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The SEIS (seismic experiment for the interior structure of Mars) experiment on the NASA InSight mission has catalogued hundreds of marsquakes so far. However, the detectability of these events is controlled by the weather which generates noise on the seismometer. This affects the catalogue on both diurnal and seasonal scales. We propose to use machine learning methods to fit the wind, pressure and temperature data to the seismic energy recorded in the 0.4–1 and 2.2–2.6 Hz bandwidths to examine low- (LF) and high-frequency (HF) seismic event categories respectively. We implement Gaussian process regression and neural network models for this task. This approach provides the relationship between the atmospheric state and seismic energy. The obtained seismic energy estimate is used to calculate signal-to-noise ratios (SNR) of marsquakes for multiple bandwidths. We can then demonstrate the presence of LF energy above the noise level during several events predominantly categorized as HF, suggesting a continuum in event spectra distribution across the marsquake types. We introduce an algorithm to detect marsquakes based on the subtraction of the predicted noise from the observed data. This algorithm finds 39 previously undetected marsquakes, with another 40 possible candidates. Furthermore, an analysis of the detection algorithm’s variable threshold provides an empirical estimate of marsquake detectivity. This suggests that events producing the largest signal on the seismometer would be seen almost all the time, the median size signal event 45–50 per cent of the time and smallest signal events 5−20 per cent of the time.

Since early February 2019, the SEIS (Seismic Experiment for Interior Structure) seismometer deployed at the surface of Mars in the framework of the InSight mission has been continuously recording the ground motion at Elysium Planitia. In this study, we take advantage of this exceptional data set to put constraints on the crustal properties of Mars using seismic interferometry (SI). To carry out this task, we first examine the continuous records from the very broadband seismometer. Several deterministic sources of environmental noise are identified and specific preprocessing strategies are presented to mitigate their influence. Applying the principles of SI to the single-station configuration of InSight, we compute, for each Sol and each hour of the martian day, the diagonal elements of the time-domain correlation tensor of random ambient vibrations recorded by SEIS. A similar computation is performed on the diffuse waveforms generated by more than a hundred Marsquakes. A careful signal-to-noise ratio analysis and an inter-comparison between the two datasets suggest that the results from SI are most reliable in a narrow frequency band around 2.4 Hz, where an amplification of both ambient vibrations and seismic events is observed. The average autocorrelation functions (ACFs) contain well identifiable seismic arrivals, that are very consistent between the two datasets. Interpreting the vertical and horizontal ACFs as, respectively, the P- and S- seismic reflectivity below InSight, we propose a simple stratified velocity model of the crust, which is mostly compatible with previous results from receiver function analysis. Our results are discussed and compared to recent works from the literature.

Since early February 2019, the SEIS (Seismic Experiment for Interior Structure) seismometer deployed at the surface of Mars in the framework of the InSight mission has been continuously recording the ground motion at Elysium Planitia. In this study, we take advantage of this exceptional data set to put constraints on the crustal properties of Mars using seismic interferometry (SI). To carry out this task, we first examine the continuous records from the very broadband seismometer. Several deterministic sources of environmental noise are identified and specific preprocessing strategies are presented to mitigate their influence. Applying the principles of SI to the single-station configuration of InSight, we compute, for each Sol and each hour of the martian day, the diagonal elements of the time-domain correlation tensor of random ambient vibrations recorded by SEIS. A similar computation is performed on the diffuse waveforms generated by more than a hundred Marsquakes. A careful signal-to-noise ratio analysis and an inter-comparison between the two datasets suggest that the results from SI are most reliable in a narrow frequency band around 2.4 Hz, where an amplification of both ambient vibrations and seismic events is observed. The average autocorrelation functions (ACFs) contain well identifiable seismic arrivals, that are very consistent between the two datasets. Interpreting the vertical and horizontal ACFs as, respectively, the P- and S- seismic reflectivity below InSight, we propose a simple stratified velocity model of the crust, which is mostly compatible with previous results from receiver function analysis. Our results are discussed and compared to recent works from the literature.

