Single seismometer structure Because of the lack of direct seismic observations, the interior structure of Mars has been a mystery. Khan et al., Knapmeyer-Endrun et al., and Stähler et al. used recently detected marsquakes from the seismometer deployed during the InSight mission to map the interior of Mars (see the Perspective by Cottaar and Koelemeijer). Mars likely has a 24- to 72-kilometer-thick crust with a very deep lithosphere close to 500 kilometers. Similar to the Earth, a low-velocity layer probably exists beneath the lithosphere. The crust of Mars is likely highly enriched in radioactive elements that help to heat this layer at the expense of the interior. The core of Mars is liquid and large, ∼1830 kilometers, which means that the mantle has only one rocky layer rather than two like the Earth has. These results provide a preliminary structure of Mars that helps to constrain the different theories explaining the chemistry and internal dynamics of the planet. Science, abf2966, abf8966, abi7730, this issue p. 434, p. 438, p. 443 see also abj8914, p. 388 Data from the InSight mission on Mars help constrain the structure and properties of the martian interior. For 2 years, the InSight lander has been recording seismic data on Mars that are vital to constrain the structure and thermochemical state of the planet. We used observations of direct (P and S) and surface-reflected (PP, PPP, SS, and SSS) body-wave phases from eight low-frequency marsquakes to constrain the interior structure to a depth of 800 kilometers. We found a structure compatible with a low-velocity zone associated with a thermal lithosphere much thicker than on Earth that is possibly related to a weak S-wave shadow zone at teleseismic distances. By combining the seismic constraints with geodynamic models, we predict that, relative to the primitive mantle, the crust is more enriched in heat-producing elements by a factor of 13 to 20. This enrichment is greater than suggested by gamma-ray surface mapping and has a moderate-to-elevated surface heat flow.

Single seismometer structure Because of the lack of direct seismic observations, the interior structure of Mars has been a mystery. Khan et al., Knapmeyer-Endrun et al., and Stähler et al. used recently detected marsquakes from the seismometer deployed during the InSight mission to map the interior of Mars (see the Perspective by Cottaar and Koelemeijer). Mars likely has a 24- to 72-kilometer-thick crust with a very deep lithosphere close to 500 kilometers. Similar to the Earth, a low-velocity layer probably exists beneath the lithosphere. The crust of Mars is likely highly enriched in radioactive elements that help to heat this layer at the expense of the interior. The core of Mars is liquid and large, ∼1830 kilometers, which means that the mantle has only one rocky layer rather than two like the Earth has. These results provide a preliminary structure of Mars that helps to constrain the different theories explaining the chemistry and internal dynamics of the planet. Science, abf2966, abf8966, abi7730, this issue p. 434, p. 438, p. 443 see also abj8914, p. 388 Data from the InSight mission on Mars help constrain the structure and properties of the martian mantle. 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.

Single seismometer structure Because of the lack of direct seismic observations, the interior structure of Mars has been a mystery. Khan et al., Knapmeyer-Endrun et al., and Stähler et al. used recently detected marsquakes from the seismometer deployed during the InSight mission to map the interior of Mars (see the Perspective by Cottaar and Koelemeijer). Mars likely has a 24- to 72-kilometer-thick crust with a very deep lithosphere close to 500 kilometers. Similar to the Earth, a low-velocity layer probably exists beneath the lithosphere. The crust of Mars is likely highly enriched in radioactive elements that help to heat this layer at the expense of the interior. The core of Mars is liquid and large, ∼1830 kilometers, which means that the mantle has only one rocky layer rather than two like the Earth has. These results provide a preliminary structure of Mars that helps to constrain the different theories explaining the chemistry and internal dynamics of the planet. Science, abf2966, abf8966, abi7730, this issue p. 434, p. 438, p. 443 see also abj8914, p. 388 Data from the InSight mission on Mars help constrain the structure and properties of the martian interior. Clues to a planet’s geologic history are contained in its interior structure, particularly its core. We detected reflections of seismic waves from the core-mantle boundary of Mars using InSight seismic data and inverted these together with geodetic data to constrain the radius of the liquid metal core to 1830 ± 40 kilometers. The large core implies a martian mantle mineralogically similar to the terrestrial upper mantle and transition zone but differing from Earth by not having a bridgmanite-dominated lower mantle. We inferred a mean core density of 5.7 to 6.3 grams per cubic centimeter, which requires a substantial complement of light elements dissolved in the iron-nickel core. The seismic core shadow as seen from InSight’s location covers half the surface of Mars, including the majority of potentially active regions—e.g., Tharsis—possibly limiting the number of detectable marsquakes.

