Oceanic lithosphere-asthenosphere boundaryfrom surface wave dispersion data

International audienceAbstract According to different types of observations, the nature of lithosphere-asthenosphereboundary (LAB) is controversial. Using a massive data set of surface wave dispersions in a broad periodrange (15–300 s), we have developed a three-dimensional upper mantle tomographic model (first-orderperturbation theory) at the global scale. This is used to derive maps of the LAB from the resolved elasticparameters. The key effects of shallow layers and anisotropy are taken into account in the inversion process.We investigate LAB distribution primarily below the oceans, according to different kinds of proxies thatcorrespond to the base of the lithosphere from the shear velocity variation at depth, the amplituderadial anisotropy, and the changes in azimuthal anisotropy G orientation. The estimations of the LAB depthbased on the shear velocity increase from a thin lithosphere (∼20 km) in the ridges, to a thick old-oceanlithosphere (∼120–130 km). The radial anisotropy proxy shows a very fast increase in the LAB depth fromthe ridges, from ∼50 km to the older ocean where it reaches a remarkable monotonic subhorizontal profile(∼70–80 km). The LAB depths inferred from the azimuthal anisotropy proxy show deeper values for theincreasing oceanic lithosphere (∼130–135 km). The difference between the evolution of the LAB depth withthe age of the oceanic lithosphere computed from the shear velocity and azimuthal anisotropy proxies andfrom the radial anisotropy proxy raises questions about the nature of the LAB in the oceanic regions and ofthe formation of the oceanic plate

The influence of gravity on granular impacts II. A gravity-scaled collision model for slow interactions

Slow interactions on small body surfaces occur both naturally and through human intervention. The resettling of grains and boulders following a cratering event, as well as observations made during small body missions, can provide clues regarding the material properties and the physical evolution of a surface. In order to analyze such events, it is necessary to understand how gravity influences granular behavior. In this work, we study slow impacts into granular materials for different collision velocities and gravity levels. Our objectives are to develop a model that describes penetration depth in terms of the dimensionless Froude number and to use this model to understand the relationship between collision behavior, collision velocity, and gravity. We use the soft-sphere discrete element method to simulate impacts into glass beads under gravitational accelerations ranging from 9.81 m/s^2 to 0.001 m/s^2. We quantify collision behavior using the peak acceleration, the penetration depth, and the collision duration of the projectile, and we compare the collision behavior for impacts within a Froude number range of 0 to 10. The measured penetration depth and collision duration for low-velocity collisions are comparable when the impact parameters are scaled by the Froude number, and the presented model predicts the collision behavior well within the tested Froude number range. If the impact Froude number is low (0 < Fr < 1.5), the collision occurs in a regime that is dominated by a depth-dependent quasi-static friction force. If the impact Froude number is high enough (1.5 < Fr < 10), the collision enters a second regime that is dominated by inertial drag. The presented collision model can be used to constrain the properties of a granular surface material using the penetration depth measurement from a single impact event. If the projectile size, the collision velocity, the gravity level, and the final penetration depth are known and the material density is estimated, then the internal friction angle of the material can be deduced

Low-velocity impacts into granular material: application to small-body landing

With the flourishing number of small body missions that involve surface interactions, understanding the mechanics of spacecraft - surface interactions is crucial for improving our knowledge about the landing phases of space missions, for preparing spacecraft operations, and for interpreting the results of measurements made during the surface interactions. Given their regolith-covered surfaces, the process of landing on a small body can be considered as an impact at low-velocity onto a granular material in reduced-gravity. In order to study the influence of the surface material, projectile shape, and gravity on the collision dynamics we used two experimental configurations (one for terrestrial gravity experiments and one for reduced-gravity experiments) to perform low-velocity collisions into different types of granular materials: quartz sand, and two different sizes of glass beads (1.5 and 5 mm diameter). Both a spherical and a cubic projectile (with varying impact orientation) were used. The experimental data support a drag model for the impact dynamics composed of both a hydrodynamic drag force and quasi-static resistance force. The hydrodynamic and quasi-static contributions are related to the material frictional properties, the projectile geometry, and the gravity. The transition from a quasi-static to a hydrodynamical regime is shown to occur at lower impact velocities in reduced-gravity trials than in terrestrial gravity trials, indicating that regolith has a more fluid-like behaviour in low-gravity. The reduced quasi-static regime of a granular material under low-gravity conditions leads to a reduction in the strength, resulting in a decreased resistance to penetration and larger penetration depths