NASA¿s InSight mission [1] has for the first time placed a very broad-band seismometer on the surface of Mars. The Seismic Experiment for Interior Structure (SEIS) [2] has been collecting continuous data since early February 2019. The main focus of InSight is to enhance our understanding of the internal structure and dynamics of Mars, which includes the goal to better constrain the crustal thickness of the planet [3]. Knowing the present-day crustal thickness of Mars has important implications for its thermal evolution [4] as well as for the partitioning of silicates and heat-producing elements between the different layers of Mars. Current estimates for the crustal thickness of Mars are based on modeling the relationship between topography and gravity [5,6], but these studies rely on different assumptions, e.g. on the density of the crust and upper mantle, or the bulk silicate composition of the planet and the crust. The resulting values for the average crustal thickness differ by more than 100%, from 30 km to more than 100 km [7]. New independent constraints from InSight will be based on seismically determining the crustal thickness at the landing site. This single firm measurement of crustal thickness at one point on the planet will allow to constrain both the average crustal thickness of Mars as well as thickness variations across the planet when combined with constraints from gravity and topography [8]. Here we describe the determination of the crustal structure and thickness at the InSight landing site based on seismic receiver functions for three marsquakes compared with autocorrelations of InSight data [9].

A planet's crust bears witness to the history of planetary formation and evolution, but for Mars, no absolute measurement of crustal thickness has been available. Here, we determine the structure of the crust beneath the InSight landing site on Mars using both marsquake recordings and the ambient wavefield. By analyzing seismic phases that are reflected and converted at subsurface interfaces, we find that the observations are consistent with models with at least two and possibly three interfaces. If the second interface is the boundary of the crust, the thickness is 20 +/- 5 kilometers, whereas if the third interface is the boundary, the thickness is 39 +/- 8 kilometers. Global maps of gravity and topography allow extrapolation of this point measurement to the whole planet, showing that the average thickness of the martian crust lies between 24 and 72 kilometers. Independent bulk composition and geodynamic constraints show that the thicker model is consistent with the abundances of crustal heat-producing elements observed for the shallow surface, whereas the thinner model requires greater concentration at depth.

Mars’s seismic activity and noise have been monitored since January 2019 by the seismometer of the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) lander. At night, Mars is extremely quiet; seismic noise is about 500 times lower than Earth’s microseismic noise at periods between 4 s and 30 s. The recorded seismic noise increases during the day due to ground deformations induced by convective atmospheric vortices and ground-transferred wind-generated lander noise. Here we constrain properties of the crust beneath InSight, using signals from atmospheric vortices and from the hammering of InSight’s Heat Flow and Physical Properties (HP) instrument, as well as the three largest Marsquakes detected as of September 2019. From receiver function analysis, we infer that the uppermost 8–11 km of the crust is highly altered and/or fractured. We measure the crustal diffusivity and intrinsic attenuation using multiscattering analysis and find that seismic attenuation is about three times larger than on the Moon, which suggests that the crust contains small amounts of volatiles.

Mars’s seismic activity and noise have been monitored since January 2019 by the seismometer of the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) lander. At night, Mars is extremely quiet; seismic noise is about 500 times lower than Earth’s microseismic noise at periods between 4 s and 30 s. The recorded seismic noise increases during the day due to ground deformations induced by convective atmospheric vortices and ground-transferred wind-generated lander noise. Here we constrain properties of the crust beneath InSight, using signals from atmospheric vortices and from the hammering of InSight’s Heat Flow and Physical Properties (HP3) instrument, as well as the three largest Marsquakes detected as of September 2019. From receiver function analysis, we infer that the uppermost 8–11 km of the crust is highly altered and/or fractured. We measure the crustal diffusivity and intrinsic attenuation using multiscattering analysis and find that seismic attenuation is about three times larger than on the Moon, which suggests that the crust contains small amounts of volatiles.