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Abstract Barystatic sea level rise (SLR) caused by the addition of freshwater to the ocean from melting ice can in principle be recorded by a reduction in seawater salinity, but detection of this signal has been hindered by sparse data coverage and the small trends compared to natural variability. Here, we develop an autoregressive machine learning method to estimate salinity changes in the global ocean from 2001 to 2019 that reduces uncertainties in ocean freshening trends by a factor of four compared to previous estimates. We find that the ocean mass rose by 13,000 ± 3,000 Gt from 2001 to 2019, implying a barystatic SLR of 2.0 ± 0.5 mm/yr. Combined with SLR of 1.3 ± 0.1 mm/yr due to ocean thermal expansion, these results suggest that global mean sea level rose by 3.4 ± 0.6 mm/yr from 2001 to 2019. These results provide an important validation of remote‐sensing measurements of ocean mass changes, global SLR, and global ice budgets.
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Global mean sea level rise inferred from ocean salinity and temperature changes
Barystatic sea level rise caused by the addition of freshwater to the ocean from melting ice can in principle be recorded by a reduction in seawater salinity, but detection of this signal has been hindered by sparse data coverage and the small trends compared to natural variability. Here, we develop an autoregressive machine learning method to estimate salinity changes in the global ocean from 2001-2019 that reduces uncertainties in ocean freshening trends by a factor of four compared to previous estimates. We find that the ocean mass rose by 13,000±3,000 Gt from 2001-2019, implying a barystatic sea level rise of 2.0±0.5 mm/yr. Combined with sea level rise of 1.3±0.1 mm/yr due to ocean thermal expansion, these results suggest that global mean sea level rose by 3.4±0.6 mm/yr from 2001-2019. These results provide an important validation of remote-sensing measurements of ocean mass changes, global sea level rise, and global ice budgets.
more »
« less
- Award ID(s):
- 1948985
- PAR ID:
- 10630646
- Publisher / Repository:
- figshare
- Date Published:
- Subject(s) / Keyword(s):
- Climatology Oceanography not elsewhere classified
- Format(s):
- Medium: X Size: 917590307 Bytes
- Size(s):
- 917590307 Bytes
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
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