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During the past few years, distributed acoustic sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS—the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., urban centers, underground mines, and seafloor), spanning from several days to several years, offering both continuous and triggered active source recordings, and totaling up to ∼90 TB of data. This article describes these datasets, their metadata, and how to access and download them. Some of these datasets have only been shallowly explored, leaving the door open for new discoveries in Earth sciences and beyond.

Quantifying the response of human activity to different COVID-19 measures may serve as a potential way to evaluate the effectiveness of the measures and optimize them. Recent studies reported that seismic noise reduction caused by limited human activity due to the COVID-19 lockdown had been observed with seismometers. However, it is difficult for the current seismic infrastructure in urban cities to characterize spatiotemporal seismic noise during the post-COVID-19 lockdown, because of their sparse distribution. Here, we show key connections between progressive COVID-19 measures and spatiotemporal seismic noise changes recorded by a distributed acoustic sensing (DAS) array deployed in State College, Pennsylvania. We first show a spatiotemporal seismic noise reduction (up to 90%) corresponding to reduced human activity in different city blocks during the stay-at-home period. We also show partial noise recovery corresponding to increased road traffic and industrial machinery in phase yellow and phase green of the lockdown. Nonrecovery seismic noise in the 0.01–10 Hz band suggests the low level of pedestrian movement during phase yellow and phase green. According to a linear correlation between Google mobility change and seismic noise change, we emphasize that DAS recordings using city-wide fiber optics could provide a way for quantifying the impact of COVID-19 measures on human activity in different blocks.

Thunderstorms are a common atmospheric phenomenon that cause abundant acoustic disturbances, which can interact with the ground surface, creating a link between atmospheric and solid Earth processes. This article reports seismological observations of four thunderstorms through the spring and summer of 2019, as recorded by the distributed acoustic sensing fiber-optic array (4.9 km) on the Penn State campus in State College, Pennsylvania. With a dense sensor array in the local region, we are able to construct the seismic full waveform response of the thunderstorm events (hereafter referred to as thunderquakes) and track the wave propagation across the array. We use a time-domain grid search to obtain the back azimuth and slowness of the waves, and a modified Geiger’s method to pinpoint source locations of the thunderquakes. Correlated with the time of the recorded signal, this data allows reconstruction of thunderstorm movement as well as offering measurements of the seismic velocity.