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We report Global Positioning System (GPS) measurements of postseismic deformation following the 2015 M_w7.8 Gorkha (Nepal) earthquake, including previously unpublished data from 13 continuous GPS stations installed in southern Tibet shortly after the earthquake. We use variational Bayesian Independent Component Analysis (vbICA) to extract the signal of postseismic deformation from the GPS time series, revealing a broad displacement field extending >150 km northward from the rupture. Kinematic inversions and dynamic forward models show that these displacements could have been produced solely by afterslip on the Main Himalayan Thrust (MHT) but would require a broad distribution of afterslip extending similarly far north. This would require the constitutive parameter(a − b)σto decrease northward on the MHT to ≤0.05 MPa (an extreme sensitivity of creep rate to stress change) and seems unlikely in light of the low interseismic coupling and high midcrustal temperatures beneath southern Tibet. We conclude that the northward reach of postseismic deformation more likely results from distributed viscoelastic relaxation, possibly in a midcrustal shear zone extending northward from the seismogenic MHT. Assuming a shear zone 5–20 km thick, we estimate an effective shear‐zone viscosity of ~3·10¹⁶–3·10¹⁷ Pa·s over the first 1.12 postseismic years. Near‐field deformation can be more plausibly explained by afterslip itself and implies(a − b)σ ~ 0.5–1 MPa, consistent with other afterslip studies. This near‐field afterslip by itself would have re‐increased the Coulomb stress by ≥0.05 MPa over >30% of the Gorkha rupture zone in the first postseismic year, and deformation further north would have compounded this reloading.

 

Deformation of the Earth's surface associated with redistributions of continental water mass explains, to first order, the seasonal signals observed in geodetic position time series. Discriminating these seasonal signals from other sources of deformation in geodetic measurements is essential to isolate tectonic signals and to monitor spatio‐temporal variations in continental water storage. We propose a new methodology to identify and extract these seasonal signals. The approach uses a variational Bayesian Independent Component Analysis (vbICA) to extract the seasonal signals and a gravity‐based deformation model to identify which of these signals are caused by surface loading. We test the procedure on two study areas, the Arabian Peninsula and the Nepal Himalaya, and find that the technique successfully extracts the seasonal signals with one or two independent components, depending on whether the load is stationary or moving. The approach is robust to spatial heterogeneities inherent to geodetic measurements and can help extract systematic errors in geodetic products (e.g., draconitic errors). We also discuss how to handle the degree‐1 deformation field present in the geodetic data set but not captured by the gravity‐based model.

 

Slow earthquakes, like regular earthquakes, result from unstable frictional slip. They produce little slip and can therefore repeat frequently. We assess their predictability using the slip history of the Cascadia subduction between 2007 and 2017, during which slow earthquakes have repeatedly ruptured multiple segments. We characterize the system dynamics using embedding theory and extreme value theory. The analysis reveals a low-dimensional (<5) nonlinear chaotic system rather than a stochastic system. We calculate properties of the underlying attractor like its correlation and instantaneous dimension, instantaneous persistence, and metric entropy. We infer that the system has a predictability horizon of the order of days weeks. For the better resolved segments, the onset of large slip events can be correctly forecasted by high values of the instantaneous dimension. Longer-term deterministic prediction seems intrinsically impossible. Regular earthquakes might similarly be predictable but with a limited predictable horizon of the order of their durations. 

Abstract—In this study, we model geodetic strain accumulation along the Cascadia subduction zone between 2007.0 and 2017.632 using position time series from 352 continuous GPS stations. First, we use the secular linear motion to determine interseismic locking along the megathrust. We determine two end member models, assuming that the megathrust is either a priori locked or creeping, which differ essentially along the trench where the inversion is poorly constrained by the data. In either case, significant locking of the megathrust updip of the coastline is needed. The downdip limit of the locked portion lies * 20–80 km updip from the coast assuming a locked a priori, but very close to the coast for a creeping a priori. Second, we use a variational Bayesian Independent Component Analysis (vbICA) decomposition to model geodetic strain time variations, an approach which is effective to separate the geodetic strain signal due to non-tectonic and tectonic sources. The Slow Slip Events (SSEs) kinematics is retrieved by linearly inverting for slip on the megathrust the Independent Components related to these transient phenomena. The procedure allows the detection and modelling of 64 SSEs which spatially and temporally match with the tremors activity. SEEs and tremors occur well inland from the coastline and follow closely the estimated location of the mantle wedge corner. The transition zone, between the locked portion of the megathrust and the zone of tremors, is creeping rather steadily at the long-term slip rate and probably buffers the effect of SSEs on the megathrust seismogenic portion.