Vertical temperature profiles influence the wind power generation of large offshore wind farms through stability-dependent effects such as blockage and gravity waves. However, numerical tools that are used to model these effects are often computationally too expensive to cover the large variety of atmospheric states occurring over time. Generally, an informed decision about which representative nonidealized situations to simulate is missing because of the lack of easily available information on representative vertical profiles, taking into account their spatiotemporal variability. Therefore, we present a novel framework that allows a smart selection of vertical temperature profiles. The framework consists of an improved analytical temperature model for the atmospheric boundary layer and lower troposphere, a subsequent clustering of these profiles to identify representatives, and last, a determination of areas with similar spatiotemporal characteristics of vertical profiles. When applying this framework on European ERA5 data, physically realistic representatives were identified for Europe, excluding the Mediterranean. Two or three profiles were found to be dominant for the open ocean, whereas more profiles prevail for land. Over the open ocean, weak temperature gradients in the boundary layer and a clear capping inversions are widespread, and stable profiles are absent except in the region of the East Icelandic Current. Interestingly, according to the ERA5 data, at its resolution, coastal areas and seas surrounded by land behave more similar to the land areas than to the open ocean, implying that a larger set of model integrations are needed for these areas to obtain representative results for offshore wind power assessments in comparison with the open ocean.

In this paper we report the results of a workshop organised by the Delft University of Technology in 2014,
aiming at the comparison between different state-of-the-art numerical models for the simulation of
wind turbine wakes. The chosen benchmark case is a wind tunnel measurement, where stereoscopic
Particle Image Velocimetry was employed to obtain the velocity field and turbulence statistics in the near
wake of a two-bladed wind turbine model and of a porous disc, which mimics the numerical actuator
used in the simulations. Researchers have been invited to simulate the experimental case based on the
disc drag coefficient and the inflow characteristics. Four large eddy simulation (LES) codes from different
institutions and a vortex model are part of the comparison. The purpose of this benchmark is to validate
the numerical predictions of the flow field statistics in the near wake of an actuator disc, a case that is
highly relevant for full wind farm applications. The comparison has shown that, despite its extreme
simplicity, the vortex model is capable of reproducing the wake expansion and the centreline velocity
with very high accuracy. Also all tested LES models are able to predict the velocity deficit in the very near
wake well, contrary to what was expected from previous literature. However, the resolved velocity
fluctuations in the LES are below the experimentally measured values.