Central and Eastern United States (CEUS) earthquakes are less common than those in the tectonically active West Coast, but their significance is elevated due to higher population densities, less-attenuating bedrock geology, variable site-amplification effects, and a higher proportion of structures prone to damage from shaking. Associating CEUS earthquake focal mechanisms with causative crustal faults is challenging due to a lack of mapped faults. Aftershock productivity of CEUS earthquakes is difficult to predict because it is highly variable, displaying globally typical behavior in some regions (Wu et al., 2015; Wu and Chapman, 2017) and low decay rates (Stein and Liu, 2009; Calais et al., 2016; Toda and Stein, 2018) in others. Here, we study the aftershock sequence of an unusual Mw 4.24 CEUS earthquake that occurred below the Atlantic Coastal Plain east of Dover, Delaware, in late 2017. We analyze data from a temporary 14-station network and use template matching to search for aftershocks, which we locate using a custom 1D velocity model. We find aftershock locations favoring slip on a northwest–southeast-striking fault oblique to the presumed fault where the mainshock was located. We document an unusually low a value and large magnitude difference between the mainshock and the largest aftershock, as well as an average aftershock decay p value. Factors proposed to explain variations in aftershock productivity include fault alignment relative to the prevailing stress field (Hardebeck, 2010) and low productivity after a high stress drop (Wetzler et al., 2018). We test these hypotheses in relation to the 2017 Delaware earthquake aftershocks, showing the Delaware earthquake had a stress drop of 35 MPa, normal for an intraplate region (Boyd et al., 2017), and had favorable alignment for aftershock thrust faulting. We therefore propose a small fault of possible pre-Mesozoic origin, limiting the productivity observed.

Mantle plumes beneath major oceanic hot spots appear to be rooted in unusually large structures near the core-mantle boundary, which have markedly reduced seismic wave speeds. The origin of these large ultralow-velocity zones (ULVZs), referred to as mega-ULVZs, remains uncertain partly because of lack of constraints on the relative reduction in shear versus compressional wave speeds (RS/P). This ratio can give clues into the compositional makeup of the mega-ULVZs. Through joint seismic analysis of core-diffracted P and S waves beneath Hawai’i, we constrain the RS/P of its mega-ULVZ to 1 to 1.3. Mineralogical modeling reveals that iron enrichment via solid iron-rich magnesiowüstite [(Mg,Fe)O] matches this seismic constraint, independent of modeled ULVZ thickness. Enrichment of metallic iron-rich magnesiowüstite likely enhances the thermal conductivity of mega-ULVZs and provides a mechanism to drive localized plume upwelling. Higher reported RS/P values for smaller ULVZs near subduction zones may therefore indicate different processes at play controlling ULVZ formation across the diverse core-mantle boundary landscape.

Posterior sampling algorithms have been applied to many geophysical inverse problems, including electrical resistivity sounding, seismic tomography, and gravity and geodetic inversions. Unlike optimization‐based approaches that yield a single best‐fit solution, these algorithms produce an ensemble of solutions that sample the posterior probability distributions of the model parameters given the data and prior knowledge. These distributions can be multi‐modal in the presence of significant non‐linearity in the forward model and uncertainty in observations. Communicating the richness of information contained in the ensemble solutions is not straightforward, so practitioners often present a single preferred solution such as a 2D image of subsurface structure or a 1D profile of a parameter. Ensemble solutions generated by transdimensional, hierarchical, Bayesian methods, in which the ensemble samples solutions with different levels of complexity, present particular challenges. As a model problem, we use 1D electrical resistivity sounding to assess methods for extracting representative solutions from ensembles. Due to the problem's non‐linearity and non‐uniqueness, the model‐space average is not a good predictor of the data and thus not representative of the solutions within the ensemble. We apply clustering and sorting algorithms to ensemble solutions in order to extract information about central tendencies. We illustrate how manifold learning and dimensionality reduction techniques can provide insight into ensemble solutions even in the presence of nonlinearity and uncertainty. Finally, we show that the direct application of K‐medoids clustering in model space can select solutions that are representative of the ensemble in both model space and data space.

Lava tubes, a common volcanic feature on terrestrial planets, offer critical insights into lava flow processes and may serve as future potential habitats for space crews and other facilities on the Moon and Mars. Seismic detection of these features is challenging as the irregular morphology and rough cave ceilings and walls generate complex seismic wavefields dominated by strong scattering and reverberation rather than pure reflections. Here we present observations of enhanced backscattering in seismic data collected above terrestrial lava tubes. We show that the spatial and frequency characteristics of wavefield intensity can be related to the dimensions of the lava tubes. Our findings suggest that, when geological indicators such as collapse pits are present, this method would enable mapping lava tubes on Earth and, by proxy, on the Moon and Mars, and that the approach is readily adaptable for future planetary exploration.

Analysis of conversions between compressional and shear waves is a workhorse method for constraining crustal and lithospheric structure on Earth; yet, such converted waves have not been unequivocally identified in seismic data from the largest events on the Moon, due to the highly scattered waveforms of shallow seismic events. We reanalyze the polarization attributes of waveforms recorded by the Apollo seismic network to identify signals with rectilinear particle motion below 1 Hz, arising from conversions across the crust‐mantle boundary. Delay times of these converted waves are inverted to estimate crustal thickness and wavespeeds beneath the seismometers. Combined with gravimetric modeling, these new crustal thickness tie‐points yield an updated lunar crustal model with an average thickness of 29–47 km. Unlike previous models, ours include explicit uncertainty estimates, offering critical context for future lunar missions, geophysical studies, and predicting 15–36 km crust at Schrödinger and 29–52 km at Artemis III sites.

