## 1 Introduction  
There is need for accurate information on ocean winds for offshore wind farms and turbine clusters in the Northern European Seas. In large offshore wind farm projects the economic risk is considerably reduced when accurate wind data are available at hub height for a minimum of one year. For a decrease in uncertainty on the predicted mean wind speed at hub height of 0.1 m\(\cdot\)s\({}^{-1}\) there is an estimated saving worth around PS10 million per year for 25 years for a large offshore wind farm project according to industry experts. The cost of installing and operating tall meteorological masts has increased in recent years and has a price tag around PS10 million for a two-year campaign, thus alternatives are desirable. The motivation for choosing lidar remote sensing technology is to provide ocean wind data at higher levels than meteorological masts' typical span and at the same time to ensure high accuracy wind speed measurements at relatively low cost. The need for improved knowledge on winds at higher levels is twofold: Firstly modern wind turbines, especially offshore, are increasing in dimension and the flow across their large rotors is not well-explained by hub height winds alone [1]. Secondly the marine atmospheric boundary layer and its temporal behavior at higher levels are poorly known. There is a need for improved parameterizations of the marine vertical wind profiles in order to improve modeling of offshore winds for wind energy [2] and to experimentally evaluate atmospheric wind resource model predictions against offshore winds [3]. Wind lidar remote sensing has had a very rapid growth and dissemination within the wind energy community in recent years. The early experiments at DTU Wind Energy (formerly Riso) with a focused continuous wave (cw) Doppler wind lidar took place onshore over flat terrain at Hovsore near the tall meteorological mast in 2003 [4]. This was followed by an experimental deployment offshore on the Fino-1 platform in 2005 [5], the Nysted 1 offshore wind farm transformer platform in 2006 [6] and the Horns Rev 1 offshore wind farm transformer platform in 2007 [2]. At all three offshore sites meteorological masts were located nearby and the concurrent meteorological observations were used for comparisons to the lidar observations. The data analysis from these early offshore experiments gave promising results. This fact stimulated the idea for using an array of wind profiling lidars in the Northern European Seas where the majority of European offshore wind farms are planned but where the knowledge of the wind resources is limited. In the EU FP7 Northern Sea Wind Index Database (NORSEWiND) investigation from 2008 to 2012 [7] nine lidars were deployed on offshore platforms in the North Sea and one lidar was deployed near the coast of the Norwegian island of Utsira. The research objectives of the NORSEWiND project included systematic analysis of the marine wind shear observed from the lidars [8] and investigation of the flow distortion around the offshore platforms [9]. It was important to investigate the platforms' influence on the free stream wind speed profiles at hub height. Other results from the project included a wind atlas based on numerical modeling and satellite data [3, 10-15]. The wind atlas is public available from the project web-site. The purpose of this article is to present the lessons learnt on the lidar measurement technique, deployment strategies and pre- and post- deployment validation including the definition of data quality acceptance levels: the so-called \"NORSEWiND standard\". Also the requirements for installation setup, the data availability, system consistency and multi-year performance are described. The work demonstrates the data management strategy for reliable application of lidar data. The measurement of flow distortion by the platforms using sub-scale models in a wind tunnel and computational fluid dynamics is described with the aim to clarify the level of flow distortion influence on the lidar wind profile observations at hub height.