Lunar Seismology: An Update on Interior Structure Models

An international team of researchers gathered, with the support of the Interna- tional Space Science Institute (ISSI), (1) to review seismological investigations of the lunar interior from the Apollo-era and up until the present and (2) to re-assess our level of knowl- edge and uncertainty on the interior structure of the Moon. A companion paper (Nunn et al. in Space Sci. Rev., submitted) reviews and discusses the Apollo lunar seismic data with the aim of creating a new reference seismic data set for future use by the community. In this study, we first review information pertinent to the interior of the Moon that has become available since the Apollo lunar landings, particularly in the past ten years, from orbiting spacecraft, continuing measurements, modeling studies, and laboratory experiments. Fol- lowing this, we discuss and compare a set of recent published models of the lunar interior, including a detailed review of attenuation and scattering properties of the Moon. Common features and discrepancies between models and moonquake locations provide a first esti- mate of the error bars on the various seismic parameters. Eventually, to assess the influence of model parameterisation and error propagation on inverted seismic velocity models, an inversion test is presented where three different parameterisations are considered. For this purpose, we employ the travel time data set gathered in our companion paper (Nunn et al. in Space Sci. Rev., submitted). The error bars of the inverted seismic velocity models demon- strate that the Apollo lunar seismic data mainly constrain the upper- and mid-mantle struc- ture to a depth of ∼1200 km. While variable, there is some indication for an upper mantle low-velocity zone (depth range 100–250 km), which is compatible with a temperature gradi- ◦ent around 1.7 C/km. This upper mantle thermal gradient could be related to the presence of the thermally anomalous region known as the Procellarum Kreep Terrane, which contains a large amount of heat producing elements

The Seismic Experiment for Interior Structure (SEIS): Experiment Data Distribution

The six sensors of SEIS (The Seismic Experiment for Interior Structure) [- one of three primary instruments on NASA's Mars Lander Insight] cover a broad range of the seismic bandwidth, from 0.01 hertz to 50 hertz, with possible extension to longer periods. Data are transmitted in the form of three continuous VBB (Very Broad-Band) components at 2 samples per second (sps), an estimation of the short period (SP) energy content from the SP at 1 sps, and a continuous compound VBB/SP vertical axis at 10 sps. The continuous streams are augmented by requested event data with sample rates from 20 to 100 sps. SEIS data products are downlinked from the spacecraft in raw CCSDS (Consultative Committee for Space Data Systems) packets and converted to both the Standard for the Exchange of Earthquake Data (SEED) format files and ASCII tables (GeoCSV) for analysis and archiving. Metadata are available in dataless SEED and StionXML. Time series data (waveforms) are available in miniseed and GeoCSV. Data are distributed according to FDSN (Federation of Digital Seismograph Networks - http://www.fdsn.org) formats and interfaces. Wind, pressure and temperature data from the Auxiliary Payload Sensor Suite (APSS) will also be available in SEED format, and can be used for decorrelation and diagnostic purposes on SEIS

SEIS: Insight's Seismic Experiment for Internal Structure of Mars.

