S U M M A R Y Inversion of surface wave data for crustal and upper-mantle structure is a staple of passive seismology, particularly since the advent of techniques enabling surface wave dispersion (SWD) and Rayleigh wave ellipticity measurements from ambient noise. Recent development and application of transdimensional Bayesian (TB) seismic inversion offers an approach to quantify model parameter uncertainties and trade-offs with fewer assumptions than traditional methods. Using synthetic tests, we investigate choices in the implementation of TB for the inversion of SWD and Rayleigh wave ellipticity to constrain the structure of Earth’s continental lithosphere. We focus on three aspects of the inversion: limitation of data sensitivity, assumed scaling among parameters (compressional wave speed, Vp, shear wave speed, Vs, density and radial anisotropy) and parametrization choices. We show that while surface wave data provide relatively strong constraints on the posterior distribution of Vs and, to a lesser extent, Vp, common parametrization choices can potentially bias structure estimates. This is particularly the case for radial anisotropy (ξ ), due to the inability to distinguish variations of Vp and density from those of ξ . Inferred results therefore depend substantially on the parametrization and scaling choices. We illustrate how layered parametrizations can, in the TB framework, recover smoothly varying profiles, and quantify the number of layers recoverable at different levels of measurement uncertainty. Finally, we propose two types of model parametrization for TB inversion involving multiple types of parameters. We demonstrate that by implementing an independent parametrization for different physical quantities, we can avoid imposing identical model geometry across multiple types of model parameters, and obtain better model estimates with reduced trade-offs. We advocate for such a parametrization in TB inversion of radial anisotropy using surface wave data, and when targeting disparate Vp and Vs structures such as those associated with α-β quartz transtion.

Seismic properties and equation-of-state parameters of the liquid iron alloy in the outer core are inferred from normal mode data. Turbulent convection of the liquid iron alloy outer core generates Earth’s magnetic field and supplies heat to the mantle. The exact composition of the iron alloy is fundamentally linked to the processes powering the convection and can be constrained by its seismic properties. Discrepancies between seismic models determined using body waves and normal modes show that these properties are not yet fully agreed upon. In addition, technical challenges in experimentally measuring the equation-of-state (EoS) parameters of liquid iron alloys at high pressures and temperatures further complicate compositional inferences. We directly infer EoS parameters describing Earth’s outer core from normal mode center frequency observations and present the resulting Elastic Parameters of the Outer Core (EPOC) seismic model. Unlike alternative seismic models, ours requires only three parameters and guarantees physically realistic behavior with increasing pressure for a well-mixed homogeneous material along an isentrope, consistent with the outer core’s condition. We show that EPOC predicts available normal mode frequencies better than the Preliminary Reference Earth Model (PREM) while also being more consistent with body wave–derived models, eliminating a long-standing discrepancy. The velocity at the top of the outer core is lower, and increases with depth more steeply, in EPOC than in PREM, while the density in EPOC is higher than that in PREM across the outer core. The steeper profiles and higher density imply that the outer core comprises a lighter but more compressible alloy than that inferred for PREM. Furthermore, EPOC’s steeper velocity gradient explains differential SmKS body wave travel times better than previous one-dimensional global models, without requiring an anomalously slow ~90- to 450-km-thick layer at the top of the outer core.

Abstract. Knowing the location of large-scale turbulent eddies during catastrophic flooding events improves predictions of erosive scour. The erosion damage to the Oroville Dam flood control spillway in early 2017 is an example of the erosive power of turbulent flow. During this event, a defect in the simple concrete channel quickly eroded into a 47 m deep chasm. Erosion by turbulent flow is difficult to evaluate in real time, but near-channel seismic monitoring provides a tool to evaluate flow dynamics from a safe distance. Previous studies have had limited ability to identify source location or the type of surface wave (i.e., Love or Rayleigh wave) excited by different river processes. Here we use a single three-component seismometer method (frequency-dependent polarization analysis) to characterize the dominant seismic source location and seismic surface waves produced by the Oroville Dam flood control spillway, using the abrupt change in spillway geometry as a natural experiment. We find that the scaling exponent between seismic power and release discharge is greater following damage to the spillway, suggesting additional sources of turbulent energy dissipation excite more seismic energy. The mean azimuth in the 5–10 Hz frequency band was used to resolve the location of spillway damage. Observed polarization attributes deviate from those expected for a Rayleigh wave, though numerical modeling indicates these deviations may be explained by propagation up the uneven hillside topography. Our results suggest frequency-dependent polarization analysis is a promising approach for locating areas of increased flow turbulence. This method could be applied to other erosion problems near engineered structures as well as to understanding energy dissipation, erosion, and channel morphology development in natural rivers, particularly at high discharges.

