High-resolution meteocean and seismic dataset for AI modeling of seawater CO₂ at Deception Island
The full DeceptionCO2 dataset is included in a zip file and divided into four files. The main dataset combines georeferenced time-series measurements from oceanographic, meteorological, and geophysical sources and is organized in the Deception_2025_CO2_ocean_meteo_seismic.csv file. Estimated surface...
| Autores: | , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | conjunto de datos |
| Estado: | Versión publicada |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/418839 |
| Acceso en línea: | http://hdl.handle.net/10261/418839 |
| Access Level: | acceso abierto |
| Palabra clave: | GHG emission accounts Ocean acidification levels Machine learning technique Climate change (as an object of study) Chemical oceanography Oceanography Environmental monitoring |
| Sumario: | The full DeceptionCO2 dataset is included in a zip file and divided into four files. The main dataset combines georeferenced time-series measurements from oceanographic, meteorological, and geophysical sources and is organized in the Deception_2025_CO2_ocean_meteo_seismic.csv file. Estimated surface pCO2, aligned with in situ observations and spatio-temporal data, is included in the additional Deception_2025_CO2_predictions.csv file. Both CSV files are in semicolon format. Each data file also includes a README file in text format that describes general information about the datasets. |
|---|