Iceberg A-68 separated from the Larsen C Ice Shelf in July 2017 and the impact of this event on the local ocean circulation has yet to be assessed. Here, we conduct numerical simulations of ocean dynamics near and below the ice shelf pre- and post-calving. Results agree with in situ and remote observations of the area as they indicate that basal melt is primarily controlled by wintertime sea-ice formation, which in turn produces High Salinity Shelf Water (HSSW). After the calving event, we simulate a 50% increase in HSSW intrusion under the ice shelf, enhancing ocean heat delivery by 30%. This results in doubling of the melt rate under Gipps Ice Rise, suggesting a positive feedback for further retreat that could destabilize the Larsen C Ice Shelf. Assessing the impact of ice-front retreat on the heat delivery under the ice is crucial to better understand ice-shelf dynamics in a warming environment.

Greater landward velocities were recorded after six megathrust earthquakes in subduction zone regions adjacent to the ruptured portion. Previous explanations invoked either increased slip deficit accumulation or plate bending during postseismic relaxation, with different implications for seismic hazard. We investigate whether bending can be expected to reproduce this observed enhanced landward motion (ELM). We use 3D quasi-dynamic finite element models with periodic earthquakes. We find that afterslip downdip of the brittle megathrust exclusively produces enhanced trenchward surface motion in the overriding plate. Viscous relaxation produces ELM when a depth limit is imposed on afterslip. This landward motion results primarily from in-plane elastic bending of the overriding plate due to trenchward viscous flow in the mantle wedge near the rupture. Modeled ELM is, however, incompatible with the observations, which are an order of magnitude greater and last longer after the earthquake. This conclusion does not significantly change when varying mantle viscosity, plate elasticity, maximum afterslip depth, earthquake size, megathrust locking outside of the rupture, or nature and location of relevant model boundaries. The observed ELM consequently appears to reflect faster slip deficit accumulation, implying a greater seismic hazard in lateral segments of the subduction zone.

In this study, we examine the effect of transient mantle creep on the prediction of glacial isostatic adjustment (GIA) signals. Specifically, we compare predictions of relative sea level (RSL) change from GIA from a set of Earth models in which transient creep parameters are varied in a simple Burgers model to a reference case with a Maxwell viscoelastic rheology. The model predictions are evaluated in two ways: first, relative to each other to quantify the effect of parameter variation, and second, for their ability to reproduce well-constrained sea level records from selected locations. Both the resolution and geographic location of the RSL observations determine whether the data can distinguish between model cases. Model predictions are most sensitive to the inclusion of transient mantle deformation in regions that are near-field and peripheral relative to former ice sheets. This sensitivity appears particularly true along the North American west coast in the region of the former Cordilleran Ice Sheet, which experienced rapid sea-level fall following deglaciation between 14 and 12 kyr BP. Relative to the Maxwell case, Burgers models better reproduce this rapid phase of regional postglacial sea-level fall. As well, computed goodness-of-fit values in this region show a clear preference for models where transient deformation is present in the whole or lower mantle, and for models where the rigidity of the Kelvin element is weakened relative to the rigidity of the Maxwell element. In contrast, model predictions of relative sea-level change in the far-field show weak sensitivity to the inclusion of transient deformation.

A devastating tsunami struck Palu Bay in the wake of the 28 September 2018 M_w = 7.5 Palu earthquake (Sulawesi, Indonesia). With a predominantly strike-slip mechanism, the question remains whether this unexpected tsunami was generated by the earthquake itself, or rather by earthquake-induced landslides. In this study we examine the tsunami potential of the co-seismic deformation. To this end, we present a novel geodetic data set of Global Positioning System and multiple Synthetic Aperture Radar-derived displacement fields to estimate a 3D co-seismic surface deformation field. The data reveal a number of fault bends, conforming to our interpretation of the tectonic setting as a transtensional basin. Using a Bayesian framework, we provide robust finite fault solutions of the co-seismic slip distribution, incorporating several scenarios of tectonically feasible fault orientations below the bay. These finite fault scenarios involve large co-seismic uplift (>2 m) below the bay due to thrusting on a restraining fault bend that connects the offshore continuation of two parallel onshore fault segments. With the co-seismic displacement estimates as input we simulate a number of tsunami cases. For most locations for which video-derived tsunami waveforms are available our models provide a qualitative fit to leading wave arrival times and polarity. The modeled tsunamis explain most of the observed runup. We conclude that co-seismic deformation was the main driver behind the tsunami that followed the Palu earthquake. Our unique geodetic data set constrains vertical motions of the sea floor, and sheds new light on the tsunamigenesis of strike-slip faults in transtensional basins.

