Super-large-scale particle image velocimetry (SLPIV) using natural snowfall is used to investigate the influence of nacelle and tower generated flow structures on the near-wake of a 2.5 MW wind turbine at the EOLOS field station. The analysis is based on the data collected in a field campaign on March 12th, 2017, with a sample area of 125 m (vertical) x 70 m (streamwise) centred on the plane behind the turbine support tower. The SLPIV measurement provides the velocity field over the entire rotor span, revealing a region of accelerated flow around the hub caused by the reduction in axial induction at the blade roots. The in-plane turbulent kinetic energy field shows an increase in turbulence in the regions of large shear behind the blade tips and the hub, and a reduction in turbulence behind the tower where the large-scale turbulent structures in the boundary layer are broken up. Snow voids reveal coherent structures shed from the blades, nacelle, and tower. The hub wake meandering frequency is quantified and found to correspond to the vortex shedding frequency of an Ahmed body (St=0.06). Persistent hub wake deflection is observed and shown to be connected with the turbine yaw error. In the region below the hub, strong interaction between the tower- and blade-generated structures is observed. The temporal characteristics of this interaction are quantified by the co-presence of two dominant frequencies, one corresponding to the blade vortex shedding at the blade pass frequency and the other corresponding to tower vortex shedding at St=0.2. This study highlights the influence of the tower and nacelle on the behaviour of the near-wake, informing model development and elucidating the mechanisms that influence wake evolution.
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