Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

Wang, Wei-Lei; Song, Guisheng; Primeau, François; Saltzman, Eric S.; Bell, Thomas G.; Moore, J. Keith

doi:https://doi.org/10.5194/bg-17-5335-2020

Articles | Volume 17, issue 21

https://doi.org/10.5194/bg-17-5335-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-17-5335-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 21

Research article

|

06 Nov 2020

Research article |

| 06 Nov 2020

Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

Wei-Lei Wang, Guisheng Song, François Primeau, Eric S. Saltzman, Thomas G. Bell, and J. Keith Moore

Data sets

DMS concentration and flux climatologies Wang et al., https://doi.org/10.5281/zenodo.3833233

Short summary

Dimethyl sulfide, a volatile compound produced as a byproduct of marine phytoplankton activity, can be emitted to the atmosphere via gas exchange. In the atmosphere, DMS is oxidized to cloud condensation nuclei, thus contributing to cloud formation. Therefore, oceanic DMS plays an important role in regulating the planet's climate by influencing the radiation budget. In this study, we use an artificial neural network model to update the global DMS climatology and estimate the sea-to-air flux.