InSight’s seismometers recorded more than 1300 events. Ninety-eight of these, named the low-frequency family, show energy predominantly below 1 Hz down to ∼0.125 Hz. The Marsquake Service identified seismic phases and computed distances for 42 of these marsquakes, 26 of which have backazimuths. Hence, the locations of the majority of low-frequency family events remain undetermined. Here, we use an envelope shape similarity approach to determine event classes and distances, and introduce an alternative method to estimate the backazimuth. In our similarity approach, we use the highest quality marsquakes with well-constrained distance estimates as templates, including the largest event S1222a, and assign distances to marsquakes with relatively high signal-to-noise ratio based on their similarities to the template events. The resulting enhanced catalog allows us to re-evaluate the seismicity of Mars. We find the Valles Marineris region to be more active than initially perceived, where only a single marsquake (S0976a) had previously been located. We relocated two marsquakes using new backazimuth estimates, which had reported distances of ∼90o, in the SW of the Tharsis region, possibly at Olympus Mons. In addition, two marsquakes with little or no S-wave energy have been located in the NE of the Elysium Bulge. Event epicenters in Cerberus Fossae follow a North-South trend due to uncertainties in location, while the fault system is in the NW-SE direction; therefore, these events are re-projected along the observed fault system.

We report observations of Rayleigh waves that orbit around Mars up to three times following the S1222a marsquake. Averaging these signals, we find the largest amplitude signals at 30 s and 85 s central period, propagating with distinctly different group velocities of 2.9 km/s and 3.8 km/s, respectively. The group velocities constraining the average crustal thickness beneath the great circle path rule out the majority of previous crustal models of Mars that have a >200 kg/m3 density contrast across the dichotomy. We find that the thickness of the martian crust is 42-56 km on average, and thus thicker than the crusts of the Earth and Moon. Together with thermal evolution models, a thick martian crust suggests that the crust must contain 50-70% of the total heat production to explain present-day local melt zones in the interior of Mars.

The relatively unconstrained internal structure of Venus is a missing piece in our understanding of the Solar System formation and evolution. To determine the seismic structure of Venus’ interior, the detection of seismic waves generated by venusquakes is crucial, as recently shown by the new seismic and geodetic constraints on Mars’ interior obtained by the InSight mission. In the next decades multiple missions will fly to Venus to explore its tectonic and volcanic activity, but they will not be able to conclusively report on seismicity or detect actual seismic waves. Looking towards the next fleet of Venus missions in the future, various concepts to measure seismic waves have already been explored in the past decades. These detection methods include typical geophysical ground sensors already deployed on Earth, the Moon, and Mars; pressure sensors on balloons; and airglow imagers on orbiters to detect ground motion, the infrasound signals generated by seismic waves, and the corresponding airglow variations in the upper atmosphere. Here, we provide a first comparison between the detection capabilities of these different measurement techniques and recent estimates of Venus’ seismic activity. In addition, we discuss the performance requirements and measurement durations required to detect seismic waves with the various detection methods. As such, our study clearly presents the advantages and limitations of the different seismic wave detection techniques and can be used to drive the design of future mission concepts aiming to study the seismicity of Venus.

On May 4th, 2022 the InSight seismometer SEIS recorded the largest marsquake ever observed, S1222a, with an initial magnitude estimate of Mw 4.7. Understanding the depth and source properties of this event has important implications for the nature of tectonic activity on Mars. Located ~37 degrees to the southeast of InSight, S1222a is one of the few non-impact marsquakes that exhibits prominent ratio surface waves. We use waveform modeling of body waves (P and S) and surface waves (Rayleigh and Love) to constrain the moment tensor and quantify the associated uncertainty. We find that S1222a likely resulted from dip-slip faulting in the mid-crust (source depth ~18 – 28 km) and estimate a scalar moment of 3.51015 – 5.01015 Nm (magnitude Mw 4.3 – 4.4). The best-fitting focal mechanism is sensitive to the choice of phase windows and misfit weights, as well as the structural model of Mars used to calculate Green’s functions. We find that an E-W to SE-NW striking thrust fault can explain the data well, although depending on the choice of misfit weighting, a normal fault solution is also permissible. The orientation of the best-fitting fault plane solutions suggests that S1222a takes place on a fault system near the martian crustal dichotomy accommodating relative motion between the northern lowlands and southern highlands. Independent constraints on the event depth and improved models of the (an)isotropic velocity structure of the martian crust and mantle could help resolve the ambiguity inherent to single-station moment tensor inversions of S1222a and other marsquakes.

