The 2014 Iquique‐Pisagua M_w 8.1 earthquake ruptured only parts of the 1877 Northern Chile‐Southern Peru seismic gap. Here we present a comprehensive analysis of 152 continuous and campaign Global Positioning System time series that captured more than a decade of interseismic loading prior to the event and 2 years of afterslip. In high spatiotemporal resolution, our data document upper plate response not only at the coseismically affected latitudes but also at the adjacent Loa plate segment to the south. Using a combination of elastic and viscoelastic half‐space models of different stages of the seismic cycle, we found that the highly coupled, former seismic gap contains a narrow low coupling zone at 21°S latitude. Just after the 2014 earthquake, this zone acts as a barrier impeding afterslip to continue southward. Possible reasons for this impediment could involve crustal heterogeneities or coupling discontinuities at the plate interface. After 2 years, afterslip cumulates to a maximum of ~89 cm and becomes negligible. Global Positioning System observations south of the inferred seismotectonic barrier reveal a deformation rate increase in the second year after the event. Our slip models suggest that this could be caused by a downdip coupling increase, perhaps bringing the highly coupled southern Loa segment closer to failure. Taken together, our results reveal (1) the interaction between different areas undergoing stress release and stress buildup in a major seismic gap, (2) constraints for the temporal variation of coupling degree in different stages of the seismic cycle, and (3) the influence of large earthquakes at adjacent segments.

At the northwestern tip of the India‐Asia collision zone, the Pamir orocline overrides the Tajik Depression and the Tarim Basin and collides with the Tian Shan. Currently, the Pamir's northern edge exhibits localized shortening rates of 13–19 mm/yr. While the eastern Pamir and the Tarim Basin move northward nearly en block, north‐south shortening decreases westward along the Pamir front into the Tajik Depression. In the northeastern Tajik Depression, the wedge‐shaped crustal sliver of the Peter the First Range is squeezed between the dextral‐transpressive Vakhsh and the sinistral‐transpressive Darvaz faults. Global Navigation Satellite System (GNSS) data collected along two densely surveyed profiles detail the kinematics of north‐south shortening and westward lateral extrusion in the northwestern Pamir. The 2016 campaign data suggest a short‐duration dextral‐slip activation of the Darvaz fault, which we interpret as a far‐field effect triggered by the 2015, M_w7.2 Sarez, Central Pamir earthquake. 2013–2015 interseismic GNSS velocities and kinematic modeling show that the Darvaz fault zone accommodates ~15 mm/yr sinistral shear and ~10 mm/yr fault‐normal extension below a locking depth of 9.0 + 0.4/−1.1 km. The Vakhsh fault shows shortening rates of 15 + 4/−2 mm/yr and dextral shear rates of 16 ±3 mm/yr. Jointly, these faults accommodate NW‐SE shortening and southwestward material flow out of the Peter the First Range into the Tajik Depression. Together with seismic and geologic data, our and published geodetic surveys showcase the prolonged interaction of shortening and lateral material flow out of a plateau margin.

Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.

Errors in ultra-rapid UT1-UTC primarily affect the overall rotation of spatial datum expressed by GNSS (Global Navigation Satellite System) satellite ultra-rapid orbit. In terms of existing errors of traditional strategy, e.g., piecewise linear functions, for ultra-rapid UT1-UTC determination, and the requirement to improve the accuracy and consistency of ultra-rapid UT1-UTC, the potential to improve the performance of ultra-rapid UT1-UTC determination based on an LS (Least Square) + AR (Autoregressive) combination model is explored. In this contribution, based on the LS+AR combination model and by making joint post-processing/rapid UT1-UTC observation data, we propose a new strategy for ultra-rapid UT1-UTC determination. The performance of the new strategy is subsequently evaluated using data provided by IGS (International GNSS Services), iGMAS (international GNSS Monitoring and Assessment System), and IERS (International Earth Rotation and Reference Systems Service). Compared to the traditional strategy, the numerical results over more than 1 month show that the new strategy improved ultra-rapid UT1-UTC determination by 29–43%. The new strategy can provide a reference for GNSS data processing to improve the performance of ultra-rapid products.