Filtered HF Radar Surface Current Fields from CODAR DF System – Ligurian and N. Tyrrhenian Seas (Quality-Restricted Thresholds Applied)

This dataset provides hourly surface current velocity fields derived from a high-frequency (HF) radar network operating at 13.5 MHz using a CODAR SeaSonde Direction Finding system. The radar network consists of three coastal stations located at Livorno (LIVO), San Vincenzo (SVIN), and Isola del Tino (TINO), covering a large portion of the Ligurian and Northern Tyrrhenian Seas. Radial current measurements are collected on a polar grid with approximately 1.5 km radial resolution and 5° angular spacing. These radial components are then combined into total vector current fields using a least-squares method. The resulting velocities represent surface currents in the upper ~0.3 to 2.5 meters of the water column and are aggregated over 1-hour intervals centered on the cardinal hour. The dataset has been filtered using different threshold configurations of the VART_QC (temporal variance) and MDFL_QC (median) filters, with cutoff values ranging from 0.182 to 1 m/s. These variants allow users to evaluate the impact of quality control settings on spatial coverage and data reliability. Data are georeferenced using the WGS84 geographic coordinate system (EPSG:4326), with a spatial extent approximately between 41.5°–44.5° N and 8.5°–12.5° E. All data are stored in NetCDF-4 classic model format and conform to the CF-1.6 and Copernicus InSitu-TAC metadata conventions. This dataset corresponds to a subset of HF radar observations recorded between October and November 2020, specifically selected for its temporal overlap with drifter deployments and for use in data validation and modeling applications. The data are owned by the LaMMA Consortium (Consorzio LaMMA).An extended version of the HF radar dataset is available at the following link:https://thredds.hfrnode.eu:8443/thredds/NRTcurrent/HFR-LaMMA/HFR-LaMMA_catalog.html(hosted on the European HFR data-sharing server, part of the EuroGOOS HFR Task Team network).