Articles | Volume 19, issue 6
https://doi.org/10.5194/bg-19-1705-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.Improved prediction of dimethyl sulfide (DMS) distributions in the northeast subarctic Pacific using machine-learning algorithms
Data sets
bjmcnabb/DMS_Climatology: DMS_Climatology publication (v1.0.0) https://doi.org/10.5281/zenodo.6354169
An updated climatology of surface dimethlysulfide concentrations and emission fluxes in the global ocean (https://www.bodc.ac.uk/solas_integration/implementation_products/group1/dms/) 10/dbqjrm
Model code and software
bjmcnabb/DMS_Climatology: DMS_Climatology publication (v1.0.0) https://doi.org/10.5281/zenodo.6354169