The lack of observations at heights relevant to the wind energy industry constitutes a major challenge for the development of the next generation of offshore wind turbines (over 10 MW), which are expected to operate within the first few tens kilometres from the coast with turbine tips extending more than 250 m. Observations within the coastal zone, which proves to be complex by its very nature given that the site of sea breezes, low-level jets and land/sea transition are keys to both understanding the marine atmospheric boundary layer processes interacting with the turbine and parameterizing the wind profile well above the surface layer. These needs introduce difficulties associated with measuring wind properties in the region 150-500 m above the sea surface. This paper uses the virtual mast method to reconstruct the 10-min averaged wind profile 1.5 km offshore using a scanning Doppler LiDAR (Light Detection And Ranging) installed on the coastline. A novel method is proposed herein to increase the vertical resolution to 27 levels, from the sea surface to 500 m above sea level. Being mainly based on the homogeneity hypothesis, this method's sensitivity to wind direction is evaluated, while results are compared with reanalysis data at several heights. This method is then implemented as part of a 7-month test campaign on the northeastern Atlantic coast, yielding a dataset of wind profile measurements. An analysis of this dataset shows a 15.4% proportion of lowlevel jets, mainly originating from land at night, with a core well inside the rotor area of > 10 MW wind turbines. The power production is subsequently analysed for 10 MW, 15 MW and 22 MW wind turbines. Wind shear events above the design values are observed in 30% of all profiles, accounting for more than a third of the total power production. High shear events are found to be more probable during low-level jets (56% of the time), compared to no low-level jet events (26%). A description of low-level jets and high-shear events is thus key since these are situations where the wind profile differs from the standard values used for wind turbine design and may affect both the load and fatigue predictions.