<p>The scattering of seismic waves is the signature of random heterogeneities, present in the lithospheric structure of a terrestrial planet. It is the result of refraction and reflection of the seismic waves generated by a quake, when they cross materials with different shear rigidity, bulk modulus, and density and therefore different seismic wave velocities, compared to the ambient space. &#160;On Earth, the seismic waves show relatively weak scattering, identified in later arriving coda waves that follow the main arrivals of body waves and decay with time. In contrast, seismic wave scattering is much more significant on the Moon, where the high heterogeneous structure of the lunar megaregolith, produced through millions of years of impact bombardment, is a structure that creates an extreme scattering environment.</p> <p>The landing of the NASA InSight mission on Mars in 2018, which carried and deployed a seismometer for the first time on the Martian ground, offered a pristine dataset for the investigation and analysis of the characteristics of the scattering attenuation of the Martian crust and uppermost mantle which is important for understanding the structure of the Martian interior. Lognonn&#233; et al. (2020) used a methodology based on the radiative transfer model (Margerin et al., 1998) to offer the first constraints for the scattering and attenuation in the Martian crust. In this study, we performed a further examination based on more and newer events of the Martian Seismic Catalog (InSight Marsquake Service, 2021).</p> <p>The Marsquake Catalog contains events that are categorized according to the frequency content of the seismic signal (Clinton et al., 2021). In this study, we used 19 events of 4 different families, namely the Low Frequency, Broadband, High Frequency, and Very High Frequency events, for our investigation. We focused our investigation on the characteristics of the S-coda waveforms and for this reason, we worked on the respective energy envelopes. We manually picked the envelopes, defining the time window of the S-coda waves, as well the frequency range for each event, directly from the spectrograms of the events' signals, using an appropriately developed visual tool.</p> <p>We used a modeling approach (Dainty et al., 1974) that was developed for the computation of the energy envelopes of shallow events (Lunar impacts) and a diffusive, highly scattering layer, sitting over an elastic half-space. The energy envelope depends on the thickness of the diffusive layer, the range of the seismic ray, the diffusivity and the attenuation in the top layer, and the seismic wave velocity in the underneath elastic half-space. We analyzed all the tradeoffs between the terms of the modeling equation, namely the geometrical relationship of the velocity contrast between the diffusive layer and the elastic half-space with the seismic ray range and the diffusive layer thickness, the diffusivity with the diffusive layer thickness, and between the diffusivity and the velocity contrast of the two examined layers.</p> <p>The presence of the aforementioned tradeoffs made the definition of a unique model a very hard task, as the information for the azimuthal characteristics of the signal is not available for the examined events. This is a limitation that exists in seismology only while working with one station, with the InSight seismometer being the only station on a planet, and the amplitude of the seismic signal is not big enough to perform a specific polarization analysis and derive the azimuthal origin of the recorded signal. For this reason, we reviewed the fit between the modeling and the data, depending on the frequency content of the events.</p> <p>The Low Frequency and the Broadband events, which have a frequency content mainly below the tick noise detected at 1 Hz, could not satisfy the modeling approach of a simple diffusive layer. The spectral envelopes of the S-coda waves of these events are decaying very rapidly, which suggests an origin in a more elastic environment. This is in agreement with previous studies (Giardini et al., 2020) that suggest that these events are generated deeper in the Martian mantle. For this reason, we applied another approach to these signals, with an energy envelope equation designed for deep moonquakes (Dainty et al.,1974), but it was not either capable to fit the examined data envelopes, suggesting the absence of a very thick megaregolith structure on Mars.</p> <p>Based on the results of the High Frequency (HF) and Very High Frequency (VF) events we observed a range of possible paths and diffusivities that can satisfy the data and we investigated the tradeoffs between the parameters of a modeling equation that control the shape of the energy envelope for the events. The analysis of these tradeoffs does not permit us to make any assumptions about the depth of the diffusive region in the Martian crust and the upper mantle as their azimuthal characteristics are unknown and therefore it is not feasible to tell if the difference in the result analysis reflects vertical or lateral variations of the uppermost diffusive layer in the Martian lithosphere.</p> <p>The results of this study illustrate one of the challenges in working with single-station seismic data where event location information, including distance, azimuth, and depth are crucial for understanding the lateral variation in seismic properties of a planet. The existence of a seismic network on the planetary scale will improve the ability of phase peaking and location identification of the events and therefore it will give additional constraints for a similar analysis.</p> <p>References</p> <p>Clinton, J. F. et al. (2021). The Marsquake catalogue from InSight, sols 0&#8211;478.Phys Earth Planet In, 310:106595.</p> <p>Dainty, &#160;A. M. et al. (1974). Seismic scattering and shallow structure of the Moon in Oceanus Procellarum.The Moon,9(1-2):11&#8211;29.</p> <p>Giardini, D. et al. (2020). The seismicity of Mars.Nat Geosci, 13(3):205&#8211;212.InSight Marsquake Service (2021).&#160;</p> <p>Mars Seismic Catalogue, InSight Mission; V5 2021-01-04.</p> <p>Lognonn&#233;, P. et al. (2020). &#160;Constraints on the shallow elastic and anelastic structure of Mars from InSight seismic data.NatGeosci, 13(3):213&#8211;220.</p> <p>Margerin, L. et al. (1998). &#160;Radiative transfer and diffusion of waves in a layered medium: new insight into coda Q.GeophysJ Int, 134(2):596&#8211;612.</p>

