SUMMARY
Mapping the elastic and anelastic structure of the Earth's mantle is crucial for understanding the temperature, composition and dynamics of our planet. In the past quarter century, global ...tomography based on ray theory and first‐order perturbation methods has imaged long‐wavelength elastic velocity heterogeneities of the Earth's mantle. However, the approximate techniques upon which global tomographers have traditionally relied become inadequate when dealing with crustal structure, as well as short‐wavelength or large amplitude mantle heterogeneity. The spectral element method, on the other hand, permits accurate calculation of wave propagation through highly heterogeneous structures, and is computationally economical when coupled with a normal mode solution and applied to a restricted region of the Earth such as the upper mantle (SEM). Importantly, SEM allows a dramatic improvement in accounting for the effects of crustal structure. Here, we develop and apply a new hybrid method of tomography, which allows us to leverage the accuracy of SEM to model fundamental and higher‐mode long period (>60 s) waveforms. We then present the first global model of upper‐mantle velocity and radial anisotropy developed using SEM. Our model, SEMum, confirms that the long‐wavelength mantle structure imaged using approximate semi‐analytic techniques is robust and representative of the Earth's true structure. Furthermore, it reveals structures in the upper mantle that were not clearly seen in previous global tomographic models. We show that SEMum favourably compares to and rivals the resolving power of continental‐scale studies. This new hybrid approach to tomography can be applied to a larger and higher‐frequency data set in order to gain new insights into the structure of the lower mantle and more robustly map seismic structure at the regional and smaller scales.
Sequencing for seismic structures
Structures illuminated by seismic waves at the core-mantle boundary of the Earth are traditionally found by focusing on a specific target area. Kim
et al.
used an ...unsupervised manifold learning algorithm called “the Sequencer” to automatically detect anomalies in seismic data (see the Perspective by Miller). Using this technique, they uncovered structures at the core-mantle boundary across the entire Pacific region all at once. They found many structures previously identified, but also a new, ultra-low-velocity zone beneath the Marquesas Islands.
Science
, this issue p.
1223
; see also p.
1183
An unsupervised machine learning algorithm uncovers the structure of the core-mantle boundary region under the Pacific.
Scattering of seismic waves can reveal subsurface structures but usually in a piecemeal way focused on specific target areas. We used a manifold learning algorithm called “the Sequencer” to simultaneously analyze thousands of seismograms of waves diffracting along the core-mantle boundary and obtain a panoptic view of scattering across the Pacific region. In nearly half of the diffracting waveforms, we detected seismic waves scattered by three-dimensional structures near the core-mantle boundary. The prevalence of these scattered arrivals shows that the region hosts pervasive lateral heterogeneity. Our analysis revealed loud signals due to a plume root beneath Hawaii and a previously unrecognized ultralow-velocity zone beneath the Marquesas Islands. These observations illustrate how approaches flexible enough to detect robust patterns with little to no user supervision can reveal distinctive insights into the deep Earth.
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.
Plain Language Summary
The viscosity of Earth's mantle affects nearly every aspect of Earth's evolution, including its convective vigor and rate of cooling, the motion of mantle plumes and subducted oceanic lithosphere through the mantle, and the deep volatile cycle. We use the long‐wavelength geoid to constrain the variation of mantle viscosity with depth. In so doing, we use newly available whole‐mantle models of seismic wavespeeds and density that incorporate constraints on the lowermost mantle density from the free oscillations of the Earth. We find evidence for an increase in viscosity within the mid mantle and for a low‐viscosity region below the mantle transition zone. We demonstrate that depending on choices made in the data weighting and regularization of tomographic models, it is possible to obtain solutions that include a reduced viscosity region in the lower mantle as well. We argue that in joint inversions of seismic and geodynamic observations, viscosity variations must be solved for together with wavespeed and density variations, and should not be assumed a priori.
