T he Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission landed on Mars on 26 November 2018 in Elysium Planitia 1,2 , 38 years after the end of Viking 2 lander operations. At the time, Viking's seismometer 3 did not succeed in making any convincing Marsquake detections, due to its on-deck installation and high wind sensitivity. InSight therefore provides the first direct geophysical in situ investigations of Mars's interior structure by seismology 1,4. The Seismic Experiment for Interior Structure (SEIS) 5 monitors the ground acceleration with six axes: three Very Broad Band (VBB) oblique axes, sensitive to frequencies from tidal up to 10 Hz, and one vertical and two horizontal Short Period (SP) axes, covering frequencies from ~0.1 Hz to 50 Hz. SEIS is complemented by the APSS experiment 6 (InSight Auxiliary Payload Sensor Suite), which includes pressure and TWINS (Temperature and Winds for InSight) sensors and a magnetometer. These sensors monitor the atmospheric sources of seismic noise and signals 7. After seven sols (Martian days) of SP on-deck operation, with seismic noise comparable to that of Viking 3 , InSight's robotic arm 8 placed SEIS on the ground 22 sols after landing, at a location selected through analysis of InSight's imaging data 9. After levelling and noise assessment, the Wind and Thermal Shield was deployed on sol 66 (2 February 2019). A few days later, all six axes started continuous seismic recording, at 20 samples per second (sps) for VBBs and 100 sps for SPs. After onboard decimation, continuous records at rates from 2 to 20 sps and event records 5 at 100 sps are transmitted. Several layers of thermal protection and very low self-noise enable the SEIS VBB sensors to record the daily variation of the

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.

Analyses of seismic data from the InSight mission have provided the first in situ constraints on the thickness of the crust of Mars. These crustal thickness constraints are currently limited to beneath the lander that is located in the northern lowlands, and we use gravity and topography data to construct global crustal thickness models that satisfy the seismic data. These models consider a range of possible mantle and core density profiles, a range of crustal densities, a low-density surface layer, and the possibility that the crustal density of the northern lowlands is greater than that of the southern highlands. Using the preferred InSight three-layer seismic model of the crust, the average crustal thickness of the planet is found to lie between 30 and 72 km. Depending on the choice of the upper mantle density, the maximum permissible density of the northern lowlands and southern highlands crust is constrained to be between 2,850 and 3,100 kg m −3 . These crustal densities are lower than typical Martian basaltic materials and are consistent with a crust that is on average more felsic than the materials found at the surface. We argue that a substantial portion of the crust of Mars is a primary crust that formed during the initial differentiation of the planet. Various hypotheses for the origin of the observed intracrustal seisimic layers are assessed, with our preferred interpretation including thick volcanic deposits, ejecta from the Utopia basin, porosity closure, and differentiation products of a Borealis impact melt sheet. Plain Language SummaryThe crust, mantle and core are the three major geochemical layers that make up a planet. Before NASA's InSight mission, the thickness of the crust of Mars was inferred using indirect techniques, including analyses of gravity data collected from orbit and the composition of surface rocks. Estimates for the average thickness using these techniques spanned the range from 27 to 118 km. Analyses of data collected by the InSight seismometer have provided us with the first direct seismic measurement of the thickness of the crust, but this measurement is only for beneath the lander that is located in the northern lowlands where the crust is expected to be thinner than average. In this work, gravity and topography data are used to construct global crustal thickness models that satisfy the new seismic constraints. The average crustal thickness is found to be somewhere between 32 and 70 km, and the average density of the crust can be no larger than 3,100 kg m −3 . This bulk crustal density is lower than most typical Martian WIECZOREK ET AL.

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". Glitches show up in the recorded data as one-sided pulses and have strong implications for the typical seismic data analysis. Glitches can be understood as step-like changes in the acceleration sensed by the seismometers. We attribute them 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 whole SEIS instrument. In this study, we focus on the detection and removal of glitches and anticipate

We detected surface waves from two meteorite impacts on Mars. By measuring group velocity dispersion along the impact-lander path, we obtained a direct constraint on crustal structure away from the InSight lander. The crust north of the equatorial dichotomy had a shear wave velocity of approximately 3.2 kilometers per second in the 5- to 30-kilometer depth range, with little depth variation. This implies a higher crustal density than inferred beneath the lander, suggesting either compositional differences or reduced porosity in the volcanic areas traversed by the surface waves. The lower velocities and the crustal layering observed beneath the landing site down to a 10-kilometer depth are not a global feature. Structural variations revealed by surface waves hold implications for models of the formation and thickness of the martian crust.

Seismological constraints obtained from receiver function (RF) analysis provide important information about the crust and mantle structure. Here, we explore the utility of the free‐surface multiple of the P‐wave (PP) and the corresponding conversions in RF analysis. Using earthquake records, we demonstrate the efficacy of PPs‐RFs before illustrating how they become especially useful when limited data is available in typical planetary missions. Using a transdimensional hierarchical Bayesian deconvolution approach, we compute robust P‐to‐S (Ps)‐ and PPs‐RFs with InSight recordings of five marsquakes. Our Ps‐RF results verify the direct Ps converted phases reported by previous RF analyses with increased coherence and reveal other phases including the primary multiple reverberating within the uppermost layer of the Martian crust. Unlike the Ps‐RFs, our PPs‐RFs lack an arrival at 7.2 s lag time. Whereas Ps‐RFs on Mars could be equally well fit by a two‐ or three‐layer crust, synthetic modeling shows that the disappearance of the 7.2 s phase requires a three‐layer crust, and is highly sensitive to velocity and thickness of intra‐crustal layers. We show that a three‐layer crust is also preferred by S‐to‐P (Sp)‐RFs. While the deepest interface of the three‐layer crust represents the crust‐mantle interface beneath the InSight landing site, the other two interfaces at shallower depths could represent a sharp transition between either fractured and unfractured materials or thick basaltic flows and pre‐existing crustal materials. PPs‐RFs can provide complementary constraints and maximize the extraction of information about crustal structure in data‐constrained circumstances such as planetary missions.

SEIS, the seismometer of the InSight mission, which landed on Mars on 26 November 2018, is monitoring the seismic activity of the planet. The goal of the Mars Structure Service (MSS) is to provide, as a mission product, the first average 1-D velocity model of Mars from the recorded InSight data. Prior to the mission, methodologies have been developed and tested to allow the location of the seismic events and estimation of the radial structure, using surface waves and body waves arrival times, and receiver functions. The paper describes these validation tests and compares the performance of the different algorithms to constrain the velocity model below the InSight station and estimate the 1-D average model over the great circle path between source and receiver. These tests were performed in the frame of a blind test, during which synthetic data were inverted. In order to propagate the data uncertainties on the output model distribution, Bayesian inversion techniques are mainly used. The limitations and strengths of the methods are assessed. The results show the potential of the MSS approach to retrieve the structure of the crust and underlying mantle. However, at this time, large quakes with clear surface waves have not yet been recorded by SEIS, which makes the estimation of the 1-D average seismic velocity model challenging. Additional locatable events, especially at large epicentral distances, and development of new techniques to fully investigate the data, will ultimately provide more constraints on the crust and mantle of Mars.

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". Glitches show up in the recorded data as one-sided pulses and have strong implications for the typical seismic data analysis. Glitches can be understood as step-like changes in the acceleration sensed by the seismometers. We attribute them 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 whole SEIS instrument. In this study, we focus on the detection and removal of glitches and anticipate