Mapping variations in the attenuation of seismic energy is important for understanding dissipative mechanisms in the lithosphere, and for modeling ground shaking associated with earthquakes. We cross-correlate ambient seismic signal recorded across the EarthScope Transportable Array in the 3–15 s period range. We apply to the resulting cross correlations a new method to estimate lateral variations in Rayleigh-wave attenuation, as a function of period, beneath North America. Between 3 and 6 s, our maps are dominated by a strong eastward decrease in attenuation. This pattern vanishes at longer periods, confirming early observations based on regional earthquakes. Attenuation maps and phase-velocity maps are anti-correlated at periods between 3 and 6 s, but the anti-correlation is also largely lost at longer periods. This corresponds to the attenuation coefficient decreasing with period more rapidly in the west than in the east, while the change in phase velocity with period is more uniform across the continent. Our results point to a transition in the properties of upper-crustal materials with depth, probably related to the closure of fluid-filled cracks and pores, and imply that measures of attenuation from seismic noise carry significant information on crustal rheology.

The critical zone (CZ) is the region of the Earth’s surface that extends from the bottom of the weathered bedrock to the tree canopy and is important because of its ability to store water and support ecosystems. A growing number of studies use active source shallow seismic refraction to explore and define the size and structure of the CZ across landscapes. However, measurement uncertainty and model resolution at depth are generally not evaluated, which makes the identification and interpretation of CZ features inconclusive. To reliably resolve seismic velocity with depth, we implement a Transdimensional Hierarchical Bayesian (THB) framework with reversible‐jump Markov Chain Monte Carlo to generate samples from the posterior distribution of velocity structures. We also perform 2D synthetic tests to explore how well THB traveltime inversion can resolve different subsurface velocity structures. We find that THB recovers both sharp changes in velocity as well as gradual velocity increases with depth. Furthermore, we explore the velocity structure in a series of ridge‐valley systems in northern California. The posterior velocity model shows an increasing thickness of low velocity material from channels to ridgetops along a transect parallel to bedding strike, implying a deeper weathering zone below ridgetops and hillslopes than below channels. The THB method enhances the ability to reliably image CZ structure, and the model uncertainty estimates it yields provides an objective way to interpret deep CZ structure. The method can be applied across other near‐surface studies, especially in the presence of significant surface topography.

Mars is the first extraterrestrial planet with seismometers (Seismic Experiment for Interior Structure, SEIS) deployed directly on its surface in the framework of the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission. The lack of strong Marsquakes, however, strengthens the need of seismic noise studies to additionally constrain the Martian structure. Seismic noise autocorrelations of single‐station recordings permit the determination of the zero‐offset reflection response underneath SEIS. We present a new autocorrelation study which employs state‐of‐the‐art approaches to determine a robust reflection response by avoiding bias from aseismic signals which are recorded together with seismic waves due to unfavorable deployment and environmental conditions. Data selection and segmentation is performed in a data‐adaptive manner which takes the data root‐mean‐square amplitude variability into account. We further use the amplitude‐unbiased phase cross‐correlation and work in the 1.2–8.9 Hz frequency band. The main target are crustal scale reflections, their robustness and convergence. The strongest signal appears at 10.6 s, and, if interpreted as a P‐wave reflection, would correspond to a discontinuity at about 21 km depth. This signal is a likely candidate for a reflection from the base of the Martian crust due to its strength, polarity, and stability. Additionally we identify, among the stable signals, a signal at about 6.15 s that can be interpreted as the P‐wave reflection from the mid‐crust at about 9.5 km depth.