The seismic activity of a planet can be described by the corner magnitude, events larger than which are extremely unlikely, and the seismic moment rate, the long-term average of annual seismic moment release. Marsquake S1222a proves large enough to be representative of the global activity of Mars and places observational constraints on the moment rate. The magnitude-frequency distribution of relevant Marsquakes indicates a b-value of 1.17, but with its uncertainty and a volcanic region bias, b=1 is still possible. The moment rate is likely between 1.5e15 Nm/a and 1.6e18 Nm/a, with a marginal distribution peaking at 4.9e16 Nm/a. Comparing this with pre-InSight estimations shows that these tended to overestimate the moment rate, and that 30 % or more of the tectonic deformation may occur silently, whereas the seismicity is probably restricted to localized centers rather than spread over the entire planet.

The instrument package SEIS (Seismic Experiment for Internal Structure) with the three very broadband and three short-period seismic sensors is installed on the surface on Mars as part of NASA’s InSight Discovery mission. When compared to terrestrial installations, SEIS is deployed in a very harsh wind and temperature environment that leads to inevitable degradation of the quality of the recorded data. One ubiquitous artifact in the raw data is an abundance of transient one-sided pulses often accompanied by high-frequency spikes. These pulses, which we term “glitches”, can be modeled as the response of the instrument to a step in acceleration, while the spikes can be modeled as the response to a simultaneous step in displacement. We attribute the glitches primarily to SEIS-internal stress relaxations caused by the large temperature variations to which the instrument is exposed during a Martian day. Only a small fraction of glitches correspond to a motion of the SEIS package as a whole caused by minuscule tilts of either the instrument or the ground. In this study, we focus on the analysis of the glitch+spike phenomenon and present how these signals can be automatically detected and removed from SEIS’ raw data. As glitches affect many standard seismological analysis methods such as receiver functions, spectral decomposition and source inversions, we anticipate that studies of the Martian seismicity as well as studies of Mars’ internal structure should benefit from deglitched seismic data.

The InSight mission (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) has been collecting high-quality seismic data from Mars since February 2019, shortly after its landing. The Marsquake Service (MQS) is the team responsible for the prompt review of all seismic data recorded by the InSight’s seismometer (SEIS), marsquake event detection, and curating seismicity catalogues. Until sol 1011 (end of September 2021), MQS have identified 951 marsquakes that we interpret to occur at regional and teleseismic distances, and 1062 very short duration events that are most likely generated by local thermal stresses nearby the SEIS package. Here, we summarize the seismic data collected until sol 1011, version 9 of the InSight seismicity catalogue. We focus on the significant seismicity that occurred after sol 478, the end date of version 3, the last catalogue described in a dedicated paper. In this new period, almost a full Martian year of new data has been collected, allowing us to observe seasonal variations in seismicity that are largely driven by strong changes in atmospheric noise that couples into the seismic signal. Further, the largest, closest and most distant events have been identified, and the number of fully located events has increased from 3 to 7. In addition to the new seismicity, we document improvements in the catalogue that include the adoption of InSight-calibrated Martian models and magnitude scales, the inclusion of additional seismic body-wave phases, and first focal mechanism solutions for three of the regional marsquakes at distances ~30 degrees.

One of the goals of the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission is to constrain the interior structure of Mars. We present a hierarchical transdimensional Bayesian approach to extract phase velocity dispersion and interior shear-wave velocity (VS) models from a single seismogram. This method was adapted to Mars from a technique recently developed for Earth (Xu & Beghein, 2019). Monte Carlo Markov Chains (MCMC) seek an ensemble of one dimensional (1-D) VS models between a source and a receiver that can explain the observed waveform. The models obtained are used to calculate the phase velocities of fundamental and higher modes at selected periods, and a subsequent analysis is performed to assess which modes were reliably measured. An advantage of our approach is that it can also fit unknown data noise, which reduces the risk of overfitting the data. In addition, uncertainties in the source parameters can be propagated, yielding more accurate model parameter uncertainties. In this paper, we first present our technique and discuss the challenges stemming from using a single station to characterize both structure and the source and from the absence of a Mars reference model. We then demonstrate the method feasibility using the MSS blind test data and our own synthetic data, which included realistic noise levels based on the noise recorded by InSight.

