We present the new model SP12RTS of isotropic shear-wave (V
S
) and compressional-wave (V
P
) velocity variations in the Earth's mantle. SP12RTS is derived using the same methods as employed in the ...construction of the shear-wave velocity models S20RTS and S40RTS, and the same data types. SP12RTS includes additional traveltime measurements of P-waves and new splitting measurements: 33 normal modes with sensitivity to the compressional-wave velocity and 9 Stoneley modes with sensitivity primarily to the lowermost mantle. Contrary to S20RTS and S40RTS, variations in V
S
and V
P
are determined without invoking scaling relationships. Lateral velocity variations in SP12RTS are parametrised using spherical harmonics up to degree 12, to focus on long-wavelength features of V
S
and V
P
and their ratio R. Large-low-velocity provinces (LLVPs) are observed for both V
S
and V
P
. SP12RTS also features an increase of R up to 2500 km depth, followed by a decrease towards the core–mantle boundary. A negative correlation between the shear-wave and bulk-sound velocity variations is observed for both the LLVPs and the surrounding mantle. These characteristics can be explained by the presence of post-perovskite or large-scale chemical heterogeneity in the lower mantle.
SUMMARY
Observations of seismic anisotropy provide useful information to infer directions of mantle flow. However, existing global anisotropic tomography models are not consistent, particularly in ...the lower mantle. Therefore, the interpretation of seismic anisotropy in terms of mantle dynamics and evolution remains difficult. While surface and body waves are commonly used to build radially anisotropic tomography models, they provide heterogeneous data coverage and the radial anisotropy structure retrieved using these data may be biased by the use of imperfect crustal corrections. Normal modes, the free oscillations of the Earth, automatically provide global data coverage and their sensitivity to shear wave (vs) and compressional wave (vp) velocity makes them suitable to study both vs and vp anisotropy in the mantle. In this study, we assess whether current normal mode splitting data have sufficient sensitivity to lower mantle anisotropy to potentially constrain it. We consider the uncertainties in the data and the effect of inaccuracies in crustal thickness corrections and the assumed scaling between vp and vs. We perform forward modelling of normal mode data using six different 3-D global radially anisotropic tomography models to document how strong and widespread anisotropy has to be to be observable in current normal mode data. We find that, on average 50% of the spheroidal and 55% of the toroidal modes investigated show significant sensitivity to vs anisotropy, while roughly 57% of the spheroidal modes also have strong sensitivity to vp anisotropy. Moreover, we find that the normal mode data fit varies substantially for the various anisotropic tomography models considered, with the addition of anisotropy not always improving the data fit. While we find that crustal thickness corrections do not strongly impact modes that are sensitive to the lower mantle, we observe a trade-off between radial anisotropy and vp scaling for these modes. As long as this is taken into consideration, our findings suggest that existing normal mode data sets can provide valuable information on both vs and vp anisotropy in the mantle.
Lower mantle tomography models consistently feature an increase in the ratio of shear-wave velocity (VS) to compressional-wave velocity (VP) variations and a negative correlation between shear-wave ...and bulk-sound velocity (VC) variations. These seismic characteristics, also observed in the recent SP12RTS model, have been interpreted to be indicative of large-scale chemical variations. Other explanations, such as the lower mantle post-perovskite (pPv) phase, which would not require chemical heterogeneity, have been explored less. Constraining the origin of these seismic features is important, as geodynamic simulations predict a fundamentally different style of mantle convection under both scenarios. Here, we investigate to what extent the presence of pPv explains the observed high VS/VP ratios and negative VS–VC correlation globally. We compare the statistical properties of SP12RTS with the statistics of synthetic tomography models, derived from both thermal and thermochemical models of 3-D global mantle convection. We convert the temperature fields of these models into seismic velocity structures using mineral physics lookup tables with and without pPv. We account for the limited tomographic resolution of SP12RTS using its resolution operator for both VS and VP structures. This allows for direct comparisons of the resulting velocity ratios and correlations. Although the tomographic filtering significantly affects the synthetic tomography images, we demonstrate that the effect of pPv remains evident in the ratios and correlations of seismic velocities. We find that lateral variations in the presence of pPv have a dominant influence on the VS/VP ratio and VS–VC correlation, which are thus unsuitable measures to constrain the presence of large-scale chemical variations in the lowermost mantle. To explain the decrease in the VS/VP ratio of SP12RTS close to the CMB, our results favour a pPv-bearing CMB region, which has implications for the stability field of pPv in the Earth's mantle.
•Meaningful comparisons of tomographic model SP12RTS with geodynamic models.•Focus on high VS/VP ratio and negative VS–VC correlation in lowermost mantle.•Areal extent of post-perovskite has a dominant influence on these properties.•SP12RTS is best fit by a pPv-bearing CMB, implying the presence of pPv inside LLVPs.•Indicate potential for constraining Clapeyron slope of the phase transition.
