PREEVENTS Track 2: Cascadia Scenario Earthquakes: Source, Path, and implications for Earthquake Early Warning

卡斯卡迪亚俯冲带是一个1200公里长的板块边界，能够承载9级大推力地震，是太平洋西北部最大的地震和海啸危险源。一个非常紧迫的问题是准确估计潜在的地面运动，因为它们是地震造成的破坏的预测器，可以指导应急反应。在卡斯卡迪亚，目前的地面运动预测不包括控制板块界面上地震破裂的物理过程，也不考虑地壳中现实的3D波传播。该项目旨在通过结合基于物理学的地震模型和对波传播的现实估计，预测太平洋西北部9级地震造成的强烈地面运动。预测的地面运动将用于测试西海岸地震预警系统ShakeAlert的当前运行版本。该项目将为当地居民提供有关卡斯卡迪亚可能发生的地震的最先进的科学信息，并帮助利益相关者做出明智的决定，以提高太平洋西北地区的地震恢复力。这项研究将促进三名早期职业女性教授，四名学生（研究生和本科生）和两名博士后研究人员之间的实质性合作。此外，它还在震源、地面运动和早期预警社区之间建立了一个有效的沟通框架，以促进地震灾害减轻的综合方法。地震地面运动预测需要对震源动力学的基本理解和对波传播路径效应的准确估计。以前的地面运动预测的巨型逆冲断层地震要么依赖于经验关系，没有很好地约束在这个地区的数据或模拟波传播假设一定的运动破裂的历史，不一定满足物理的动态破裂。此外，以前的计算强烈依赖于速度模型的准确性，其中现实波传播通过弧前和沉积盆地没有得到很好的代表。最后，真实的震源过程和准确的波传播是必要的，以建立可靠的信息，在地震波形的地震预警。该项目将使用创新的三阶段方法构建一套可能发生在卡斯卡迪亚俯冲带的现实场景地震。首先，卡斯卡迪亚俯冲带的属性（例如几何形状，耦合和应力条件）的最新知识将被纳入完全动态破裂模拟，以确定这些因素对破裂历史的影响，并构建一套潜在的破裂历史为9级地震。然后将震源模型与绿色？的功能来自周围的地震场估计在太平洋西北部的主要人口中心的地面运动。最后，该项目将探讨这些地面运动对目前正在开发的地震预警算法的影响。

The Cascadia Subduction Zone is a 1200 km-long plate boundary that is capable of hosting a magnitude 9 megathrust earthquake and is the greatest source of seismic and tsunami hazard in the Pacific Northwest. One very pressing issue is accurate estimation of potential ground motions because they are a predictor of damage resulting from an earthquake and can guide emergency response. In Cascadia, current ground motion predictions do not incorporate the physical processes governing earthquake rupture on the plate interface or account for realistic 3D wave propagation in the Earth's crust. The project aims to predict strong ground motions resulting from a magnitude 9 earthquake in the Pacific Northwest by combining physics-based earthquake models and realistic estimates of wave propagation. The predicted ground motions will be used to test the currently operating version of ShakeAlert, the West Coast Earthquake Early Warning system. This project will provide state-of-the-art scientific information about possible Cascadia scenario earthquakes to local residents and help stakeholders make informed decisions to improve earthquake resilience in the Pacific Northwest. The research will facilitate substantial collaboration among three early career female professors, four students (graduate and undergraduate students), and two postdoctoral researchers. Additionally, it builds an effective communication framework between earthquake source, ground motion, and early warning communities to promote a comprehensive methodology for seismic hazard mitigation.The prediction of earthquake ground motions requires fundamental understanding of earthquake source dynamics and accurate estimation of wave propagation path effects. Previous ground motion predictions for megathrust earthquakes either rely on empirical relations that are not well constrained by data in this region or simulate wave propagation assuming a certain kinematic rupture history that does not necessarily satisfy the physics of dynamic ruptures. Moreover, previous calculations strongly rely on the accuracy of a velocity model, in which realistic wave propagation through fore-arc and sedimentary basins is not well represented. Finally, both realistic source processes and accurate wave propagation are necessary to establish reliable information in the seismic waveform for earthquake early warning. The project will construct a suite of realistic scenario earthquakes that could occur in the Cascadia Subduction Zone using an innovative three-stage approach. First, the most up-to-date knowledge of properties of the Cascadia Subduction Zone (e.g. geometry, coupling and stress conditions) will be incorporated in fully dynamic rupture simulations to determine the influence of each of these factors on rupture history and to construct a suite of potential rupture histories for a magnitude 9 earthquake. The earthquake source models will then be combined with Green?s functions derived from the ambient seismic field to estimate ground motions in major population centers in the Pacific Northwest. Finally, the project will explore the implications of these ground motions for earthquake early warning algorithms that are currently under development.