Sea surface Dimethylsulfide Concentration and Emission Flux over the North Atlantic Ocean

The dataset represents gridded monthly time series of seawater dimethylsulfide (DMS) concentration and total cumulative sea-to-air emission fluxes over the North Atlantic at a spatial resolution of 0.25°×0.25°. The seawater DMS data were generated using a Gaussian process regression (GPR) model to predict daily concentrations across the North Atlantic Ocean. The predictors used are: CHL, MLD, NO₃, PAR, SSS, Si and SST. The daily sea-to-air DMS flux was calculated using gas transfer velocity (Blomquist et al., 2017) and DMS derived from GPR predictions. The monthly total cumulative emission fluxes (EDMS) were computed by integrating the daily sea-to-air DMS flux over the area of each pixel within the domain and over the days of the month.

Further information can be found in the following references:

• Mansour K., Decesari S., Ceburnis D., Ovadnevaite J. and Rinaldi M. (2023). Machine learning for prediction of daily sea surface dimethylsulfide concentration and emission flux over the North Atlantic Ocean (1998–2021)  Science of The Total Environment 871. https://doi.org/10.1016/j.scitotenv.2023.162123.
• Mansour K., Decesari S., Ceburnis D., Ovadnevaite J., Russell L. M., Paglione M., Poulain L., Huang S., O'Dowd C. and Rinaldi M. (2024). IPB-MSA&SO₄: a daily 0.25° resolution dataset of in situ-produced biogenic methanesulfonic acid and sulfate over the North Atlantic during 1998–2022 based on machine learning Earth System Science Data 16 2717–40. https://doi.org/10.5194/essd-16-2717-2024.
• Mansour K., Decesari S., Paglione M., Becagli S. and Rinaldi M. (2024). Nested cross-validation Gaussian process to model dimethylsulfide mesoscale variations in warm oligotrophic Mediterranean seawater npj Climate and Atmospheric Science 7. https://doi.org/10.1038/s41612-024-00830-y.