A large strike-slip earthquake occurred in the Caribbean Sea on 28 January 2020. We inverted teleseismic P-waveforms from the earthquake to construct a finite-fault model by a new method of inversion that simultaneously resolves the spatiotemporal evolution of fault geometry and slip. The model showed almost unilateral rupture propagation westward from the epicenter along a 300 km section of the Oriente transform fault with two episodes of rupture at speeds exceeding the local shear-wave velocity. Our modeling indicated that the 2020 Caribbean earthquake rupture encountered a bend in the fault system associated with a bathymetric feature near the source region. The geometric complexity of the fault system triggered multiple rupture episodes and a complex rupture evolution. Our analysis of the earthquake revealed complexity of rupture process and fault geometry previously unrecognized for an oceanic transform fault that was thought to be part of a simple linear transform fault system.

We developed a flexible finite-fault inversion method for teleseismic P waveforms to obtain a detailed rupture process of a complex multiple-fault earthquake. We estimate the distribution of potency-rate density tensors on an assumed model plane to clarify rupture evolution processes, including variations of fault geometry. We applied our method to the 23 January 2018 Gulf of Alaska earthquake by representing slip on a projected horizontal model plane at a depth of 33.6 km to fit the distribution of aftershocks occurring within one week of the mainshock. The obtained source model, which successfully explained the complex teleseismic P waveforms, shows that the 2018 earthquake ruptured a conjugate system of N-S and E-W faults. The spatiotemporal rupture evolution indicates irregular rupture behavior involving a multiple-shock sequence, which is likely associated with discontinuities in the fault geometry that originated from E-W sea-floor fracture zones and N-S plate-bending faults.

We consider a Bayesian multi-model fault slip estimation (BMMFSE), in which many candidates of the underground-structure model characterized by a prior probability density function (PDF) are retained for a fully Bayesian estimation of fault slip distribution to manage model uncertainty properly. We performed geodetic data inversions to estimate slip distribution in long-term slow slip events (L-SSEs) that occurred beneath the Bungo Channel, southwest Japan, in around 2010 and 2018, focusing on the two advantages of BMMFSE: First, it allows for estimating slip distribution without introducing strong prior information such as smoothing constraints, handling an ill-posed inverse problem by combining a full Bayesian inference and accurate consideration of model uncertainty to avoid overfitting; second, the posterior PDF for the underground structure is also obtained through a fault slip estimation, which enables the estimation of sequential events by reducing the model uncertainty. The estimated slip distribution obtained using BMMFSE agreed better with the distribution of deep tectonic tremors at the down-dip side of the main rupture area than those obtained based on strong prior constraints in terms of the spatial distribution of the Coulomb failure stress change. This finding suggests a mechanical relationship between the L-SSE and the synchronized tremors. The use of the posterior PDF for the underground structure updated by the estimation for the 2010 L-SSE as an input of the analysis for the one in 2018 resulted in a more preferable Bayesian inference, indicated by a smaller value of an information criterion.