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Seismic ocean thermometry uses sound waves generated by repeating earthquakes to measure temperature change in the deep ocean. In this study, waves generated by earthquakes along the Japan Trench and received at Wake Island are used to constrain temperature variations in the Kuroshio Extension region. This region is characterized by energetic mesoscale eddies and large decadal variability, posing a challenging sampling problem for conventional ocean observations. The seismic measurements are obtained from a hydrophone station off and a seismic station on Wake Island, with the seismic station's digital record reaching back to 1997. These measurements are combined in an inversion for the time and azimuth dependence of the range‐averaged deep temperatures, revealing lateral and temporal variations due to Kuroshio Extension meanders, mesoscale eddies, and decadal water mass displacements. These results highlight the potential of seismic ocean thermometry for better constraining the variability and trends in deep‐ocean temperatures. By overcoming the aliasing problem of point measurements, these measurements complement existing ship‐ and float‐based hydrographic measurements.
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This content will become publicly available on May 1, 2026
Estimating temperature variability and trends from a combination of seismic and in situ data
Estimating the large-scale variability and trends in subsurface ocean temperatures is limited by sparse in situ observations inadequate for resolving mesoscale eddies. Travel times of seismically generated sound waves, sensitive to path-integrated temperature, provide complementary integral constraints. We here use earthquakes along the Japan Trench and receivers at Wake Island to sample the Kuroshio Extension region in the Northwest Pacific. We develop a Gaussian process framework, optimized via maximum likelihood, to estimate temperature anomalies and uncertainties from this seismic data and to combine it with in situ data from Argo profiles and shipboard data. This framework shows seismic measurements are quantitatively consistent with in situ data and substantially reduce uncertainties in large-scale variability and trends. Relative to their prior, error variances of area-mean temperature fluctuations due to mesoscale eddies from 2008 to 2021 are reduced by 30% by the in situ data, 39% by the seismic data and 50% by the combination. For path-mean estimates, the combined reduction is 83% in error variances, compared to 45% from in situ data alone. The data show a steady subsurface warming of 11.8±5.0 mK/yr (2σ uncertainty) from 2008 to 2021 and no substantial trend between 1997 and 2008.
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- Award ID(s):
- 2023161
- PAR ID:
- 10639746
- Publisher / Repository:
- Royal Society
- Date Published:
- Journal Name:
- Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Volume:
- 481
- Issue:
- 2313
- ISSN:
- 1364-5021
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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