High Frequency Radar (HFR) technology refers to land based remote sensing instruments capable of measuring surface currents and ocean waves at ranges up to 200 km or more. HFR technology is widely acknowledged as a cost-efficient tool to monitor coastal regions and has potential use to monitor coastal regions all over the world. Globally, the number of HFR stations is steadily increasing. Regional networks provide real-time data in support of operational activities such as search and rescue operations, fast response in case of maritime accidents and spill of pollutants, and resource management. Each operator needs a general understanding of the working principles in order to ensure that instruments are managed properly. A set of harmonized quality assurance and quality control procedures is recommended, along with an effective approach to HFR data discovery and dissemination, to provide high quality measurements to the end users. Different documents providing best practices for operation and maintenance have emerged in the past years. They are oriented either to Direction Finding (DF) or Beam Forming (BF) systems, or to specific manufacturer’s radar systems. The main objective of this paper is to offer a comprehensive “Best Practices” document in an effort of ensuring consistency between different deployments and harmonized operations of HFR systems. This, regardless of system manufacturer, antenna design and setup. A homogeneous approach is given when possible, general concepts and definitions are introduced in order to provide a framework for both data processing and management steps. Examples are also given from the European HFR users with focus on Near Real Time data flow suitable for operational services.

Ocean practices, intended as a wide spectrum of methodologies supporting ocean-related research, operations, and applications, are constantly developed and improved to enable informed decision-making. Practices start from the idea of an individual or a group and often evolve towards what can be called good or best practices. This bottom-up approach may in principle result in different paths for the evolution of each practice, and ultimately generate situations where it is not clear to a new user how to compare two practices aiming at the same objective, and determine which one is best. Also, although a best practice is supposed to be the result of a multi-institutional collaborative effort based on the principles of evidence, repeatability and comparability, a set of individual requirements is not yet defined in literature for a practice to be considered a good, better, and ultimately a best practice. This paper proposes a method for addressing those questions and presents a new maturity model for ocean practices, built upon existing maturity models for systems and software, developed and adopted in the last decades. The model provides attributes for assessing both the maturity of the practice description and its implementation. It also provides a framework for analyzing gaps and suggesting actions for practice evolution. The model has been tested against a series of widely adopted practices and the results are reported and discussed. This work facilitates a common approach for developing and assessing practices, from which greater interoperability and trust can be achieved.

In this paper, a high-frequency (HF) coastal radar network is described, which is established and maintained by the Institute of Marine Sciences (ISMAR) of the National Research Council of Italy (CNR) for the measurement of surface current velocities in the Gulf of Manfredonia, located in the semienclosed Adriatic Sea (Mediterranean Sea), during 2013–2015. The network consisted of four HF radars (HFRs) that provided hourly sea surface velocity data in real-time mode in a netCDF format compliant to the Climate and Forecast Metadata Conventions CF-1.6 and the INSPIRE directive. The hourly netCDF files are disseminated via a Thematic Real-time Environmental Distributed Data Services catalog supporting OGC compliant distributions and protocols for data visualization, metadata interrogation, and data download. HFR velocity data were compared with in situ velocity measurements by Global Positioning System tracked surface drifters deployed within the radar footprint. The results show a good agreement, with the root mean square (rms) of the difference between radial velocities from HFR and drifters ranging between $20\%$ and $50\%$ of the drifter velocity rms. The HFR data have also been compared with subsurface velocity profiles from an upward looking acoustic Doppler current profiler (ADCP) during winter 2015, to gain information on the correlation between surface and water column velocities. This information is especially relevant for fishery and coastal management applications, where transport of larvae, sediments, and pollutants in the water column are considered. Results show that, at least in the considered period, the velocity in the water column is well correlated, and there is a good agreement between surface HFR and ADCP data (correlations between 0.95 and 0.75). The Gulf of Manfredonia network has been instrumental to the set up of a core of quality control practices and interoperable data and metadata formats that have been subsequently adopted within the Italian RITMARE network and that are presently discussed and refined at the European level through the projects Jerico-NEXT and INCREASE.

High-frequency radars (HFRs) provide remote information on ocean surface velocity in extended coastal areas at high resolutions in space ($\mathcal{O}$(km)) and time ($\mathcal{O}$(h)). They directly produce radial velocities (in the radar antenna’s direction) combined to provide total vector velocities in areas covered by at least two radars. HFRs are a key element in ocean observing systems, with several important environmental applications. Here, we provide an assessment of the HFR-TirLig network in the NW Mediterranean Sea, including results from the gap-filling open-boundary modal analysis (OMA) using in situ velocity data from drifters. While the network consists of three radars, only two were active during the assessment experiment, so the test also includes an area where the radial velocities from only one radar system were available. The results, including several metrics, both Eulerian and Lagrangian, and configurations, show that the network performance is very satisfactory and compares well with the previous results in the literature in terms of both the radial and total combined vector velocities where the coverage is adequate, i.e., in the area sampled by two radars. Regarding the OMA results, not only do they perform equally well in the area sampled by the two radars but they also provide results in the area covered by one radar only. Even though obviously deteriorated with respect to the case of adequate coverage, the OMA results can still provide information regarding the velocity structure and speed as well as virtual trajectories, which can be of some use in practical applications. A general discussion on the implications of the results for the potential of remote sensing velocity estimation in terms of HFR network configurations and complementing gap-filling analysis is provided.