Key Points
We model mantle flow with density variations from full‐spectrum tomography
We generate Bayesian estimates of the radial viscosity profile with uncertainties
There is evidence for a low‐viscosity channel below the transition zone and a viscosity increase in the mid mantle
The largest seismic event ever recorded on Mars, with a moment magnitude of 4.7 ± 0.2, is the first event to produce both Love and Rayleigh wave signals. We measured their group velocity dispersion ...between about 15 and 40 s period and found that no isotropic depth‐dependent velocity model could explain the two types of waves wave simultaneously, likely indicating the presence of seismic anisotropy. Inversions of Love and Rayleigh waves yielded velocity models with horizontally polarized shear waves traveling faster than vertically polarized shear waves in the top 10–25 km. We discuss the possible origins of this signal, including the preferred orientation of anisotropic crystals due to shear deformation, alignment of cracks, layered intrusions due to an impact, horizontal layering due to the presence of a large‐scale sediment layer on top of the crust, and alternation of sedimentation and basalt layers deposits due to large volcanic eruptions.
Plain Language Summary
The largest marsquake recorded so far sent energy across the red planet in the form of different kinds of waves, including two types of waves trapped near the surface. This was the first time both types of so‐called surface waves were detected on Mars. Combining measurements from these two types of surface waves allowed us to determine the speed of other types of waves, that is, waves that travel horizontally and that make rocks move perpendicular to the direction of propagation. We found that these waves move faster in the crust between 10 and 25 km depth when the rocks oscillate in a direction sub‐parallel to the planet surface than if the rocks vibrate in the vertical direction. This wave speed dependence can tell us about deformation mechanisms inside the crust. We found that either an alternation of volcanic rocks and sediments layers due to volcanic eruptions or internal layering within the crust due to an impact are the preferred explanations for our observations.
Key Points
Rayleigh and Love waves were detected on Mars
Seismic wave speed is directionally dependent over large‐scales within Mars crust
The shear wave horizontal velocity is faster than the vertical velocity at 10–25 km depth in the lowlands between the event and the lander
Accurately inferring the radially anisotropic structure of the mantle using seismic waveforms requires correcting for the effects of crustal structure on waveforms. Recent studies have quantified the ...importance of accurate crustal corrections when mapping upper mantle structure using surface waves and overtones. Here, we explore the effects of crustal corrections on the retrieval of deep mantle velocity and radial anisotropy structure. We apply a new method of nonlinear crustal corrections to a three‐component surface and body waveform data set and invert for a suite of models of radially anisotropic shear velocity. We then compare the retrieved models against each other and a model derived from an identical data set but using a different nonlinear crustal correction scheme. While retrieval of isotropic structure in the deep mantle appears to be robust with respect to changes in crustal corrections, we find large differences in anisotropic structure that result from the use of different crustal corrections, particularly at transition zone and greater depths. Furthermore, anisotropic structure in the lower mantle, including the depth‐averaged signature in the core‐mantle boundary region, appears to be quite sensitive to choices of crustal correction. Our new preferred model, SAW642ANb, shows improvement in data fit and reduction in apparent crustal artifacts. We argue that the accuracy of crustal corrections may currently be a limiting factor for improved resolution and agreement between models of mantle anisotropy.
