Our current understanding of the interaction between the atmosphere and surface obstacles crucial for boundary-layer meteorology, forestry, urban climate, wind engineering, and wind energy is limited mainly to observations acquired in wind tunnel experiments and flow predictions from computational fluid dynamic models. Here, as a case study, we present spatially distributed measurements of a utility-scale wind turbine’s wake using three wind lidars that synchronously scan a volume of the atmosphere. The results reveal not only information of the mean wake flow generated by a wind turbine, such as the distribution of the velocity deficit and its spatial gradients, but also observations of the momentum fluxes that control the interaction between the wake and the surrounding atmospheric flow, which is essential for optimizing wind energy production. The presented remote sensing methodology represents a paradigm shift for atmospheric field studies, enabling unprecedented flow observations.