  As wind energy expands worldwide, the demand of reliable, fast,
cost-efficient wind turbine wake models is growing. This is a significant
challenge as wind turbines face various inflow conditions, that include
turbulence, inhomogeneities/instationarities and upstream wakes. In
consequence, an enormous number of engineering models, each one based on
different physical concepts, has been proposed. The majority focuses on the far
wake where the mean velocity recovers and turbulence decays after it built up.
We argue that the most important, or the leading, parameter for wake modeling
is the length scale of a virtual origin. Testing different models from the
literature for data sets from laboratory wind turbines and multi-megawatt
turbines obtained by LiDAR, we find that all models perform significantly
better when such a virtual origin is added. Our results can therefore be used
for a yet missing definition of a near wake zone.
