A rockslide-generated tsunami in a Greenland fjord rang Earth for 9 days.

Climate change is increasingly predisposing polar regions to large landslides. Tsunamigenic landslides have occurred recently in Greenland (Kalaallit Nunaat), but none have been reported from the eastern fjords. In September 2023, we detected the start of a 9-day-long, global 10.88-millihertz (92-second) monochromatic very-long-period (VLP) seismic signal, originating from East Greenland. In this study, we demonstrate how this event started with a glacial thinning-induced rock-ice avalanche of 25 × 106 cubic meters plunging into Dickson Fjord, triggering a 200-meter-high tsunami. Simulations show that the tsunami stabilized into a 7-meter-high long-duration seiche with a frequency (11.45 millihertz) and slow amplitude decay that were nearly identical to the seismic signal. An oscillating, fjord-transverse single force with a maximum amplitude of 5 × 1011 newtons reproduced the seismic amplitudes and their radiation pattern relative to the fjord, demonstrating how a seiche directly caused the 9-day-long seismic signal. Our findings highlight how climate change is causing cascading, hazardous feedbacks between the cryosphere, hydrosphere, and lithosphere.

Segregated oceanic crust trapped at the bottom mantle transition zone revealed from ambient noise interferometry.

The recycling of oceanic crust, with distinct isotopic and chemical signature from the pyrolite mantle, plays a critical role in the chemical evolution of the Earth with insights into mantle circulation. However, the role of the mantle transition zone during this recycling remains ambiguous. We here combine the unique resolution reflected body waves (P410P and P660P) retrieved from ambient noise interferometry with mineral physics modeling, to shed new light on transition zone physics. Our joint analysis reveals a generally sharp 660-km discontinuity and the existence of a localized accumulation of oceanic crust at the bottom mantle transition zone just ahead of the stagnant Pacific slab. The basalt accumulation is plausibly derived from the segregation of oceanic crust and depleted mantle of the adjacent stagnant slab. Our findings provide direct evidence of segregated oceanic crust trapped within the mantle transition zone and new insights into imperfect whole mantle circulation.

Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning.

The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert-intensive, supervised fashion. Moreover, analyses that are conducted can be strongly biased by the standard models employed by seismologists. In response to both of these challenges, we develop a new unsupervised machine learning framework for detecting and clustering seismic signals in continuous seismic records. Our approach combines a deep scattering network and a Gaussian mixture model to cluster seismic signal segments and detect novel structures. To illustrate the power of the framework, we analyze seismic data acquired during the June 2017 Nuugaatsiaq, Greenland landslide. We demonstrate the blind detection and recovery of the repeating precursory seismicity that was recorded before the main landslide rupture, which suggests that our approach could lead to more informative forecasting of the seismic activity in seismogenic areas.

The 2020 coronavirus lockdown and seismic monitoring of anthropic activities in Northern Italy.

In March/April 2020 the Italian government drastically reduced vehicle traffic and interrupted all non-essential industrial activities over the entire national territory. Italy thus became the first country in the world, with the exception of Hubei, to enact lockdown measures as a consequence of the COVID-19 outbreak and the need to contain it. Italy is also a seismically active area, and as such is monitored by a dense permanent network of seismic stations. We analyse continuous seismic data from many stations in northern and central Italy, and quantify the impact of the lockdown on seismic ambient noise, as a function of time and location. We find that the lockdown reduces ambient noise significantly in the 1-10 Hz frequency range; because natural sources of seismic noise are not affected by the lockdown, the seismic signature of anthropic noise can be characterised with unprecedented clarity, by simply comparing the signal recorded before and after the lockdown. Our results correlate well with independent evaluations of the impact of the lockdown (e.g., cell phone displacements), and we submit that ambient-noise seismology is a useful tool to monitor containment measures such as the coronavirus lockdowns.

Earthquake rupture below the brittle-ductile transition in continental lithospheric mantle.

Earthquakes deep in the continental lithosphere are rare and hard to interpret in our current understanding of temperature control on brittle failure. The recent lithospheric mantle earthquake with a moment magnitude of 4.8 at a depth of ~75 km in the Wyoming Craton was exceptionally well recorded and thus enabled us to probe the cause of these unusual earthquakes. On the basis of complete earthquake energy balance estimates using broadband waveforms and temperature estimates using surface heat flow and shear wave velocities, we argue that this earthquake occurred in response to ductile deformation at temperatures above 750°C. The high stress drop, low rupture velocity, and low radiation efficiency are all consistent with a dissipative mechanism. Our results imply that earthquake nucleation in the lithospheric mantle is not exclusively limited to the brittle regime; weakening mechanisms in the ductile regime can allow earthquakes to initiate and propagate. This finding has significant implications for understanding deep earthquake rupture mechanics and rheology of the continental lithosphere.