Articles | Volume 19, issue 6
https://doi.org/10.5194/bg-19-1705-2022
https://doi.org/10.5194/bg-19-1705-2022
Research article
 | 
24 Mar 2022
Research article |  | 24 Mar 2022

Improved prediction of dimethyl sulfide (DMS) distributions in the northeast subarctic Pacific using machine-learning algorithms

Brandon J. McNabb and Philippe D. Tortell

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Latest update: 19 Jul 2024
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Short summary
The trace gas dimethyl sulfide (DMS) plays an important role in the ocean sulfur cycle and can also influence Earth’s climate. Our study used two statistical methods to predict surface ocean concentrations and rates of sea–air exchange of DMS in the northeast subarctic Pacific. Our results show improved predictive power over previous approaches and suggest that nutrient availability, light-dependent processes, and physical mixing may be important controls on DMS in this region.
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