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- Title
A Mediterranean drifter dataset.
- Authors
Ribotti, Alberto; Bussani, Antonio; Menna, Milena; Satta, Andrea; Sorgente, Roberto; Cucco, Andrea; Gerin, Riccardo
- Abstract
Over a hundred experiments were conducted between 1998 and 2022 in the Mediterranean Sea using surface Lagrangian drifters at coastal and offshore levels. Raw data were initially unified and pre-processed manually by eliminating spikes and wrong positions or date/time information. The integrity of the received data packages was checked, and incomplete ones were discarded. Deployment information was retrieved for each drifter and integrated into the PostgreSQL database, realized and maintained by the National Institute of Oceanography and Applied Geophysics (OGS) in Trieste (Italy). This database also collects a variety of metadata about the drifter model, project, owner, and operator. Subsequently, data were processed using standard procedures of editing and quality control developed for the OGS drifter dataset to remove spikes generated by malfunctioning of the sensors and to obtain files with common characteristics. Drifter data and plots of each track were also visually checked to remove any point not identified by the automatic procedure and which were clearly erroneous. Drifter trajectories were split into two or more segments that are considered different deployments in the case of specific drifter behaviour. Data were interpolated at defined time intervals providing a dataset of 158 trajectories, available from the public open-access repository of SEA scieNtific Open data Edition (SEANOE) at 10.17882/90537 (Ribotti et al., 2022), in two versions (one compliant with the Copernicus format and the other one usable with Panoply netCDF viewer), and of SeaDataNet at https://cdi.seadatanet.org/search/welcome.php?query=2610&query%5fcode={9F00DF80-1881-42DD-9DF1-B9BD0282F2B0} (last access: 5 October 2023).
- Subjects
TRIESTE (Italy); DATABASES; ELECTRONIC data processing; GEOPHYSICS; OCEANOGRAPHY; QUALITY control
- Publication
Earth System Science Data, 2023, Vol 15, Issue 10, p4651
- ISSN
1866-3508
- Publication type
Article
- DOI
10.5194/essd-15-4651-2023