Global mean sea-level rise (SLR) has accelerated since 1900 from less than 2 mm yr-1 during most of the century to more than 3 mm yr-1 since 1993. Decision-makers in coastal countries, however, require information on SLR at the regional scale, where detection of an acceleration in SLR is difficult, because the long-term sea-level signal is obscured by large inter-annual variations with multi-year trends that are easily one order of magnitude larger than global mean values. Here, we developed a time series approach to determine whether regional SLR is accelerating based on tide gauge data. We applied the approach to eight 100-year records in the southern North Sea and detected, for the first time, a common breakpoint in the early 1990s. The mean SLR rate at the eight stations increases from 1.7 ± 0.3 mm yr-1 before the breakpoint to 2.7 ± 0.4 mm yr-1 after the breakpoint (95% confidence interval), which is unprecedented in the regional instrumental record. These findings are robust provided that the record starts before 1970 and ends after 2015. Our method may be applied to any coastal region with tidal records spanning at least 40 years, which means that vulnerable coastal communities still have time to accumulate the required time series as a basis for adaptation decisions in the second half of this century.

In Southeast Alaska, extreme uplift rates are primarily caused by glacial isostatic adjustment (GIA), as a result of ice thickness changes from the Little Ice Age to the present combined with a low-viscosity asthenosphere. Previous GIA models adopted a 1-D Earth structure. However, the actual Earth structure is likely more complex due to the long history of subduction and tectonism and the transition from a continental to an oceanic plate. Seismic evidence indeed shows a laterally heterogenous Earth structure. In this study, a numeral model is constructed for Southeast Alaska, which allows for the inclusion of lateral viscosity variations. The viscosity follows from scaling relationships between seismic velocity anomalies and viscosity variations. We use this scaling relationship to constrain the thermal effect on seismic variations and investigate the importance of lateral viscosity variations. We find that a thermal contribution to seismic anomalies of 10% is required to explain the GIA observations. This implies that non-thermal effects control seismic anomaly variations in the shallow upper mantle. Due to the regional geologic history, it is likely that hydration of the mantle impact both viscosity and seismic velocity. The best-fit model has a background viscosity of 5.0 × 10¹⁹ Pa-s, and viscosities at ∼80 km depth range from 1.8 × 10¹⁹ to 4.5 × 10¹⁹ Pa-s. A 1-D averaged version of the 3-D model performed slightly better, however, the two models were statistically equivalent within a 2σ measurement uncertainty. Thus, lateral viscosity variations do not contribute significantly to the uplift rates measured with the current accuracy and distribution of sites.

The 2018 (Formula presented.) Palu earthquake is a remarkable strike-slip event due to its nature as a shallow supershear fault rupture across several segments and a destructive tsunami that followed coseismic deformation. GPS offsets in the wake of the 2018 earthquake display a transient in the surface motions of northwest Sulawesi. A Bayesian approach identifies (predominantly aseismic) deep afterslip on and below the coseismic rupture plane as the dominant physical mechanism causing the cumulative, postseismic, surface displacements whereas viscous relaxation of the lower crust and poro-elastic rebound contribute negligibly. We confirm a correlation between shallow supershear rupture and postseismic surface transients with afterslip activity in the zone below an interseismically locked fault plane where the slip rate tapers from zero to creeping.

Joint effects of the dynamic sea-level rise projected changes in the large-scale atmosphere/ocean circulation, and wave climate on hurricane-induced extreme water levels in the Caribbean region are assessed. We use the 2D-depth integrated ADCIRC + SWAN wave-ocean model, baroclinically coupled to an ocean-eddying version of the Community Earth System Model, to compare impacts of the September 2017 hurricanes with projected impacts of similar hypothetical tropical storms occurring in the future. The model predicts only minor changes in the hurricane-induced extreme water levels for those Caribbean islands which were severely devastated by the 2017 tropical storms (Irma and Maria). That is, provided that the hurricane intensity remains at the present-day level, the global mean sea-level rise is the main future coastal flood risk factor.

In this study, we focus on improved constraint of the glacial isostatic adjustment (GIA) signal at present-day, and its role as a contributor to present-day sea level budgets. The main study area extends from the coastal regions of northwestern Europe to northern Europe. Both Holocene relative sea level (RSL) data as well as vertical land motion (VLM) data are incorporated as constraints in a semi-empirical GIA model. 71 geological rates of GIA-driven RSL change are inferred from Holocene proxy data and 108 rates of vertical land motion from GNSS provide an additional measure of regional GIA deformation. Within the study area, the geological RSL data complement the spatial gaps of the VLM data and vice versa. Both data sets are inverted in a semi-empirical GIA model to yield updated estimates of regional present-day GIA deformations. A regional validation using tide gauges is presented for the North Sea, where the GIA signal may be complicated by lateral variations in Earth structure and existing predictions of regional and global GIA models show discrepancies. The model validation in the North Sea region suggests that geological data are needed to fit independent estimates of GIA-related RSL change inferred from tide gauge rates, indicating that geological rates from Holocene data do provide an important additional constraint for data-driven approaches to GIA estimation.

