Collaborative Research: Incorporating SPECFEM3D numerical seismograms in the Global CMT Project

这项研究将为改进地震的科学描述奠定基础，使地震统计、地震层析成像、地震危险性和地震判别以及构造解释和分析方面的研究人员受益。这是使复杂而昂贵的数值计算结果可用于多种应用程序和广泛的用户的第一步。这项工作的重点是证明方法的可行性，但数据库和方法将是有价值的任何研究需要准确预测的全球地震波场从任意地震在任何位置，而无需昂贵的计算。两名研究生将在地震科学、理论地震学和计算地球科学的联系方面进行研究培训。这项为期两年的重点工作将：（1）开发一种计算、存储和访问高保真长周期合成地震图的新方法，用于最先进的地球三维层析成像模型;以及（2）将这些地震图纳入全球质心矩张量（CMT）项目的地震分析中。目前，CMT合成地震图是使用现代三维地球模型计算的，但精度受到模式求和和表面波射线理论的路径平均近似的有效性，地面运动的振幅和极化的不精确预测，以及其他未建模的影响，偏差检索的地震参数的限制。在CMT分析中纳入更高保真度的合成地震图将改善地震源的特性，消除对不确定性和偏差的关键来源的担忧。该团队将调整频谱元素波动方程求解器SPECFEM3D_GLOBE，以在全球震源网格上生成一个核地震图数据库，用于大量台站位置，使用源-接收器互易性来加速计算。网格上的核心地震图将以便于快速访问特定震源区和全球地震网台站的格式进行组织和储存。任意质心位置的核地震图将通过空间内插以与完全正演计算的精度相匹配的方式有效地计算。将修改CMT代码，以摄取内插的SPECFEM3D_GLOBE地震图，测试将允许评估方法和方法的成功。普林斯顿数值地震学小组和拉蒙地震分析小组将联合评估波形内插的方法和保真度，开发访问全球波形（大规模）数据库的实用格式，并评估这些开发的成功。该奖项还由地球科学理事会和高级网络基础设施办公室合作共同资助，以支持地球科学领域的人工智能/机器学习和开放科学活动。该奖项反映了NSF的法定使命，并通过使用该基金会的评估被认为值得支持智力优点和更广泛的影响审查标准。

This research will lay the groundwork for improvements in the scientific description of earthquakes, benefitting researchers in earthquake statistics, seismic tomography, seismic hazard, and seismic discrimination, as well as tectonic interpretation and analysis. This is the first step towards making the results of complex and expensive numerical calculations available for multiple applications and a wide range of users. This work focuses on demonstrating the feasibility of the methodology, but the database and method will be valuable for any research requiring accurate predictions of the global seismic wavefield from an arbitrary earthquake at any location without expensive computation. Two graduate students will be trained in research at the nexus of earthquake science, theoretical seismology, and computational Earth science.This two-year, focused effort will (1) develop a new method for calculating, storing, and accessing high-fidelity long-period synthetic seismograms for state-of-the-art 3D tomographic models of the Earth, and (2) incorporate these seismograms in the earthquake analysis of the Global Centroid-Moment-Tensor (CMT) Project. Currently, the CMT synthetic seismograms are calculated using modern 3D Earth models, but accuracy is limited by the validity of the path-average approximation for mode summation and surface-wave ray theory, inexact predictions of the amplitude and polarization of ground motion, and other unmodeled effects, bias retrieved earthquake parameters. The incorporation of higher-fidelity synthetic seismograms in the CMT analysis will improve the characterization of seismic sources and remove concerns about a key source of uncertainty and bias. The team will adapt the spectral-element wave-equation solver SPECFEM3D_GLOBE to generate a database of kernel seismograms on a global grid of hypocenters, for a large set of station locations, using source-receiver reciprocity to speed up the calculation. Kernel seismograms on the grid will be organized and stored in a format that facilitates rapid access to a particular source region and the stations of the Global Seismographic Network. Kernel seismograms for an arbitrary centroid location will be efficiently calculated by spatial interpolation, in a manner that matches the accuracy of the full forward calculation. The CMT code will be modified to ingest the interpolated SPECFEM3D_GLOBE seismograms and testing will allow the assessment of success of the approach and method. The Princeton numerical seismology group and Lamont earthquake-analysis group will jointly evaluate the approach and fidelity of the waveform interpolation, develop practical formats for accessing the (massive) database of global waveforms, and assess the success of these developments.This project is jointly supported by the Geophysics and Instrumentation and Facilities programs in the Division of Earth Sciences. It is also co-funded by a collaboration between the Directorate for Geosciences and Office of Advanced Cyberinfrastructure to support AI/ML and open science activities in the geosciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.