Seismic noise recorded at the surface of Mars has been monitored since February 2019, using the seismometers of the InSight lander. The noise on Mars is 500 times lower than on Earth at night and it increases during the day. We analyze its polarization as a function of time and frequency in the band 0.03-1Hz. We use the degree of polarization to extract signals with stable polarization whatever their amplitude. We detect polarized signals at all frequencies and all times. Glitches correspond to linear polarized signals which are more abundant during the night. For signals with elliptical polarization, the ellipse is in the horizontal plane with clockwise and anti-clockwise motion at low frequency (LF). At high frequency (HF), the ellipse is in the vertical plane and the major axis is tilted with respect to the vertical. Whereas polarization azimuths are different in the two frequency bands, they are both varying as a function of local time and season. They are also correlated with wind direction, particularly during the day. We investigate possible aseismic and seismic origin of the polarized signals. Lander or tether noise are discarded. Pressure fluctuation transported by environmmental wind may explain part of the HF polarization but not the tilt of the ellipse. This tilt can be obtained if the source is an acoustic emission in some particular case. Finally, in the evening when the wind is low, the measured polarized signals seems to correspond to a diffuse seismic wavefield that would be the Mars microseismic noise.

NASA’s InSight seismometer has been recording Martian seismicity since early 2019, and to date, over 1300 marsquakes have been catalogued by the Marsquake Service (MQS). Due to typically low signal-to-noise ratios (SNR) of marsquakes, their detection and analysis remain challenging: while event amplitudes are relatively low, the background noise has large diurnal and seasonal variations and contains various signals originating from the interactions of the local atmosphere with the lander and seismometer system. Since noise can resemble marsquakes in a number of ways, the use of conventional detection methods for catalogue curation is limited. Instead, MQS finds events through manual data inspection. Here, we present MarsQuakeNet (MQNet), a deep convolutional neural network for the detection of marsquakes and the removal of noise contamination. Based on three-component seismic data, MQNet predicts segmentation masks that identify and separate event and noise energy in time-frequency domain. As the number of catalogued MQS events is small, we combine synthetic event waveforms with recorded noise to generate a training data set. We apply MQNet to the entire continuous 20 samples-per-second waveform data set available to date, for automatic event detection and for retrieving denoised amplitudes. The algorithm reproduces all high quality-, as well as majority of low quality events in the manual, carefully curated MQS catalogue. Furthermore, MQNet detects 60% additional events that were previously unknown with mostly low SNR, that are verified in manual review. Our analysis on the event rate confirms seasonal trends and shows a substantial increase in the second Martian year.

A seismic investigation on Saturn’s moon Enceladus could determine the thickness of the ice shell, along with variations from the mean thickness, by recovering phase and group velocities, and through the frequency content of surface waves. Here, we model the Enceladus ice shell with uniform thicknesses of 5 km, 20 km, and 40 km, as well as with ice topography ranging from 5-40 km. We investigate several approaches for recovering the mean ice shell thickness. We show that surface wave dispersions could be used to determine the mean ice shell thickness. Flexural waves in the ice only occur if the shell is thinner than a critical value < 20 km. Rayleigh waves dominate only in thicker ice shells. The frequency content of Crary waves depends on the ice shell thickness.

Detecting a seismic event from Europa’s silicate interior would provide information about the geologic and tectonic setting of the moon’s rocky interior. Reflections off a metallic core would indicate the presence, size, and state of the hypothesized core. However, the subsurface ocean will attenuate the signal, possibly preventing the waveforms from being detected by a surface seismometer. Here, we investigate the minimum magnitude of a detectable event originating from Europa’s silicate interior. We analyze likely signal-to-noise ratios and compare the predicted signal strengths to current instrument sensitivities. We show that a magnitude M_w >3.5 would be sufficient to overcome the predicted background noise. However, a minimum magnitude of M_w > 5.5 would be required for current instrumentation to be able detect the event. A thinner ice shell transmits greater ground acceleration amplitudes than a thicker ice shell, which might allow for M_w > 4.5 to be detectable.