Teleseismic waves can convert from shear to compressional (Sp) or compressional to shear (Ps) across impedance contrasts in the subsurface. Deconvolving the parent waveforms (P for Ps or S for Sp) ...from the daughter waveforms (S for Ps or P for Sp) generates receiver functions which can be used to analyse velocity structure beneath the receiver. Though a variety of deconvolution techniques have been developed, they are all adversely affected by background and signal-generated noise. In order to take into account the unknown noise characteristics, we propose a method based on transdimensional hierarchical Bayesian inference in which both the noise magnitude and noise spectral character are parameters in calculating the likelihood probability distribution. We use a reversible-jump implementation of a Markov chain Monte Carlo algorithm to find an ensemble of receiver functions whose relative fits to the data have been calculated while simultaneously inferring the values of the noise parameters. Our noise parametrization is determined from pre-event noise so that it approximates observed noise characteristics. We test the algorithm on synthetic waveforms contaminated with noise generated from a covariance matrix obtained from observed noise. We show that the method retrieves easily interpretable receiver functions even in the presence of high noise levels. We also show that we can obtain useful estimates of noise amplitude and frequency content. Analysis of the ensemble solutions produced by our method can be used to quantify the uncertainties associated with individual receiver functions as well as with individual features within them, providing an objective way for deciding which features warrant geological interpretation. This method should make possible more robust inferences on subsurface structure using receiver function analysis, especially in areas of poor data coverage or under noisy station conditions.
Surface waves and crustal structure on Mars Kim, D.; Banerdt, W. B.; Ceylan, S. ...
Science (American Association for the Advancement of Science),
10/2022, Letnik:
378, Številka:
6618
Journal Article
Recenzirano
Odprti dostop
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.
An insightful impact
On 24 December 2021, the seismometer for the InSight mission on Mars detected a large seismic event with a distinct signature. Posiolova
et al
. discovered that the event was caused by a meteor impact on the surface of Mars, which was confirmed by satellite observations of a newly formed 150-meter crater. The surface nature and size of the impact allowed Kim
et al
. to detect surface waves from the event, which have yet to be observed on Mars. These surface waves help to untangle the structure of the Martian crust, which has various amounts of volcanic and sedimentary rock, along with subsurface ice, in different regions of the planet (see the Perspective by Yang and Chen). The characteristics of the impact itself are important because they provide a seismic fingerprint of an impact event that is different from the marsquakes observed so far. —BG
A new crater formed on the surface of Mars was detected with the seismometer on the InSight mission.
Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and ...data exchange. The mid‐ to late‐twentieth century saw the creation of the World‐Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global geographic coverage as seismometer bandwidth increased greatly allowing for the recording of the Earth's principal seismic spectrum. The modern era of global observations and rapid data access began during the 1980s, and notably included the inception of the GEOSCOPE initiative (1982) and GSN (1988). Through continual improvements, GEOSCOPE and the GSN have realized near‐real time recording of ground motion with state‐of‐art data quality, dynamic range, and timing precision to encompass 180 seismic stations, many in very remote locations. Data from GSNs are increasingly integrated with other geophysical data (e.g., space geodesy, infrasound and Interferometric Synthetic Aperture Radar). Globally distributed seismic data are critical to resolving crust, mantle, and core structure; illuminating features of the plate tectonic and mantle convection system; rapid characterization of earthquakes; identification of potential tsunamis; global nuclear test verification; and provide sensitive proxies for environmental changes. As the global geosciences community continues to advance our understanding of Earth structure and processes controlling elastic wave propagation, GSN infrastructure offers a springboard to realize increasingly multi‐instrument geophysical observatories. Here, we review the historical, scientific, and monitoring heritage of GSNs, summarize key discoveries, and discuss future associated opportunities for Earth Science.
Plain Language Summary
Global seismographic networks (GSNs) record information‐rich ground motion signals that allow scientists and nations to identify and quantify global earthquakes and other seismic sources, and to rapidly assess their significance and impacts on society. In addition to providing a global standard for the monitoring and assessment of such events, these networks provide unique high‐quality data that are fundamental to revealing Earth's structure and dynamic behavior. Scientific applications of GSNs, supplemented by regional data, include imaging the deep interior of the Earth and its plate tectonic system, modeling the structure and dynamics of the inner core, imaging and understanding the rupture of earthquake faults, detecting, discriminating, and characterizing nuclear and other explosions, and improving our general understanding of Earth's ubiquitous seismic wavefield and the unique information that it conveys from the deep interior to the surface and atmosphere of the planet. Leveraging the extensive and hardened infrastructure at these global observatories facilitates the recording of other signals of geophysical interest, such as the magnetic field, low frequency sound waves, and meteorological observations. We review the heritage of GSNs, including their history and resulting scientific achievements, and summarize future opportunities for these networks to contribute further to improved advancements in Earth science.