By the end of 2018, 42 years after the landing of the two Viking seismometers on Mars, InSight will deploy onto Mars' surface the SEIS (Seismic Experiment for Internal Structure) instrument; a six-axes seismometer equipped with both a long-period three-axes Very Broad Band (VBB) instrument and a three-axes short-period (SP) instrument. These six sensors will cover a broad range of the seismic bandwidth, from 0.01&nbsp;Hz to 50&nbsp;Hz, with possible extension to longer periods. Data will be transmitted in the form of three continuous VBB components at 2 sample per second (sps), an estimation of the short period energy content from the SP at 1&nbsp;sps and a continuous compound VBB/SP vertical axis at 10&nbsp;sps. The continuous streams will be augmented by requested event data with sample rates from 20 to 100 sps. SEIS will improve upon the existing resolution of Viking's Mars seismic monitoring by a factor of ∼ 2500 at 1&nbsp;Hz and ∼ 200 000 at 0.1&nbsp;Hz. An additional major improvement is that, contrary to Viking, the seismometers will be deployed via a robotic arm directly onto Mars' surface and will be protected against temperature and wind by highly efficient thermal and wind shielding. Based on existing knowledge of Mars, it is reasonable to infer a moment magnitude detection threshold of M w ∼ 3 at 40 ∘ epicentral distance and a potential to detect several tens of quakes and about five impacts per year. In this paper, we first describe the science goals of the experiment and the rationale used to define its requirements. We then provide a detailed description of the hardware, from the sensors to the deployment system and associated performance, including transfer functions of the seismic sensors and temperature sensors. We conclude by describing the experiment ground segment, including data processing services, outreach and education networks and provide a description of the format to be used for future data distribution.Electronic supplementary materialThe online version of this article (10.1007/s11214-018-0574-6) contains supplementary material, which is available to authorized users

The Polarization of Ambient Noise on Mars

Seismic noise recorded at the surface of Mars has been monitored since February 2019, using the InSight seismometers. This noise can reach −200 dB. It is 500 times lower than on Earth at night and it increases of 30 dB during the day. We analyze its polarization as a function of time and frequency in the band 0.03–1 Hz. We use the degree of polarization to extract signals with stable polarization independent of their amplitude and type of polarization. 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 below 0.3 Hz. In the 0.3-1Hz high frequency band (HF) and except in the evening, the ellipse is in the vertical plane and the major axis is tilted. While polarization azimuths are different in the two frequency bands, they both vary as a function of local hour and season. They are also correlated with wind direction, particularly during the daytime. We investigate possible aseismic and seismic origins of the polarized signals. Lander or tether noise can be discarded. Pressure fluctuations transported by 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 coming from high altitude at critical angle. Finally, in the evening when the wind is low, the measured polarized signals may correspond to the seismic wavefield of the Mars background noise

Seismic detection of the martian core by InSight

A plethora of geophysical, geo- chemical, and geodynamical observations indicate that the terrestrial planets have differentiated into silicate crusts and mantles that surround a dense core. The latter consists primarily of Fe and some lighter alloying elements (e.g., S, Si, C, O, and H) [1]¿. The Martian meteorites show evidence of chalcophile element depletion, suggesting that the otherwise Fe-Ni- rich core likely contains a sulfide component, which influences physical state

