AbstractSeismic imaging is one of the most powerful tools available for constraining the internal structure and composition of planetary bodies as well as enabling our understanding planetary evolution, geology, and distribution of natural resources. However, traditional seismic instrumentation can be heavy and voluminous, expensive, and/or difficult to rapidly deploy in large numbers. Distributed acoustic sensing (DAS) provides a promising new alternative given the ease of deployment, light weight and simplicity of fiber optic cables. However, the feasibility and best operational practices for using DAS for planetary exploration are not well‐known. We examine the use of DAS with surface deployed fiber for planetary near‐surface seismic exploration at two lunar geophysical analogue sites in San Francisco Volcanic Field. We compare DAS recordings to 3‐component seismometer recordings and geophone shot recordings and determine empirical response functions for the DAS system with respect to the 3‐component recordings. Shot sections of DAS and traditional seismic equipment compare well visually, with similar moveout of identifiable phases. DAS records first arrivals in good agreement with seismometers making them suitable for refraction work. Multichannel analysis of surface waves is performed on DAS records to estimate shallow shear velocities. The DAS has high spectral coherence with the horizontal components of ∼0.7 in the frequency band of the seismic shot energy. The empirical response functions are stable with amplitudes of ∼1.0–3.0 × 10−10 m per strain. Finally, the phase response is linear but not flat or zero. Our experiment demonstrates that there is potential for surface deployed DAS in planetary landscapes.
As the volume of data collected at monitored volcanoes continues to expand, researchers will need quick, reliable, and automated methods of inverting those data into useful models of the underlying magma systems. Recently adapted from other fields for use in volcanology, the Ensemble Kalman Filter (EnKF) is one such inversion technique that has been used to produce several successful forecasts and hind-casts of volcanic unrest, correlating geodetic deformation with mechanical stresses around the magma reservoir. However, given the similarity in which changes to a reservoir's size and pressure are expressed at the surface, the filter can have trouble fully resolving magmatic conditions. In this study, we therefore test several different published variations of the EnKF workflow to produce an optimal configuration for use in future forecasting efforts. By generating synthetic observations of ground deformation under known conditions and then assimilating them through different implementations of the EnKF, we find that many variants favored in other fields underperform for this specific application. We conclude that correlations between model parameters that develop within the EnKF's Monte Carlo ensemble distort the filter's ability to correctly update the model state, causing the filter to systematically favor changes in some parameters over others and ultimately converge to a partially inaccurate solution. This effect can be somewhat mitigated by interrupting these parameter correlations, and the filter remains sensitive to many aspects of the magma system regardless. However, further research and novel approaches will be needed to truly optimize the EnKF for use in volcanology.
AbstractThe NASA Psyche mission will explore the structure, composition, and other properties of asteroid (16) Psyche to test hypotheses about its formation. Variations in radar reflectivity, density, thermal inertia, and visible to near‐infrared (VNIR) reflectance spectra of Psyche suggest a highly metallic composition with mafic silicate minerals (e.g., pyroxene) heterogeneously distributed on the surface in low abundance (<10 vol.%). The Psyche spacecraft's Multispectral Imager is designed to map ≥80% of the surface at high spatial resolution (≤20 m/pixel) through a panchromatic filter and provide compositional information for about ≥80% of the surface using seven narrowband filters at VNIR wavelengths (∼400–1,100 nm) and at spatial scales of ≤500 m/pixel. We analyzed 359 reflectance spectra from samples consistent with current uncertainties in Psyche's composition and compared them to published reflectance spectra of the asteroid using a chi‐square test for goodness of fit. The best matches for Psyche include iron meteorite powder, powders from the sulfide minerals troilite and pentlandite, and powder from the CH/CBb chondrite Isheyevo. Comparison of absorption features support the interpretation that Psyche's surface is a metal‐silicate mixture, although the exact abundance and chemistry of the silicate component remains poorly constrained. We convolve our spectra to the Imager's spectral throughput to demonstrate preliminary strategies for mapping the surface composition of the asteroid using filter ratios and reconstructed band parameters. Our results provide predictions of the kinds of surface compositional information that the Psyche mission could reveal on the solar system's largest M‐type asteroid.
Planetary caves are desirable environments for the search for biosignatures corresponding to extant or extinct extraterrestrial life due to the protection they offer from surface-level solar radiation and ionizing particles. Near-infrared (NIR) reflectance spectroscopy is one of a multitude of techniques that, when taken together, can provide a comprehensive understanding of the geomicrobiology in planetary subsurface regions. To that end, we developed two portable NIR spectrometers that employ acousto-optic tunable filters and demonstrated them in three geochemically distinct cave environments. The instruments were deployed both as stand-alone spectrometers positioned against the targets manually and as a component of an instrument payload mounted on a quadruped robot capable of vertical excursions of several meters. In situ measurements of calcium carbonates, sulfates, metal oxides, and microbial colonies and mats revealed spectral signatures that enable a distinction between the targets of interest and the underlying substrates. The ruggedness and portability of the instruments, and their low size, weight, and power, spectral agility, and active illumination make AOTF-based spectrometers ideally suited for studies of planetary caves.
Lightning is measured from space using optical instruments that detect transient changes in the illumination of the cloud top. How much of the flash (if any) is recorded by the instrument depends on the instrument detection threshold. NOAA's Geostationary Lightning Mapper (GLM) employs a dynamic threshold that varies across the imaging array and changes over time. This causes flashes in certain regions and at night to be recorded in greater detail than other flashes, and threshold inconsistencies will impose biases on all levels of GLM data products. In this study, we quantify the impact of the varying GLM threshold on event/group/flash detection, flash clustering, and gridded product generation by imposing artificial thresholds on the event data taken from a thunderstorm with a low instrument threshold (∼0.7 fJ). We find that even modest increases in threshold severely impact event (60% loss by 2 fJ, 90% loss by 10 fJ) and group (25% loss by 2 fJ, 81% loss by 10 fJ) detection by suppressing faint illumination of the cloud top from weak sources and scattering. Flash detection is impacted less by threshold increases (4% loss by 2 fJ), but reductions are still significant at higher thresholds (35% loss by 10 fJ, or 44% if single‐group flashes are removed). Undetected pulses cause individual flashes to be split and severely impact the construction of gridded products. All of these factors complicate the interpretation of GLM data, particularly when trended over time under a changing threshold.
