan, and D. E. Goldberg (2019). Real-Time HighRate GNSS Displacements: Performance Demonstration during the 2019 Ridgecrest, California, Earthquakes, Seismol. Res. Lett. XX, 1–9, doi: 10.1785/ 0220190223. Traditional real-time (RT) seismology has relied on inertial sensors to characterize ground motions and earthquake sources, particularly for hazards applications such as warning systems. In the past decade, a revolution in high-rate, RT Global Navigation Satellite Systems (GNSS) displacement has provided a new source of data to augment traditional measurement devices. The Ridgecrest, California, earthquake sequence in 2019 provided one of the most complete recordings of RT-GNSS displacements to date, helping aid in an initial source characterization over the first few days. In this article, we analyze and make available the archived RT displacement streams and compare their performance to postprocessed results, which we also provide. We find good agreement for all stations showing a noticeable signal. This demonstrates that simple modeling in RT, such as peak ground displacement scaling, would be practically identical to postprocessed results. Similarly, we find good agreement across the full spectral range, from the coseismic offsets (∼0 Hz) to the Nyquist frequency. We also find low latency between the measurement acquisition at the field site and the position calculation at the data center. In aggregate, the performance during the Ridgecrest earthquakes is strong evidence of the viability and usefulness of RT-GNSS as a monitoring