Seismic detection of the martian core

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.This is InSight contribution 200. We acknowledge NASA, CNES, and partner agencies and institutions (UKSA, SSO, ESA-PRODEX, DLR, JPL, IPGP-CNRS, ETHZ, IC, and MPS-MPG) for the development of SEIS. Numerical simulations were supported by a grant from the Swiss National Supercomputing Centre (CSCS) under project ID s922 as well as HPC resources of CINES under the allocation A0090407341, made by GENCI. We thank B. Dintrans, director of CINES, for his efficient handling of our request for computational time. Figures were created using matplotlib (83), seismic data processing was done in ObsPy (84), and numerical evaluation was done in NumPy and SciPy (85, 86). Funding: S.C.S., A.K., D.G., J.C., A.C.D., G.Z., and N.D. acknowledge support from ETHZ through the ETH+ funding scheme (ETH+2 19-1: “Planet MARS”). S.C.S. acknowledges funding from ETH research grant ETH-10 17-3. W.B.B., A.G.M., M.P.P., and S.E.S. were supported by the NASA InSight mission and funds from the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). D.A. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement 724690). The French teams acknowledge support from CNES as well as Agence Nationale de la Recherche (ANR-14-CE36-0012-02 and ANR-19-CE31-0008-08). A.R. was financially supported by the Belgian PRODEX program managed by the European Space Agency in collaboration with the Belgian Federal Science Policy Office. M.S. wishes to thank SANIMS (RTI2018-095594-B-I00). M.v.D. received support from the ERC under the European Union’s Horizon 2020 program (grant no. 714069). D.S. and C.S. acknowledge funding from ETH research grant ETH-06 17-02. J.C.E.I. acknowledges support from NASA grant 80NSSC18K1633. N.S., D.K., Q.H., R.M., V.L., and A.G.M. acknowledge NASA grant 80NSSC18K1628 for support. V.L. acknowledges support from the Packard Foundation. W.T.P. and C.C. received funding from the UK Space Agency, grant ST/S001239/1. A.H. was funded by the UK Space Agency (grant ST/R002096/1). A.-C.P. acknowledges the financial support and endorsement from the DLR Management Board Young Research Group Leader Program and the Executive Board Member for Space Research and Technology. Author contributions: S.C.S., D.G., S.C., R.F.G., Q.H., D.K., V.L., M.S., N.S., D.S., É.S., C.S., and G.Z. analyzed the seismic data and made ScS arrival time picks. S.C.S., P.L., D.G., Z.X., C.C., and W.T.P. performed the statistical analysis of the observed signals. S.C.S., Q.H., N.S., R.M., and A.G.M. identified the arrivals as ScS waves based on interior models from A.K., H.S., and A.R. A.K., M.D., A.C.D., and H.S. performed the inversions. S.C.S., A.K., P.L., D.G., D.A., J.C.E.I., M.K., C.P., A.-C.P., A.R., T.G., and S.E.S. participated and contributed to the interpretation of the results. Review of the continuous data and detection of marsquakes was done by S.C.S., S.C., G.Z., C.C., N.D., J.C., M.v.D., T.K., M.P., and A.H. with operational support by É.B., C.P., and P.M.D. S.C.S. and A.K. wrote the central part of the paper with contributions from H.S., N.S., D.A., J.C.E.I., A.G.M., A.-C.P., A.R., J.C., and M.v.D. J.C.E.I., R.M., M.K., and V.L. reviewed the contributions to the supplementary materials. The InSight mission is managed by W.B.B., M.P.P., and S.E.S. The SEIS instrument development was led by P.L., D.G., W.T.P., and W.B.B. Supplementary section 1 was written by M.S., D.S., and É.S. with contributions from S.C.S., C.S., and Z.X. Supplementary section 2 was written by D.K. and V.L. with contributions from J.C.E.I. and N.S. Supplementary section 3 was written by M.S. and É.S. Supplementary section 4 was written by R.F.G. with contributions from M.D. Supplementary section 5 was written by Q.H. with contributions from N.S. Supplementary section 6 was written by S.C.S. with contributions from the authors of the other supplements. Supplementary section 7 was written by Z.X. and C.C. with contributions from P.L. and W.T.P. Supplementary section 8 was written by A.K., M.D., A.C.D., and H.S. Supplementary section 9 was written by M.D. Supplementary section 10 was written by A.C.D., A.K., and M.D. Supplementary section 11 was written by D.A. and A.R. with contributions from A.K. Competing interests: The authors declare that they have no competing interests. Data and materials availability: We thank the operators of JPL, SISMOC, MSDS, IRIS-DMC, and PDS for providing SEED SEIS data (87). Three hundred interior models derived in this study are available from MSDS (88)