The effect of glacial isostatic adjustment (GIA) on the shape and gravity of the Earth is usually described by numerical models that solve for both glacial evolution and Earth's rheology, being mainly constrained by the geological evidence of local ice extent and globally distributed sea level data, as well as by geodetic observations of Earth's rotation. In recent years, GPS and GRACE observations have often been used to improve those models, especially in the context of regional studies. However, consistency issues between different regional models limit their ability to answer questions from global-scale geodesy. Examples are the closure of the sea level budget, the explanation of observed changes in Earth's rotation, and the determination of the origin of the Earth's reference frame. Here, we present a global empirical model of present-day GIA, solely based on GRACE data and on geoid fingerprints of mass redistribution.We will show how the use of observations from a single space-borne platform, together with GIA fingerprints based on different viscosity profiles, allows us to tackle the questions from globalscale geodesy mentioned above. We find that, in the GRACE era (2003-2016), freshwater exchange between land and oceans has caused global mean sea level to rise by 1:2±0:2mmyr^-11, the geocentre to move by 0:4± 0:1mmyr^-11, and the Earth's dynamic oblateness (J₂) to increase by 6:0±0:4×10^-11 yr^-11,.

This work provides a comparison of four approaches that can be used to describe uncertainty in models of the long-term glacial isostatic adjustment (GIA) process. The four methods range from pessimistic to optimistic representations of GIA uncertainty. Each estimation method is applied to selected one dimensional GIA model predictions and compared with vertical land motion data from Global Positioning System (GPS) measurements across Fennoscandia and North America. The methods are evaluated relative to two main properties: (1) their expected ability to separate non-GIA from GIA signals and (2) their estimated statistical appropriateness given a specific GIA model and data set. For the first point, non-GIA signals are considered isolated from the long-term (millennial time scale) GIA signal at sites where measurement and model uncertainties do not overlap. Across methods, the frequency and accuracy with which non-GIA signals are separated from GIA signals in GPS data display both consistent similarities and disparities. For the second point, we compare model predictions with rates of vertical land motion and relative sea level change that have been cleaned of non-GIA signals to determine the most appropriate value of model uncertainty and relate the findings to the four approaches. Best fit inferences suggest that within deglaciation centers, GIA model uncertainty is up to ~2 mm/yr (vertical land motion). Likewise, away from the former ice sheet centers, GIA uncertainty for relative sea level change is inferred to be ~0.3–0.5 mm/yr along the U.S. East Coast and ~0.6–0.8 mm/yr in the North Sea.

The conventional sea level budget (SLB) equates changes in sea surface height with the sum of ocean mass and steric change, where solid-Earth movements are included as corrections but limited to the impact of glacial isostatic adjustment. However, changes in ocean mass load also deform the ocean bottom elastically. Until the early 2000s, ocean mass change was relatively small, translating into negligible elastic ocean bottom deformation (OBD), hence neglected in the SLB equation. However, recently ocean mass has increased rapidly; hence, OBD is no longer negligible and likely of similar magnitude to the deep steric sea level contribution. Here, we use a mass-volume framework, which allows the ocean bottom to respond to mass load, to derive a SLB equation that includes OBD. We discuss the theoretical appearance of OBD in the SLB equation and its implications for the global SLB.

Recent studies disagree about the contribution of variations in temperature and salinity of the oceans—steric change—to the observed sea-level change. This article explores two sources of uncertainty to both global mean and regional steric sea-level trends. First, we analyze the influence of different temperature and salinity data sets on the estimated steric sea-level change. Next, we investigate the impact of different stochastic noise models on the estimation of trends and their uncertainties. By varying both the data sets and noise models, the global mean steric sea-level trend and uncertainty can vary from 0.69 to 2.40 and 0.02 to 1.56 mm/year, respectively, for 1993–2017. This range is even larger on regional scales, reaching up to 30 mm/year. Our results show that a first-order autoregressive model is the most appropriate choice to describe the residual behavior of the ensemble mean of all data sets for the global mean steric sea-level change over the last 25 years, which consequently leads to the most representative uncertainty. Using the ensemble mean and the first-order autoregressive noise model, we find a global mean steric sea-level change of 1.36 ± 0.10 mm/year for 1993–2017 and 1.08 ± 0.07 mm/year for 2005–2015. Regionally, a combination of different noise models is the best descriptor of the steric sea-level change and its uncertainty. The spatial coherence in the noise model preference indicates clusters that may be best suited to investigate the regional sea-level budget.