The turbulent, convecting outer core is the most massive fluid region of our planet, yet its physical properties are not fully known. The blend of light elements which along with iron and nickel comprise the outer core is uncertain, and mineral physics experiments are extremely challenging at the relevant pressures and temperatures. Published seismological models of the outer core’s velocity show some disagreement, and models of the outer core’s density are few. The commonly-used seismological Preliminary Reference Earth Model is now more than 35 years old and a wealth of new seismological data are now available.

The 30 November 2017 Delaware earthquake with magnitude Mw 4.2 occurred beneath the northeastern tip of the Delmarva Peninsula near Dover, Delaware. The earthquake and its aftershocks provide an opportunity to evaluate seismicity in a passive margin setting using much improved coverage by high-quality permanent broadband seismometers at regional distance ranges in the central and eastern United States. This is the largest instrumentally recorded earthquake in Delaware, and it triggered a collaborative rapid-response effort by seismologists at five institutions along the midAtlantic. As a result of this effort, 18 portable seismographs were deployed in the epicentral region within 24 hrs of the mainshock. High-quality seismic recordings at more than 380 permanent regional broadband seismographic stations in the eastern United States show a remarkably small decrease in amplitude with distance between 800 and 2000 km. The mainshock focal mechanism shows predominantly strike slip with a significant thrust component. The orientation of the subhorizontal P axis is consistent with that of earthquakes in the nearby Reading-Lancaster seismic zone in Pennsylvania, but the trend is rotated counterclockwise about 45° from that of the Mw 5.8 Mineral, Virginia, earthquake. We detected small aftershocks below the normal event detection threshold using a waveform cross-correlation detection method. This demonstrated the effectiveness of this approach for earthquake studies and hazard evaluation in the eastern United States. Based on their waveform similarities, repeating earthquakes with magnitudes greater than 1.5 are detected in 2010, 2015, and 2017. Although there is a large time interval between events, 5 and 2.2 yrs, respectively, the events occur within a spatially tight cluster located near the 2017 Dover, Delaware, earthquake mainshock. Electronic Supplement: Peak amplitude and instrumental intensity maps of the 30 November 2017 Delaware earthquake. INTRODUCTION On 30 November 2017, a moderate earthquake of magnitude Mw 4.2 (this study) occurred about 10 km northeast of Dover, Delaware, beneath the west coast of Delaware Bay (Fig. 1). The earthquake was felt throughout Delaware and in neighboring New Jersey, Maryland, and Pennsylvania, and the ground motion near the epicenter attained a maximum intensity of V (modified Mercalli intensity [MMI] scale), moderate shaking (Community Internet Intensity Map [CIIM], see Data and Resources). Light ground shaking was reported in Wilmington, Baltimore, and Philadelphia and as far away as New York City and Washington, D.C. (“Did You Feel It?,” see Data and Resources). This event is the largest magnitude earthquake in Delaware at least in the past 150 yrs of record. The location and magnitude of the event were determined by the Lamont Cooperative Seismographic Network (LCSN) operated by more than 40 partner educational organizations in the northeastern United States and led by the Lamont–Doherty Earth Observatory (LDEO). The seismic waves generated by the 2017 Delaware earthquake were well recorded by broadband seismographic stations in the central and eastern United States (CEUS). Although the Atlantic Ocean occupies the vast majority of area to the east of the hypocenter, more than 380 broadband seismographic stations from distances of 70 to 2800 km provided regional Lg-wave peak amplitude measurements with signal-tonoise ratio greater than 2. That the event was so well recorded is largely due to funding from the 2009 American Recovery and Reinvestment Act that allowed upgrading nearly all existing seismic stations in the eastern United States in 2010 and the continued deployment of new broadband stations by regional networks. The retention of 159 temporary (18-month deployment) USArray Transportable Array (TA) stations of the EarthScope project supported with National Science Foundation and U.S. Geological Survey (USGS) funds beginning in 2013 helped fill the gap in seismic station coverage in the eastern United States. doi: 10.1785/0220180124 Seismological Research Letters Volume XX, Number XX – 2018 1 Downloaded from https://pubs.geoscienceworld.org/ssa/srl/article-pdf/doi/10.1785/0220180124/4336457/srl-2018124.1.pdf by Columbia University, 10831 on 19 September 2018 ▴ Figure 1. Historical earthquakes that occurred in and around Delaware since 1785 from earthquake catalogs are plotted with hexagons; earthquakes since 1972 from Lamont Cooperative Seismographic Network catalog are plotted with circles. Permanent seismographic stations used to locate small earthquakes around Delaware are plotted with solid triangles. 1871 is the epicenter of the largest known earthquake (M 4.1) in Delaware, and 1879 is an M 3.3 earthquake that occurred close to the 2017 Delaware event. 1984 M 4.1 Lancaster, Pennsylvania, and 1994M 4.6 Reading, Pennsylvania, earthquake sequences are indicated. Focal mechanism of the mainshock and trend of the subhorizontal P axis is indicated by thick arrows. Shaded area is Atlantic Coastal Plain strata covering bedrock. 2 Seismological Research Letters Volume XX, Number XX – 2018 Downloaded from https://pubs.geoscienceworld.org/ssa/srl/article-pdf/doi/10.1785/0220180124/4336457/srl-2018124.1.pdf by Columbia University, 10831 on 19 September 2018 The 2017 Delaware earthquake presents an opportunity for detailed study of a mainshock–aftershock sequence in a passive margin setting. The earthquake was followed by a rapid deployment of portable seismic stations by research and educational institutions in the region using limited resources but a collaborative effort. Within 24 hrs of the mainshock, 18 stations were deployed in the epicentral area on both shores of Delaware Bay. These local network stations operated for six weeks during the coldest winter in recent years. This article focuses on a description of the mainshock of the 2017 Delaware earthquake and analyses of seismic data recorded on the permanent seismographic stations in the mid-Atlantic States. More thorough analyses of the aftershock data are underway. The data from the temporary deployment are archived at the Incorporated Research Institutions for Seismology Data Management Center (see Data and Resources).

