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Clinton, John

Publications and source records attributed to Clinton, John.

Activating a Natural Fault Zone in the Swiss Alps

One major hurdle for understanding earthquake mechanics are observational limitations. Important phenomena like strain localisation, fault dilation, and fault healing are readily studied in rock mechanical laboratory experiments and with numerical models. At the scale of natural earthquakes, however, these phenomena are often unresolvable, even by state-of-the-art observatories. To overcome this limitation, we are currently building the Earthquake Physics Testbed at the Bedretto Underground Laboratory for Geosciences and Geoenergies (BedrettoLab), an experimental testbed where we can activate an extensively instrumented natural fault zone via hydraulic stimulation. The goal of the Fault Activation and Earthquake Rupture (FEAR) project is to induce earthquakes of up to Mw~1.0 on this exceptionally well characterised and instrumented fault zone. Here we summarize the main scientific goals and current FEAR project status, and present first results from conducted experiments. We discuss how this large-scale experimental approach may allow us to tackle both fundamental science as well as practical questions on earthquake physics, induced seismicity and seismic hazard.

Meier, Men-Andrin↗

Anatomy of Continuous Mars SEIS and Pressure Data from Unsupervised Learning

The seismic noise recorded by the Interior Exploration using Seismic Investigations, Geodesy, and Heat Transport (InSight) seismometer (Seismic Experiment for Interior Structure [SEIS]) has a strong daily quasi-periodicity and numerous transient microevents, associated mostly with an active Martian environment with wind bursts, pressure drops, in addition to thermally induced lander and instrument cracks. That noise is far from the Earth’s microseismic noise. Quantifying the importance of nonstochasticity and identifying these microevents is mandatory for improving continuous data quality and noise analysis techniques, including autocorrelation. Cataloging these events has so far been made with specific algorithms and operator’s visual inspection. We investigate here the continuous data with an unsupervised deep-learning approach built on a deep scattering network. This leads to the successful detection and clustering of these microevents as well as better determination of daily cycles associated with changes in the intensity and color of the background noise. We first provide a description of our approach, and then present the learned clusters followed by a study of their origin and associated physical phenomena. We show that the clustering is robust over several Martian days, showing distinct types of glitches that repeat at a rate of several tens per sol with stable time differences. We show that the clustering and detection efficiency for pressure drops and glitches is comparable to or better than manual or targeted detection techniques proposed to date, noticeably with an unsupervised approach. Finally, here we discuss the origin of other clusters found, especially glitch sequences with stable time offsets that might generate artifacts in autocorrelation analyses. We conclude with presenting the potential of unsupervised learning for long-term space mission operations, in particular, for geophysical and environmental observatories.

58 GEOSCIENCES↗

Seismic constraints from a Mars impact experiment using InSight and Perseverance

NASA’s InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission has operated a sophisticated suite of seismology and geophysics instruments on the surface of Mars since its arrival in 2018. On 18 February 2021, we attempted to detect the seismic and acoustic waves produced by the entry, descent and landing of the Perseverance rover using the sensors onboard the InSight lander. Similar observations have been made on Earth using data from both crewed and uncrewed spacecraft, and on the Moon during the Apollo era, but never before on Mars or another planet. This was the only seismic event to occur on Mars since InSight began operations that had an a priori known and independently constrained timing and location. It therefore had the potential to be used as a calibration for other marsquakes recorded by InSight. Here we report that no signal from Perseverance’s entry, descent and landing is identifiable in the InSight data. Nonetheless, measurements made during the landing window enable us to place constraints on the distance–amplitude relationships used to predict the amplitude of seismic waves produced by planetary impacts and place in situ constraints on Martian impact seismic efficiency (the fraction of the impactor kinetic energy converted into seismic energy).

79 ASTRONOMY AND ASTROPHYSICS↗

Estimation of the Seismic Moment Release Rate of Mars from InSight Seismic Data

Seismicity models for Mars usually estimate the long-term average annual seismic moment rate, and also the average annual event rate. This holds for estimations based on geological evidence (Golombek et al., 1992, Golombek, 2002, Taylor et al., 2013) as well as for models based on thermal evolution and cooling of the Martian interior (Phillips, 1991, Knapmeyer et al., 2006, Plesa et al., 2018). All studies are compatible with the conclusion based on the non-observation of any unambiguous event by Viking (Anderson et al., 1977, Goins & Lazarewicz, 1979) that Martian seismicity lies somewhere between that of the Moon and that of the Earth. We developed tools to derive reasonable estimations of the annual seismic moment rate from a number of events as small as one, provided that the observed events are beyond the global completeness threshold for observable events. Numerical tests as well as evaluation of terrestrial data shows the feasibility of the approach.

Knapmeyer, Martin↗