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Abstract Megathrusts host Earth’s largest earthquakes. Understanding the physical conditions controlling their rupture dynamics is critical for assessing seismic and tsunami hazards. These earthquakes often display complex rupture dynamics, exemplified by the 2011 Tohoku-Oki earthquake, which exhibited multiple rupture episodes, depth-dependent seismic radiation, and substantial tsunamigenic slip near the trench. However, how such complexity arises from preexisting physical conditions remains uncertain. Here, we demonstrate that the observed rupture complexity of the Tohoku-Oki earthquake can spontaneously and self-consistently emerge, driven by rapid coseismic frictional restrengthening and data-informed fault heterogeneity. We use an ensemble of 3D dynamic rupture simulations to identify that mixed downdip pulse-like and updip crack-like rupture are driven by dynamic stress redistribution with episodic rupture reactivation. By featuring low fault strength compared to its dynamic stress drop, a preferred model can consistently reproduce the observed complex depth-dependent propagation speeds, multiple rupture fronts as imaged by back-projection, and large tsunamigenic slip at the trench. Our findings demonstrate that preexisting fault heterogeneity conjointly with dynamic frictional weakening and restrengthening drives seemingly unexpected megathrust rupture complexity, highlighting the need to include dynamic effects into physics-based seismic and tsunami hazard assessments of future earthquakes. 

Abstract Large earthquakes rupture faults over hundreds of kilometers within minutes. Finite‐fault models image these processes and provide observational constraints for understanding earthquake physics. However, finite‐fault inversions are subject to non‐uniqueness and uncertainties. The diverse range of published models for the well‐recorded 2011 9.0 Tohoku‐Oki earthquake illustrates this challenge, and its rupture process remains under debate. Here, we comprehensively compare 32 published finite‐fault models of the Tohoku‐Oki earthquake. We aim to identify the most coherent slip features of the Tohoku‐Oki earthquake from these slip models and develop a new method for quantitatively analyzing their variations. We find that the models correlate poorly at 1‐km subfault size, irrespective of the data type. In contrast, model agreement improves significantly with increasing subfault sizes, consistently showing that the largest slip occurs up‐dip of the hypocenter near the trench. We use the set of models to test the sensitivity of available teleseismic, regional seismic, and geodetic observations. For the large Tohoku‐Oki earthquake, we find that the analyzed finite‐fault models are less sensitive to slip features smaller than 64 km. When we use the models to compute synthetic seafloor deformation, we observe strong variations in the synthetics, suggesting their sensitivity to small‐scale slip features. Our newly developed approach offers a quantitative framework to identify common features in distinct finite‐fault slip models and to analyze their robustness using regional and global geophysical observations for megathrust earthquakes. Our results indicate that dense offshore instrumentation is critical for resolving the rupture complexities of megathrust earthquakes. 

Abstract The 1 January 2024, moment magnitude 7.5 Noto Peninsula earthquake ruptured in complex ways, challenging analysis of its tsunami generation. We present tsunami models informed by a 6‐subevent centroid moment tensor (CMT) model obtained through Bayesian inversion of teleseismic and strong motion data. We identify two distinct bilateral rupture episodes. Initial, onshore rupture toward the southwest is followed by delayed re‐nucleation at the hypocenter, likely aided by fault weakening, causing significant seafloor uplift to the northeast. We construct a complex multi‐fault uplift model, validated against geodetic observations, that aligns with known fault system geometries and is critical in modeling the observed tsunami. The simulations can explain tsunami wave amplitude, timing, and polarity of the leading wave, which are crucial for tsunami early warning. Upon comparison with alternative source models and analysis of 2000 multi‐CMT ensemble solutions, we highlight the importance of incorporating complex source effects for realistic tsunami simulations. 

The January 1st, 2024, moment magnitude (Mw) 7.5 Noto Peninsula earthquake ruptured in complex ways, challenging timely analysis of the tsunami generation. We present rapid and accurate tsunami models informed by a 6-subevent centroid moment tensor (CMT) model that we obtain by inverting teleseismic and strong motion data and validation against geodetic observations. We identify two distinct bilateral rupture episodes, including six subevents and a re-nucleation episode at its hypocenter 20 seconds after its initiation, likely aided by fault weakening. We construct a complex uplift model that aligns with known fault system geometries and is critical in modeling the observed tsunami. Our tsunami simulation can explain wave amplitude, timing, and polarity of the leading wave, which are crucial for tsunami early warning. Analyzing a 2000 multi-CMT solution ensemble and comparing to alternative rapid source models, we highlight the importance of incorporating complex source effects for realistic tsunami simulations. 

Large earthquakes rupture faults over hundreds of kilometers withinminutes. Finite-fault models elucidate these processes and provideobservational constraints for understanding earthquake physics. However,finite-fault inversions are subject to non-uniqueness and substantialuncertainties. The diverse range of published models for thewell-recorded 2011 M_w 9.0 Tohoku-Oki earthquake aptly illustrates thisissue, and details of its rupture process remain under debate. Here, wecomprehensively compare 32 finite-fault models of the Tohoku-Okiearthquake and analyze the sensitivity of three commonly-usedobservational data types (geodetic, seismic, and tsunami) to the slipfeatures identified. We first project all models to a realisticmegathrust geometry and a 1-km subfault size. At this scale, we observepoor correlation among the models, irrespective of the data type.However, model agreement improves significantly when subfault sizes areincreased, implying that their differences primarily stem fromsmall-scale features. We then forward-compute geodetic and teleseismicsynthetics and compare them with observations. We find that seismicobservations are sensitive to rupture propagation, such as thepeak-slip-rise time. However, neither teleseismic nor geodeticobservations are sensitive to spatial slip features smaller than 64 km.In distinction, the synthesized seafloor deformation of all modelsexhibits poor correlation, indicating sensitivity to small-scale slipfeatures. Our findings suggest that fine-scale slip features cannot beunambiguously resolved by remote or sparse observations, such as thethree data types tested in this study. However, better resolution maybecome achievable from uniformly gridded dense offshore instrumentation. 

Abstract With the rise of data volume and computing power, seismological research requires more advanced skills in data processing, numerical methods, and parallel computing. We present the experience of conducting training workshops in various forms of delivery to support the adoption of large-scale high-performance computing (HPC) and cloud computing, advancing seismological research. The seismological foci were on earthquake source parameter estimation in catalogs, forward and adjoint wavefield simulations in 2D and 3D at local, regional, and global scales, earthquake dynamics, ambient noise seismology, and machine learning. This contribution describes the series of workshops delivered as part of research projects, the learning outcomes for participants, and lessons learned by the instructors. Our curriculum was grounded on open and reproducible science, large-scale scientific computing and data mining, and computing infrastructure (access and usage) for HPC and the cloud. We also describe the types of teaching materials that have proven beneficial to the instruction and the sustainability of the program. We propose guidelines to deliver future workshops on these topics.