Maars are volcanoes with a central crater surrounded by an ejecta ring formed through surface explosive processes from underlying magma interacting with fluids. The study of terrestrial maar volcanoes, as analogs to explosive volcanic vents on the Moon and other planets, can improve our understanding of planetary volcanism and evolution. In this study, we conducted a series of geophysical experiments at Kilbourne Hole Maar, New Mexico, a well‐preserved crater used for both science and crewed exploration lunar analog studies. The surveys included multiple active source seismic lines that sampled the geological units of both the crater rim and floor. We demonstrate the effectiveness of shallow seismic reflection methods integrated with P wave refraction and surface wave analysis to determine the elastic properties and create detailed near‐surface structural models in a terrestrial volcanic setting. The reflection profiles capture the top‐down strata of the crater rim. The velocity changes derived from independent inversions of refraction travel times and surface wave dispersions indicate varying (6–15 m) ash thickness around the rim and reveal the presence of high‐velocity anomalies in possible connection with crater collapse beneath the crater floor. Additionally, we estimate a base surge volume of approximately 6.4×106 $6.4\times {10}^{6}$ m3 ${\mathrm{m}}^{3}$ present on the rim. The integrated results highlight the potential for characterizing the subsurface of planetary bodies in greater detail and provide high‐fidelity data simulations for astronaut training. The operational insights serve as a valuable guideline for future crewed lunar missions and contribute to the development of strategies for optimizing planetary exploration.

Magnetometry is used to detect ferrous objects at various scales, but detecting small-size, compact sources that produce small-amplitude anomalies in the shallow subsurface remains challenging. Magnetic anomalies are often approximated as dipoles or volumes of dipoles that can be located, and their source parameters (burial depth, magnetization direction, magnetic susceptibility, etc.) are characterized using scalar or vector magnetometers. Both types of magnetometers are affected by space weather and cultural noise sources that map temporal variations into spatial variations across a survey area. Vector magnetometers provide more information about detected bodies at the cost of extreme sensitivity to orientation, which cannot be reliably measured in the field. Magnetic gradiometry addresses the problem of temporal-to-spatial mapping and reduces distant noise sources, but the heading error challenges remain, motivating the need for magnetic gradient tensor (MGT) invariants that are relatively insensitive to rotation. Here, we show that the finite size of magnetic gradiometers compared to the lengthscales of magnetic anomalies due to small buried objects affects the properties of the gradient tensor, including its symmetry and invariants. This renders traditional assumptions of magnetic gradiometry largely inappropriate for detecting and characterizing small-size anomalies. We then show how the properties of the finite-difference MGT and its invariants can be leveraged to map these small sources in the shallow critical zone, such as unexploded ordnance (UXO), landmines, and explosive remnants of war (ERW), using both synthetic and field data obtained with a triaxial magnetic gradiometer (TetraMag).

Geophysical measurements, such as seismic experiments, are a key target for scientific activities on planetary surfaces. Dense spatial sampling of such measurements is often desirable, and acquisition is traditionally performed at regular intervals. However, achieving regular and dense spatial sampling is made difficult by obstacles and operational constraints of a planetary surface mission. Here, we present an application of compressive sensing (CS) in the design of seismic surveys on planetary surfaces for imaging the shallow subsurface. This approach is based on more flexible, randomized subsampling and requires fewer sources or receivers compared to traditional methods. We illustrate the potential of CS on synthetic data and measurements made along an active seismic transect across a lunar analog site. We then explore the use of CS‐assisted seismic acquisition at a terrestrial analog site in the San Francisco Volcanic Field. We show how irregularly acquired data can be interpolated to reconstruct data at finer spatial sampling and yield seismic images comparable to those from regularly acquired high‐density data. Finally, we apply our approach to reanalyze the legacy data collected by the Active Seismic Experiments during the Apollo 14 and 16 missions. The results show that the CS method can recover missing data and increase the amount of data available for refraction analysis. Our study highlights the potential of CS in future planetary surface exploration missions for (a) an order‐of‐magnitude improvement in survey efficiency and (b) improved imaging quality to gain a deeper understanding of the geologic processes of planetary bodies.

The Pacific large low-shear-velocity province (LLSVP), as revealed by cluster analysis of global tomographic models, hosts multiple internal anomalies, including a notable gap (~20° wide) between the central and eastern Pacific. The cause of the structural gap remains unconstrained. Directly above this structural gap, we identify an anomalously thick mantle transition zone east of the East Pacific Rise, the fastest-spreading ocean ridge in the world, using a dense set of SS precursors. The area of the thickened transition zone exhibits faster-than-average velocities according to recent tomographic images, suggesting perturbed postolivine phase boundaries shifting in response to lowered temperatures. We attribute this observation to episodes of Mesozoic-aged (250 to 120 million years ago) intraoceanic subduction beneath the present-day Nazca Plate. The eastern portion of the Pacific LLSVP was separated by downwelling because of this ancient oceanic slab. Our discovery provides a unique perspective on linking deep Earth structures with surface subduction.