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
SUMMARY
The core–mantle boundary (CMB) is Earth’s most profound internal boundary separating the liquid iron outer core and the solid silicate mantle. The detailed structure near the CMB has a major ...influence on mantle convection and the evolution of the core. Seismic observations, such as topography on the CMB, thin ultra‐low velocity zones (ULVZs), seismic anisotropy and the anticorrelation between shear wave and bulk sound velocity heterogeneities have mainly been made using body waves and are still poorly constrained. We investigate the sensitivity of Earth’s free oscillations to these features and specifically show how large individual anomalies must be for them to be observable. In addition, we discuss the possible trade‐offs between these different lowermost mantle structures. Although modes have strong sensitivity to all the structures inserted, the results illustrate the limits of what normal modes can resolve. Our tests show that: (i) Even small scale features, such as ULVZs, with a thickness larger than 19 km can be observed as long as their distribution contains a long wavelength component. (ii) The peak‐to‐peak amplitude of CMB topography has a larger influence than its pattern and has to be smaller than 5 km to fit the data. (iii) The effect of scaling between shear wave velocity and density anomalies is less constrained, but a laterally varying pattern is implied by a simple test, suggesting the presence of chemical variations. (iv) A strong trade‐off exists between anisotropy in compressional wave velocity and incidence angle whereas shear wave anisotropy is less observable. These findings provide valuable information for future normal mode studies on structures in Earth’s lowermost mantle and their trade‐offs.
The Absorbing Aerosol Index (AAI) was investigated and used to analyze GOME data and compare it to TOMS data. The physical interpretation of the AAI was studied with an extensive theoretical ...sensitivity analysis. The dependence of the method on a number of atmospheric, surface, and aerosol properties was studied using a numerical radiative transfer model. It was found to be sensitive to absorbing aerosols with wavelength‐dependent refractive indices and to elevated absorbing aerosols, both with wavelength‐dependent and wavelength‐independent (gray) refractive indices. It was found to be insensitive to clouds, while small size scattering aerosols yield negative values. AAIs were calculated from GOME data for the period July 1995 to December 2000 and compared to TOMS AAI data. In a part of this period, July 1995 to October 1996, no TOMS observations were available, and the GOME data can be used to supplement the TOMS data set. The GOME AAI corresponds very well with known absorbing aerosol events. It suffers from lower spatial resolution and less frequent temporal coverage as compared to TOMS, but is useful as an independent data source of global aerosol measurements.
A global database of Lambert‐equivalent reflectivity (LER) of the Earth's surface has been constructed by analyzing observations of the reflectivity at the top of the atmosphere made by the Global ...Ozone Monitoring Experiment (GOME). Since its launch on board the ERS‐2 satellite in April 1995, the GOME instrument has been measuring spectra of the Earth between 237 and 794 nm, with a spectral resolution between 0.2 and 0.4 nm and a spatial resolution between 40 × 80 and 40 × 320 km2. The LER database covers eleven 1‐nm‐wide wavelength bins centered at 335, 380, 416, 440, 463, 494.5, 555, 610, 670, 758, and 772 nm, which were selected for various retrieval applications. The database has a spatial resolution of 1° × 1°, is made for each month of the year, and pertains to the period June 1995–December 2000. Typical spectra of various surface types are presented. Attention is paid to instrument degradation and residual cloud contamination. We have found satisfactory agreement between our database at 380 nm and the Total Ozone Mapping Spectrometer (TOMS) LER database at 340–380 nm, with negligible average difference and a standard deviation of 0.013. The database presented here can be used to improve retrievals of trace gases, clouds and aerosols from GOME, Scanning Imaging Absorption Spectrometer or Atmospheric Cartography (SCIAMACHY), Ozone Monitoring Instrument (OMI), and GOME‐2.
We present a retrieval of tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment (GOME) satellite instrument that improves in several ways over previous retrievals, ...especially in the accounting of Rayleigh and cloud scattering. Slant columns, which are directly fitted without low-pass filtering or spectral smoothing, are corrected for an artificial offset likely induced by spectral structure on the diffuser plate of the GOME instrument. The stratospheric column is determined from NO2 columns over the remote Pacific Ocean to minimize contamination from tropospheric NO2. The air mass factor (AMF) used to convert slant columns to vertical columns is calculated from the integral of the relative vertical NO2 distribution from a global 3-D model of tropospheric chemistry driven by assimilated meteorological data (Global Earth Observing System (GEOS)-CHEM), weighted by altitude dependent scattering weights computed with a radiative transfer model (Linearized Discrete Ordinate Radiative Transfer), using local surface albedos determined from GOME observations at NO2 wavelengths. The AMF calculation accounts for cloud scattering using cloud fraction, cloud top pressure, and cloud optical thickness from a cloud retrieval algorithm (GOME Cloud Retrieval Algorithm). Over continental regions with high surface emissions, clouds decrease the AMT by 20- 30% relative to clear sky. GOME is almost twice as sensitive to tropospheric NO2 columns over ocean than over land. Comparison of the retrieved tropospheric NO2 columns for July 1996 with GEOS-CHEM values tests both the retrieval and the nitrogen oxide radical (NOx) emissions inventories used in GEOS-CHEM. Retrieved tropospheric NO2 columns over the United States, where NOx emissions are particularly well known, are within 18% of GEOS-CHEM columns and are strongly spatially correlated (r = 0.78, n = 288, p less than 0.005). Retrieved columns show more NO2 than GEOS-CHEM columns over the Transvaal region of South Africa and industrial regions of the northeast United States and Europe. They are lower over Houston, India, eastern Asia, and the biomass burning region of central Africa, possibly because of biases from absorbing aerosols.
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