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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.

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 seismometer deployed at the surface of Mars in the framework of the NASA-InSight mission has been continuously recording the ground motion at Elysium Planitia. In this work, we take advantage of this exceptional dataset to put constraints on the crustal properties of Mars using seismic interferometry (SI). This method use the seismic waves, either from background vibrations of the planet or from quakes, that are scattered in the medium in order to recover the ground response between two seismic sensors. Applying the principles of SI to the single-station configuration of SEIS, we compute, for each Sol (martian day) and each local hour, all the components of the time-domain autocorrelation tensor of random ambient vibrations in various frequency bands. A similar computation is performed on the diffuse waveforms generated by more than a hundred Marsquakes. For imaging application a careful signal-to-noise ratio analysis and an inter-comparison between the two datasets are applied. These analyses suggest that the reconstructed ground responses are most reliable in a relatively narrow frequency band around 2.4Hz, where an amplification of both ambient vibrations and seismic events is observed. The average Auto-Correlation Functions (ACFs) from both ambient vibrations and seismic events contain well identifiable seismic arrivals, that are very consistent between the two datasets. We interpret the vertical and horizontal ACFs as the ground reflection response below InSight for the compressional waves and the shear waves respectively. We propose a simple stratified velocity model of the crust, which is most compatible with the arrival times of the detected phases, as well as with previous seismological studies of the SEIS record. The hourly computation of the ACFs over one martian year also allows us to study the diurnal and seasonal variations of the reconstructed ground response with a technique call Passive Image Interferometry (PII).

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's 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. Plain Language Summary The instrument package SEIS (Seismic Experiment for Internal Structure) with two fully equipped seismometers is installed on the surface of Mars as part of NASA's InSight Discovery mission. When compared to terrestrial installations, SEIS is more exposed to wind and daily temperature changes that leads to inevitable degradation of the quality of the recorded data. One consequence is the occurrence of a specific type of transient noise that we term glitch. Glitc

Planetary crusts are the results of mantle differentiation, so their thickness provides important constraints on the thermochemical evolution of a planet, including its heat budget and mantle rheology. Information on crustal layering and seismic velocities can also provide important constraints on porosity and geochemistry of the crust. Here, we use data from the InSight mission, which landed in November 2018, to provide seismological constraints on the crustal layering and thickness of Mars for the first time. Results are mainly based on Ps-receiver functions from three events with magnitudes between 3.1 and 3.6 at distances between 27.5° and 47° (±10°) from the lander, originating in the Cerberus Fossae region, the only events, so far, with clear, impulsive P-wave onsets and known epicenter. Ps-receiver functions use converted phases in the P-wave coda to derive information on discontinuities beneath the seismometer. Due to the limited number of events and the small epicentral distance range covered, inversions of the data are still ambiguous. Two sets of models can explain the waveforms, one consisting of a two-layer crust of about 20 to 23 km thickness, the other having a three-layer crust of about 40 to 45 km thickness. By excluding crustal thicknesses in excess of 45 km at the landing site, we can constrain the global average crustal thickness of Mars to be less than 70 km. Both model types also agree with S-receiver functions for two events and seismic P-waves reflected in the crust and extracted from autocorrelations using the coda of different types of marsquakes as well as the background wavefield. Furthermore, the results are compatible with independently conducted moment tensor inversions for a limited number of events as well as modeling of the wave-propagation of high-frequency events. We find low seismic P-wave velocities below 3.4 km/s within the upper approximately 10 km, likely indicating a high porosity. For the Moon, we present Sp-receiver functi

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's 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.

NASA's InSight mission arrived on Mars in November 2018 and deployed the first very broad-band seismometer, SEIS, on the planet's surface. SEIS has been collecting data continuously since early February 2019, by now recording more than 400 events of different types. InSight aims at enhancing our understanding of the internal structure and dynamics of Mars, including better constraints on its crustal thickness. Various models based on topography and gravity observed from the orbit currently vary in average crustal thickness from 30 km to more than 100 km, with important implications for Mars¿ thermal evolution, and the partitioning of silicates and heat-producing elements between different layers of Mars. We present P-to-S and S-to-P receiver functions, which are available for 4 and 3 marsquakes, respectively, up to now. Out of all of the marsquakes recorded to date, these are the only ones with clear enough P- or S-arrivals not dominated by scattering to make them suitable for the analysis. All of the quakes are located at comparatively small epicentral distances, between 25° and 40°. We observe three consistent phases within the first 10 seconds of the P-to-S receiver functions. The S-to-P receiver functions also show a consistent first phase. Later arrivals are harder to pinpoint, which could be due to the comparatively shallow incidence of the S-waves at the considered distances, which prevents the generation of converted waves. Identification of later multiple phases in the P-to-S receiver functions likewise remains inconclusive. To obtain better constraints on velocity, we also calculated apparent velocity curves from the P-to-S receiver functions, but these provide meaningful results for only one event so far, implying a large uncertainty. Due to difficulties in clearly identifying multiples, the receiver functions can currently be explained by either two crustal layers and a thin (25-30 km) crust or three crustal layers and a thicker (40-45 km) crust at the l