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Abstract Typical use of ambient noise interferometry focuses on longer period (>1 s) waves for exploration of subsurface structure and other applications, while very shallow structure and some environmental seismology applications may benefit from use of shorter period (<1 s) waves. We explore the potential for short‐period ambient noise interferometry to determine shallow seismic velocity structures by comparing two methodologies, the conventional amplitude‐based cross‐correlation and linear stacking (TCC‐Lin) and a more recently developed phase cross‐correlation and time‐frequency phase‐weighted‐stacking (PCC‐PWS) method with both synthetic and real data collected in a heterogeneous karst aquifer system. Our results suggest that the PCC‐PWS method is more effective in extracting short‐period wave velocities than the TCC‐Lin method, especially when using data collected in regions containing complex shallow structures such as the karst aquifer system investigated here. In addition to the different methodologies for computing the cross correlation functions, we also examine the relative importance of signal‐to‐noise ratio and number of wavelengths propagating between station pairs to determine data/solution quality. We find that the lower number of wavelengths of 3 has the greatest impact on the network‐averaged group velocity curve. Lastly, we test the sensitivity of the number of stacks used to create the final empirical Green's function, and find that the PCC‐PWS method required about half the number of cross‐correlation functions to develop reliable velocity curves compared to the TCC‐Lin method. This is an important advantage of the PCC‐PWS method when available data collection time is limited.
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Surface Gravity Wave Interferometry and Ocean Current Monitoring With Ocean‐Bottom DAS
Abstract The cross‐correlation of a diffuse or random wavefield at two points has been demonstrated to recover an empirical estimate of the Green's function under a wide variety of source conditions. Over the past two decades, the practical development of this principle, termed ambient noise interferometry, has revolutionized the fields of seismology and acoustics. Yet, because of the spatial sparsity of conventional water column and seafloor instrumentation, such array‐based processing approaches have not been widely utilized in oceanography. Ocean‐bottom distributed acoustic sensing (OBDAS) repurposes pre‐existing optical fibers laid in seafloor cables as dense arrays of broadband strain sensors, which observe both seismic waves and ocean waves. The thousands of sensors in an OBDAS array make ambient noise interferometry of ocean waves straightforward for the first time. Here, we demonstrate the application of ambient noise interferometry to surface gravity waves observed on an OBDAS array near the Strait of Gibraltar. We focus particularly on a 3‐km segment of the array on the continental shelf, containing 300 channels at 10‐m spacing. By cross‐correlating the raw strain records, we compute empirical ocean surface gravity wave Green's functions for each pair of stations. We first apply beamforming to measure the time‐averaged dispersion relation along the cable. Then, we exploit the non‐reciprocity of waves propagating in a flow to recover the depth‐averaged current velocity as a function of time using a waveform stretching method. The result is a spatially continuous matrix of current velocity measurements with resolution <100 m and <1 hr.
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- Award ID(s):
- 1848166
- PAR ID:
- 10445939
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Oceans
- Volume:
- 127
- Issue:
- 5
- ISSN:
- 2169-9275
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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