Introduction: The ~400 m diameter asteroid 99942 Apophis will make a close approach to Earth on April 13, 2029, passing at a distance of only 36700 ± 9000 km (or 5.7 ± 1.4 Earth radii) [1] – closer than geosynchronous satellites. While the approach is not close enough to disaggregate the asteroid, it is expected to produce changes in the rotational state, solid body deformation, and surface morphology [2–6]. Apophis’ encounter with the Earth presents a unique opportunity for a detailed study of a Near-Earth Asteroid (NEA) with a small spacecraft. The Asteroid Probe Experiment (APEX) mission is to characterize the internal structure, rotational dynamics, and surface morphology as Apophis passes the Earth in 2029. This mission would place a seismometer on the surface to monitor seismic signals generated during the Earth/asteroid encounter. The seismometer mission requirements for APEX are to record seismic energy on 3 orthogonal components and across a range of high frequencies (10–500 Hz), and amplitudes (> 10–100 ng), spanning several weeks. The seismometer concept has been developed by Hongyu Yu at Arizona State University with APL participation under the NASA MATISSE program [6]. This instrument senses seismic displacement via electrolyte flow through a sensor plate, instead of the more conventional "mass on a spring" designs. As there are no moving parts, a critical aspect of the sensor is that it is orientation independent (i.e., it does not need to be leveled), greatly simplifying deployment. The seismometer would be deployed by the spacecraft pushing it into the surface.