Key Points
Long running globally distributed seismographic networks are fundamental to understanding Earth's interior structure and processes
Networks have expanded beyond initial mid‐twentieth century design which were focused on recording signals from earthquakes and explosions
Global seismic data combined with data from nearby geophysical instrumentation continue to facilitate new discoveries in Earth science
Accurate accounting for the effects of crustal structure on long-period seismic surface waves and overtones is difficult but indispensable for determining elastic structure in the mantle. While ...standard linear crustal corrections (SLC) have been shown to be inadequate on the global scale, newer non-linear correction (NLC) techniques are computationally expensive when applied to waveforms containing higher frequencies and/or overtones. We devise, implement, and verify a modified SLC approach that mimics the non-linear effects of the crust without substantially increasing the computational costs. While theoretically less accurate than the NLC approach, in practice, the reduced computational costs allow this ‘modified linear correction’ (MLC) technique to be applied at higher frequencies and using more detailed crustal regionalizations than is possible with NLC. In order to validate the MLC technique, we use the spectral element method to carry out a series of synthetic tests. These tests demonstrate that MLC nearly eliminates the contamination of mantle isotropic structure by unmodelled crustal effects, which can be substantial in the uppermost 150 km when using SLC. Furthermore, we show that MLC significantly reduces contamination of anisotropic structure compared to SLC, the inaccuracies of which are significant in the upper 250 km and can even obliterate the mantle anisotropic signature at depths shallower than 100 km. Finally, we apply the MLC technique to a real long period waveform data set and demonstrate the benefit of improved crustal corrections on the retrieved model.
We report observations of Rayleigh waves that orbit around Mars up to three times following the S1222a marsquake. Averaging these signals, we find the largest amplitude signals at 30 and 85 s central ...period, propagating with distinctly different group velocities of 2.9 and 3.8 km/s, respectively. The group velocities constraining the average crustal thickness beneath the great circle path rule out the majority of previous crustal models of Mars that have a >200 kg/m3 density contrast across the equatorial dichotomy between northern lowlands and southern highlands. We find that the thickness of the Martian crust is 42–56 km on average, and thus thicker than the crusts of the Earth and Moon. Considered with the context of thermal evolution models, a thick Martian crust suggests that the crust must contain 50%–70% of the total heat production to explain present‐day local melt zones in the interior of Mars.
Plain Language Summary
The NASA InSight mission and its seismometer installed on the surface of Mars is retired after ∼4 years of operation. From the largest marsquake recording during the entire mission, we observe clear seismic signals from surface waves called Rayleigh waves that orbit around Mars up to three times. By measuring the wavespeeds with which these surface waves travel at different frequencies, we obtain the first seismic evidence that constrains the average crustal and uppermost mantle structures beneath the traveling path on a planetary scale. Using the new seismic observations together with gravity data, we confirm that the density of the crust in the northern lowlands and the southern highlands is similar, differing by no more than 200 kg/m3. Furthermore, we find that the global average crustal thickness on Mars is 42–56 km, much thicker than the Earth's and Moon's crusts. By exploring Mars' thermal history, a thick Martian crust requires about 50%–70% of the heat‐producing elements such as thorium, uranium, and potassium to be concentrated in the crust in order to explain local regions in the Martian mantle that can still undergo melting at present day.
Key Points
We present the first observation of Rayleigh waves that orbit around Mars up to three times
Group velocity measurements and 3‐D simulations constrain the average crustal and uppermost mantle velocities along the great‐circle propagation path
The global average crustal thickness is 42–56 km and requires a large enrichment of heat‐producing elements to explain local melt zones
PDF
