High frequency (HF) radar installations are becoming essential components of operational real-time marine monitoring systems.\nThe underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields\nover wide areas with high spatial and temporal resolution, even in adversemeteo-marine conditions. Data applications are opening\nto many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national\nand regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the\nMalta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One\nkey drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by\ninterference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates\nthe use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained\nfrom satellites are used to predict missing information and provide a more consistent dataset.
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