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High Frequency Radar (HFR) is a land-based remote sensing instrument offering a unique insight to coastal ocean variability, by providing synoptic, high frequency and high resolution data at the ocean atmosphere interface. HFRs have become invaluable tools in the field of operational oceanography for measuring surface currents, waves and winds, with direct applications in different sectors and an unprecedented potential for the integrated management of the coastal zone. In Europe, the number of HFR networks has been showing a significant growth over the past 10 years, with over 50 HFRs currently deployed and a number in the planning stage. There is also a growing literature concerning the use of this technology in research and operational oceanography. A big effort is made in Europe toward a coordinated development of coastal HFR technology and its products within the framework of different European and international initiatives. One recent initiative has been to make an up-to-date inventory of the existing HFR operational systems in Europe, describing the characteristics of the systems, their operational products and applications. This paper offers a comprehensive review on the present status of European HFR network, and discusses the next steps toward the integration of HFR platforms as operational components of the European Ocean Observing System, designed to align and integrate Europe's ocean observing capacity for a truly integrated end-to-end observing system for the European coasts.

Wind fields retrieved from high-resolution synthetic aperture radar (SAR) images are valuable in wind resource assessment offshore. In contrast to in situ measurements, SAR wind maps provide spatial information which allows wind farm developers to compare the wind resource for different sites. Further advantages include the opportunity to obtain archived data and a low cost of satellite based assessments compared to the cost of installing a meteorological mast offshore. Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. Wind speeds retrieved from a series of 97 high-resolution ERS-2 SAR and Envisat ASAR images, at moderate wind speeds (2-15 m s-1), were validated against in situ measurements from an offshore mast in the North Sea. The wind direction input, necessary for SAR wind speed retrievals, was obtained from the meteorological mast and from a local gradient analysis of streaks in the SAR images. For the first method, a standard deviation of ~1.1 m s-1 was found. The second method, which worked independently of in situ measurements, yielded a standard deviation of ~1.3 m s-1. The performance of three geophysical model functions was compared. The best approximation to the in situ measurements of wind speed was found for CMOD-IFR2, despite a bias on the order of-0.3 m s-1. CMOD4 retrievals also underestimated the wind speed, whereas the bias on CMOD5 retrievals was negligible. The accuracy on SAR wind retrievals improved as cases with a long fetch and near-neutral atmospheric stability were analyzed separately. The mean wind speed, obtained from the 97 SAR scenes, was linked closely to the bias on SAR wind retrievals. Agreement to ±15% of the in situ measurements was found for all the wind retrieval methods tested.

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