<p>The InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) lander successfully delivered a geophysical instrument package to the Martian surface on November 26, 2018, including a broadband seismometer called SEIS (Seismic Experiment for Interior Structure). After two years of recording, seismic body waves phases of a small number of high-quality marsquakes have been clearly identified. In this work, we will present how we estimate the body waves arrival times, and how we handle them to constrain the locations of the marsquakes and the interior structure. The inverse problem relies on a Bayesian approach, to investigate a large range of possible locations and interior models. Due to the small number of data, the advantage of using such a method is to provide a quantitative measure of the uncertainties and the non-uniqueness. In order to take into account the strong variations of the crustal thickness due to the crustal dichotomy, and thus consider the seismic lateral variations, which could cause significant misinterpretations, arrival times corrections are added using crustal thickness maps obtained from gravity and topography data.</p><p>&#160;</p>

<p>Since InSight (the Interior Exploration using Geodesy and Heat Transport) landed 26 months ago and deployed an ultra sensitive broadband seismometer(SEIS) on the surface of Mars, around 500 seismic events of diverse variety have been detected, making it possible to directly analyze the subsurface properties of Mars for the very first time. One of the primary goals of the mission is to retrieve the crustal structure below the landing site. Current estimates differ by more than 100% for the average crustal thickness. Since data from orbital gravity measurementsprovide information on relative variations of crustal thickness but not absolute values, this landing site measurement could serve as a tie point to retrieve global crustal structure models. To do so, we propose using a joint inversion of receiver functions and apparent incidence angles, which contain information on absolute S-wave velocities of the subsurface. Since receiver function inversions suffer from a velocity depth trade-off, we in addition exploit a simple relation which defines apparent S-wave velocity as a function of observed apparent P-wave incidence angles to constrain the parameter space. Finally we use the Neighbourhood Algorithm for the inversion of a suitable joint objective function. The resulting ensemble of models is then used to derive the full uncertainty estimates for each model parameter. Before its application on data from InSight mission, we successfully tested the method on Mars synthetics and terrestrial data from various geological settings using both single and multiple events. Using the same method, we have previously been able to constrain the S-wave velocity and depth for the first inter-crustal layer of Mars between 1.7 to 2.1 km/s and 8 to 11 km, respectively. Here we present the results of applying this technique on our selected data set from the InSight mission. Results show that the data can be explained equally well by models with 2 or 3 crustal layers with constant velocities. Due to the limited data set it is difficult to resolve the ambiguity of this bi-modal solution. We therefore investigate information theoretic statistical tests as a model selection criteria and discuss their relevance and implications in seismological framework.</p><div></div><div></div><div></div>

The long‐wavelength geoid is sensitive to Earth's mantle density structure as well as radial variations in mantle viscosity. We present a suite of inversions for the radial viscosity profile using whole‐mantle models that jointly constrain the variations in density, shear‐ and compressional‐wavespeeds using full‐spectrum tomography. We use a Bayesian approach to identify a collection of viscosity profiles compatible with the geoid, while enabling uncertainties to be quantified. Depending on tomographic model parameterization and data weighting, it is possible to obtain models with either positive‐ or negative‐buoyancy in the large low shear velocity provinces. We demonstrate that whole‐mantle density models in which density and VS variations are correlated imply an increase in viscosity below the transition zone, often near 1,000 km. Many solutions also contain a low‐viscosity channel below 650 km. Alternatively, models in which density is less‐correlated with VS—which better fit normal mode data—require a reduced viscosity region in the lower mantle. This feature appears in solutions because it reduces the sensitivity of the geoid to buoyancy variations in the lowermost mantle. The variability among the viscosity profiles obtained using different density models is indicative of the strong nonlinearities in modeling the geoid and the limited resolving power of the geoid kernels. We demonstrate that linearized analyses of model resolution do not adequately capture the posterior uncertainty on viscosity. Joint and iterative inversions of viscosity, wavespeeds, and density using seismic and geodynamic observations are required to reduce bias from prior assumptions on viscosity variation and scalings between material properties.