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Due to limited observational coverage, monitoring the warming of the global ocean, especially the deep ocean, remains a challenging sampling problem. Seismic ocean thermometry (SOT) complements existing point measurements by inferring large‐scale averaged ocean temperature changes using the sound waves generated by submarine earthquakes, calledTwaves. We demonstrate here that Comprehensive Nuclear‐Test‐Ban Treaty Organization (CTBTO) hydrophones can recordTwaves with a higher signal‐to‐noise ratio compared to a previously used land‐basedT‐wave station. This allows us to use small earthquakes (magnitude <4.0), which occur much more frequently than large events, dramatically improving the resulting temporal resolution of SOT. We also find that the travel time changes ofTwaves at the land‐basedT‐wave station and the CTBTO hydrophone show small but systematic differences, although the two stations are only about 20 km apart. We attribute this feature to their different acoustic mode components sampling different parts of the ocean. Applying SOT to two CTBTO hydrophones in the East Indian Ocean reveals signals from decadal warming, seasonal variations, and mesoscale eddies, some of which are missing or underestimated in previously available temperature reconstructions. This application demonstrates the great advantage of hydrophone stations for global SOT, especially in regions with a low seismicity level.

 

Abstract Distributed acoustic sensing (DAS) provides dense arrays ideal for seismic tomography. However, DAS only records average axial strain change along the cable, which can complicate the interpretation of surface-wave observations. With a rectangular DAS array located in the City of Oxnard, California, we compare phase velocity dispersion at the same location illuminated by differently oriented virtual sources. The dispersion curves are consistent for colinear and noncolinear virtual sources, suggesting that surface-wave observations in most of the cross-correlations are dominated by Rayleigh waves. Our measurements confirm that colinear channel pairs provide higher Rayleigh-wave signal-to-noise ratio (SNR). For cross-correlations of noncolinear channel pairs, the travel time of each connecting ray path can still be obtained despite the lower SNR of Rayleigh wave signals. The inverted Rayleigh-wave dispersion map reveals an ancient river channel consistent with the local geologic map. Our results demonstrate the potential of DAS-based 2D surface-wave tomography without special treatment of directional sensitivity in areas where one type of wave is dominating or can be identified. 

SUMMARY While distributed acoustic sensing (DAS) has been demonstrated to have great potential in seismology, DAS data often have much higher levels of stochastic and coherent noise (e.g. instrument noise, traffic vibrations) than data collected by traditional seismometers. The linearly, densely spaced nature of DAS arrays presents a suite of opportunities for more innovative processing techniques that can be used to address this issue. One way to take advantage of DAS’s array architecture is through the use of curvelets. Curvelets have a non-uniform scaling property that makes them an excellent tool for representing images with discontinuities along piecewise, twice continuously differentiable curves. This anisotropic scaling property makes curvelets an ideal processing tool for DAS data, for which the measured wavefield can be represented as an image composed of curved features. Here, we use the curvelet frame as a tool for the manipulation of DAS signal and demonstrate how this manipulation can improve our ability to identify important features in DAS data sets. We use the curvelet representation to partition the measured wavefield using DAS data collected near Ridgecrest, CA, following the 2019 Mw7.1 Ridgecrest earthquake. Here, we isolate the earthquake-induced wavefield from coherent and stochastic noise using the curvelet frame in an effort to improve the results of template matching of the Ridgecrest aftershock sequence. We show that our wavefield-partitioning technique facilitates the identification of over 30 per cent more aftershocks and greatly reduces the magnitude of diurnal depressions in the aftershock catalogue due to cultural noise. 

Fault zone complexities contain important information about factors controlling earthquake dynamic rupture. High‐resolution fault zone imaging requires high‐quality data from dense arrays and new seismic imaging techniques that can utilize large portions of recorded waveforms. Recently, the emerging Distributed Acoustic Sensing (DAS) technique has enabled near‐surface imaging by utilizing existing telecommunication infrastructure and anthropogenic noise sources. With dense sensors at several meters' spacing, the unaliased wavefield can provide unprecedented details for fault zones. In this work, we use a DAS array converted from a 10‐km underground fiber‐optic cable across Ridgecrest City, California. We report clear acausal and coda signals in ambient noise cross‐correlations caused by surface‐to‐surface wave scattering. We use these scattering‐related waves to locate and characterize potential faults. The mapped fault locations are generally consistent with those in the United States Geological Survey Quaternary Fault database of the United States but are more accurate than the extrapolated ones. We also use waveform modeling to infer that a 35 m wide, 90 m deep fault with 30% velocity reduction can best fit the observed scattered coda waves for one of the identified fault zones. These findings demonstrate the potential of DAS for passive imaging of fine‐scale faults in an urban environment.

 

Small‐scale intraslab heterogeneity is well documented seismically in multiple subduction zones, but its nature remains elusive. Previous efforts have been mostly focusing on the scattering strength at intermediate depth (<350 km), without constraining its evolution as a function of depth. Here, we illustrate that the inter‐source interferometry method, which turns deep earthquakes into virtual receivers, can resolve small‐scale intraslab heterogeneity in the mantle transition zone. The interferometric waveform observations in the Japan subduction zone require weak scattering (<1.0%) within the slab below 410 km. Combining with previous studies that suggest high heterogeneity level (∼2.5%) at intermediate depth, we conclude that the small‐scale intraslab heterogeneity weakens as slabs subduct. We suggest that the heterogeneities are caused by intraslab hydrous minerals, and the decrease in their scattering strength with depth reveals processes associated with dehydration of subducting slabs.