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Journal of Geophysical Research Oceans
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Freshwater Sources in the Global Ocean Through Salinity‐ δ 18 O Relationships: A Machine Learning Solution to a Water Mass Problem

Authors: Davila, Xabier; McDonagh, Elaine L.; Jebri, Fatma; Gebbie, Geoffrey; Meredith, Michael P.;

Freshwater Sources in the Global Ocean Through Salinity‐ δ 18 O Relationships: A Machine Learning Solution to a Water Mass Problem

Abstract

Abstract Changes in the hydrological cycle can affect ocean circulation and ventilation. Freshwater enters the ocean as meteoric water (MW; precipitation, river runoff, and glacial discharge) and sea ice meltwater (SIM). These inputs are traced using seawater salinity and stable oxygen isotopes in seawater, . We apply a self‐organizing map, a machine learning technique, to water mass properties to estimate the global distribution of the isotopic signature of MW by characterizing distinct salinity‐ relationships from two comprehensive data sets. The inferred is then used in a three‐endmember mixing model to provide a globally coherent MW and SIM contributions to the extratropical ocean freshwater budget. Through the use of , our results show the role of MW and SIM in dense water formation and the resulting interhemispheric asymmetry in the freshwater sources that fill the interior ocean freshwater budget. Trends drawn in ‐S space show a significant decrease in sea ice formation driving the freshening of Antarctic bottom water for the 1980–2023 period, whereas SIM is significantly increasing in parts of the Arctic halocline. The different roles of sea ice in dense water formation has implications for future ocean circulation under climate change, where machine learning techniques applied to have been proven to have utility in detecting such changes.

Country
United Kingdom
Keywords

meteoric water, machine learning, Antarctic bottom water, freshwater, sea ice, water mass

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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