Effect of Merging Multiscale Models on Seismic Wavefield Predictions Near the Southern San Andreas Fault
Effect of Merging Multiscale Models on Seismic Wavefield Predictions Near the Southern San Andreas Fault
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DOI：
10.1029/2021jb021915
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发表时间：
2021-09
期刊：
影响因子：
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通讯作者：
R. Ajala;P. Persaud
中科院分区：
文献类型：
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作者：
R. Ajala;P. Persaud
更新科学界在地质研究和灾害评估中使用的地球模型具有重大的社会影响，但由于空间尺度很大，计算量很大。城市地震学的出现使得使用短期密集地震阵列的局部高分辨率模型的快速发展成为常规。为了将这些局部模型中的细节融入社区模型中，我们开发了一种技术，用于在规则网格上的任意形状的空间域中构建窗口锥度函数，如余弦锥度。我们通过创建两个混合模型将我们的算法应用于最南端圣安德烈亚斯断层附近的低频地面震动估计问题。这些模型由盆地尺度（顶部10公里或更少）的高分辨率模型组成，这些模型使用嵌入到两个流行的南加州地震中心社区模型中的受控源数据开发。我们评估的模型计算长周期（6-30秒）波场能量失配使用11个地震矩震级在3.5和5.5之间，没有使用在开发任何模型正在考虑。其中一个混合模型相对于其原始社区模型的整体中位数失配减少了24%，而另一个则增加了0.6%。模型之间的重叠失配值以及不同事件和台站的波形拟合的可变性凸显了模型验证的困难。我们的方法可以合并任何类型的网格多尺度和多维数据集，并代表了一个有价值的工具，在计算科学建模。
Updating Earth models used by the scientific community in geologic studies and hazard assessment has a significant societal impact but is computationally prohibitive due to the large spatial scale. The advent of urban seismology allowed rapid development of local high‐resolution models using short‐term dense seismic arrays to become conventional. To incorporate the details in these local models in community models, we developed a technique for constructing window taper functions like the cosine taper in arbitrarily shaped spatial domains on regular grids. We apply our algorithm to the problem of low‐frequency ground shaking estimation near the southernmost San Andreas fault by creating two hybrid models. These models consist of basin‐scale (top 10 km or less) high‐resolution models developed using controlled source data embedded into two popular Southern California Earthquake Center community models. We evaluate the models by computing long period (6–30 s) wavefield energy misfits using 11 earthquakes with moment magnitudes between 3.5 and 5.5 not used in developing any of the models under consideration. One of the hybrid models produces an ∼24% decrease while the other has an ∼0.6% increase in the overall median misfit relative to their original community models. The overlapping misfit values between the models and variability in waveform fit for different events and stations emphasize the difficulties in model validation. Our approach can merge any type of gridded multiscale and multidimensional datasets, and represents a valuable tool for modeling in the computational sciences.