Machine-Learning-Derived Dimethyl Sulphide (DMS) estimation for North Atlantic across 2002-2024 (2002-2009 Subset)
Abstract
DMS Dataset for olfactory navigation and related research. The data was produced from machine learning ensemble methods, with a fine spatio-temporal resolution of 4km, daily. See the author's article for technical details and workflow. The dataset covers 04/07/2002-22/06/2024, latitude [0, 60], and longitude [-80, 15]. Due to upload limitations, the daily DMS 2D fields were aggregated into monthly 3D fields with time dimensions, saved as netcdf files. The 22-year DMS dataset will be split into three uploads. For more convenient data query and annotation, the AniDMS Python package is recommended. This upload contains metadata recording the gaps from satellite data for users to look up, which will not be downloaded or cached via AniDMS.
Fields of Study & Subjects
Marine and coastal ecosystems
Atmospheric chemistry and aerosols
Atmospheric and Environmental Gas Dynamics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 12 February 2026
- Language
- EN
- Document type
- Dataset