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.

Convective vortices (whirlwinds) and dust devils (dust-loaded vortices) are one of the most common phenomena on Mars, observable on a daily basis. They reflect the local thermodynamical structure of the atmosphere and are the driving force of the dust cycle. Additionally, they cause an elastic ground deformation, which is useful for retrieving the subsurface rigidity. Therefore, investigating Martian convective vortices with the right instrumentation can lead to a better understanding of the Martian atmospheric structures as well as the subsurface physical properties. In this study, we quantitatively characterized the convective vortices detected by NASA’s InSight mission (~13,000 events) using both meteorological (e.g., pressure, wind speed, temperature) and seismic data. The evaluated parameters, such as the signal-to-noise ratio, event duration, asymmetricity of pressure drop profiles, and cross-correlation coefficient between seismic and pressure signals, are compiled as a catalog. To demonstrate how our catalog can contribute to scientific investigations, we show two analysis results about (i) asymmetrical features seen in the vortex-related pressure drops and (ii) atmospheric-ground interaction to retrieve the subsurface physical properties.

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.

Seismic observations involve signals that can be easily masked by noise injection. For InSight, NASA's lander on Mars, the atmosphere is a significant noise contributor for two thirds of a Martian day, and while the noise is below that seen at even the quietest sites on Earth, the amplitude of seismic signals on Mars is also considerably lower requiring an understanding and quantification of environmental injection at unprecedented levels. Mars' ground and atmosphere provide a continuous coupled seismic system, and although atmospheric functions are of distinct origins, the superposition of these noise contributions is poorly understood, making separation a challenging task. We present a novel method for partitioning the observed signal into seismic and environmental contributions. Pressure and wind fluctuations are shown to exhibit temporal cross-frequency coupling across multiple bands, injecting noise that is neither random nor coherent. We investigate this through comodulation, quantifying the signal synchrony in seismic motion, wind and pressure. By working in the time-frequency domain, we discriminate the origins of underlying processes and provide the site's environmental sensitivity. Our method aims to create a virtual vault at InSight, shielding the seismometers with effective post-processing in lieu of a physical vault. This allows us to describe the environmental and seismic signals over a sequence of sols, to quantify the wind and pressure injection, and estimate the seismic content of possible Marsquakes with a signal-to-noise ratio that can be quantified in terms of environmental independence. Finally, we exploit the temporal energy correlations for source attribution of our observations.

In early 2019, NASA’s InSight lander successfully deployed a single three-component very broadband seismometer (VBB) on the surface of Mars to detect and characterize marsquakes. Using these data, we present a method to infer the source mechanisms of marsquakes from waveforms of P and S waves recorded at a single station. We show that the three events with the highest signal-to-noise ratio (SNR) and a robust distance estimate S0173a, (May 23rd 2019), S0235b, (July 27th 2019) and S0183a, (June 3rd 2019) are all likely the results of normal faulting, suggesting an extensional regime mainly oriented south-east north-west in the respective source regions, Cerberus Fossae and Orcus Patera. We quantify the uncertainty of our solutions by comparing results of a direct inversion with a grid-search method.