More than 12 GW of offshore wind turbines are currently in operation in European waters. To optimise the use of the marine areas, wind farms are typically clustered in units of several hundred turbines. Understanding wakes of wind farms, which is the region of momentum and energy deficit downwind, is important for optimising the wind farm layouts and operation to minimize costs. While in most weather situations (unstable atmospheric stratification), the wakes of wind turbines are only a local effect within the wind farm, satellite imagery reveals wind-farm wakes to be several tens of kilometres in length under certain conditions (stable atmospheric stratification), which is also predicted by numerical models. The first direct in situ measurements of the existence and shape of large wind farm wakes by a specially equipped research aircraft in 2016 and 2017 confirm wake lengths of more than tens of kilometres under stable atmospheric conditions, with maximum wind speed deficits of 40%, and enhanced turbulence. These measurements were the first step in a large research project to describe and understand the physics of large offshore wakes using direct measurements, together with the assessment of satellite imagery and models.

[1] In this study a new empirical approach to retrieve integral ocean wave parameters from synthetic aperture radar (SAR) data is presented. The idea behind this computationally efficient technique is to estimate integral ocean wave parameters without the intermediate step of retrieving the two-dimensional ocean wave spectrum. The method has the radiometrically calibrated SAR image as the only source of information and is based on a quadratic model function with 22 input parameters. These parameters include the radar cross section, the image variance, and 20 parameters computed from the SAR image variance spectrum using a set of orthonormal functions. The coefficients of the quadratic function were fitted for the estimation of H s , the mean periods T m01 , T m02 , T À10 , the wave power, and the wave heights associated with different spectral bands. The fit procedure is based on a stepwise regression method. A data set of 12,000 globally distributed ERS-2 wave mode image spectra and colocated WAM ocean wave spectra was available for the study. Two separate subsets of 6000 collocation pairs each were used to fit the model and to carry out comparisons of the retrieved wave parameters with numerical model results. Additional comparisons were performed using NDBC buoy measurements. Scatterplots and global maps with the derived parameters are presented. It is shown that the rms of the SAR derived H s with respect to the WAM H s is about 0.5 m. For the mean period T mÀ10 an rms of 0.72 s with a high-frequency cutoff period of about 6 s is achieved.

We present an analysis of wind measurements from a series of airborne campaigns conducted to sample the wakes from two North Sea wind farm clusters, with the aim of determining the dependence of the downstream wind speed recovery on the atmospheric stability. The consequences of the stability dependence of wake length on the expected annual energy yield of wind farms in the North Sea are assessed by an engineering model. Wakes are found to extend for significantly longer downstream distances (>50 km) in stable conditions than in neutral and unstable conditions (<15 km). The parameters of one common engineering model are modified to reproduce the observed wake decay at downstream distances >30 km. More significant effects on the energy yield are expected for wind farms separated by distances <30 km, which is generally the case in the North Sea, but additional data would be required to validate the suggested parameter modifications within the engineering model. A case study is accordingly performed to show reductions in the farm efficiency downstream of a wind farm. These results emphasize not only the importance of understanding the impact of atmospheric stability on offshore wind farms but also the need to update the representation of wakes in current industry models to properly include wake-induced energy losses, especially in large offshore clusters. KEYWORDS atmospheric stability, offshore wind farm cluster, wake recovery, wind farm efficiency

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.

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