The Predictive Skills of Elastic Coulomb Rate-and-State Aftershock Forecasts during the 2019 Ridgecrest, California, Earthquake Sequence
The Predictive Skills of Elastic Coulomb Rate-and-State Aftershock Forecasts during the 2019 Ridgecrest, California, Earthquake Sequence
复制标题
DOI：
10.1785/0120200028
复制
发表时间：
2020-08-01
影响因子：
3
通讯作者：
Parsons, Tom
中科院分区：
文献类型：
--
作者：
Mancini, Simone;Segou, Margarita;Parsons, Tom
业务地震预报协议通常使用统计模型，其公认的易于实施和鲁棒性，在描述触发地震活动的短期时空模式。然而，基于物理的余震预测的最新进展显示，当考虑到故障和应力场的不均匀性时，与标准的统计对应物具有相当的性能，并具有显著提高的预测技能。在这里，我们在2019年里奇克雷斯特（加州）地震序列的第一个月进行了伪前瞻性预测实验。我们开发了七个库仑速率和状态模型，耦合静态应力变化估计与连续介质力学表示的速率和状态摩擦定律。我们的模型参数化支持一个逐渐增加的复杂性，我们从一个初步的模型实施与简化的滑移分布和空间均匀的接收器故障，以达到一个增强的具有优化的故障本构参数，有限故障滑动模型，二次触发效应，和空间异质性平面通知预先存在的破裂。加州南部数据丰富的环境使我们能够测试在地震序列展开期间近实时收集的数据是否会提高我们的预测能力。我们评估的绝对和相对性能的预测，通过统计测试的地震可预测性的研究合作实验室内使用，并比较他们的技能对一个标准的基准地震型余震序列（ETAS）模型的短期（24小时后的两个里奇克雷斯特主震）和中期（一个月）。基于压力的预测预计，整个近断层地区的地震率将沿着升高，加洛克断层中部的地震率也将升高。我们的比较模型评估不仅支持断层不均匀性加上二次触发效应是基于物理的预测背后最关键的成功组件，而且还强调了模型更新的重要性，包括近实时可用的余震数据，达到比标准ETAS更好的性能。我们通过调查里奇克雷斯特近源区预先存在的正断层的局部关闭来探索我们结果背后的物理基础。
Operational earthquake forecasting protocols commonly use statistical models for their recognized ease of implementation and robustness in describing the short-term spatiotemporal patterns of triggered seismicity. However, recent advances on physics-based aftershock forecasting reveal comparable performance to the standard statistical counterparts with significantly improved predictive skills when fault and stress-field heterogeneities are considered. Here, we perform a pseudoprospective forecasting experiment during the first month of the 2019 Ridgecrest (California) earthquake sequence. We develop seven Coulomb rate-and-state models that couple static stress-change estimates with continuum mechanics expressed by the rate-and-state friction laws. Our model parameterization supports a gradually increasing complexity; we start from a preliminary model implementation with simplified slip distributions and spatially homogeneous receiver faults to reach an enhanced one featuring optimized fault constitutive parameters, finite-fault slip models, secondary triggering effects, and spatially heterogenous planes informed by pre-existing ruptures. The data-rich environment of southern California allows us to test whether incorporating data collected in near-real time during an unfolding earthquake sequence boosts our predictive power. We assess the absolute and relative performance of the forecasts by means of statistical tests used within the Collaboratory for the Study of Earthquake Predictability and compare their skills against a standard benchmark epidemictype aftershock sequence (ETAS) model for the short (24 hr after the two Ridgecrest mainshocks) and intermediate terms (one month). Stress-based forecasts expect heightened rates along the whole near-fault region and increased expected seismicity rates in central Garlock fault. Our comparative model evaluation not only supports that faulting heterogeneities coupled with secondary triggering effects are the most critical success components behind physics-based forecasts, but also underlines the importance of model updates incorporating near-real-time available aftershock data reaching better performance than standard ETAS. We explore the physical basis behind our results by investigating the localized shut down of pre-existing normal faults in the Ridgecrest near-source area.