RESUMEN
Distributed acoustic sensing (DAS) is a technology that turns a fiber-optic cable into an acoustic sensor by measuring the phase change of backscattered light caused by changes in strain from an acoustic field. In October 2022, 9 days of DAS and co-located hydrophone data were collected in the Puget Sound near Seattle, WA. Passive data were continuously recorded for the duration and a broadband source was fired from several locations and depths on the first and last days. This dataset provides comparisons between DAS and hydrophone measurements and demonstrates the ability of DAS to measure acoustics signals up to â¼700 Hz.
RESUMEN
Distributed acoustic sensing (DAS) is a technique that measures strain changes along an optical fiber to distances of â¼100 km with a spatial sensitivity of tens of meters. In November 2021, 4 days of DAS data were collected on two cables of the Ocean Observatories Initiative Regional Cabled Array extending offshore central Oregon. Numerous 20 Hz fin whale calls, northeast Pacific blue whale A and B calls, and ship noises were recorded, highlighting the potential of DAS for monitoring the ocean. The data are publicly available to support studies to understand the sensitivity of submarine DAS for low-frequency acoustic monitoring.
RESUMEN
Stearns and van der Veen (Reports, 20 July 2018, p. 273) conclude that fast glacier sliding is independent of basal drag (friction), even where drag balances most of the driving stress. This conclusion raises fundamental physical issues, the most striking of which is that sliding velocity would be independent of stresses imparted through the ice column, including gravitational driving stress.
RESUMEN
The Greenland ice sheet presently accounts for ~70% of global ice sheet mass loss. Because this mass loss is associated with sea-level rise at a rate of 0.7 mm/year, the development of improved monitoring techniques to observe ongoing changes in ice sheet mass balance is of paramount concern. Spaceborne mass balance techniques are commonly used; however, they are inadequate for many purposes because of their low spatial and/or temporal resolution. We demonstrate that small variations in seismic wave speed in Earth's crust, as measured with the correlation of seismic noise, may be used to infer seasonal ice sheet mass balance. Seasonal loading and unloading of glacial mass induces strain in the crust, and these strains then result in seismic velocity changes due to poroelastic processes. Our method provides a new and independent way of monitoring (in near real time) ice sheet mass balance, yielding new constraints on ice sheet evolution and its contribution to global sea-level changes. An increased number of seismic stations in the vicinity of ice sheets will enhance our ability to create detailed space-time records of ice mass variations.