Light Detection and Ranging (LIDAR) systems are able to measure the speed of incoming wind before it interacts with a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine loads. However, the degree to which such preview-based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. Past studies have assumed Taylor's frozen turbulence hypothesis, which implies that turbulence remains unchanged as it advects downwind at the mean wind speed. With Taylor's hypothesis applied, the only source of wind speed measurement error is distortion caused by the LIDAR. This study introduces wind evolution, characterized by the longitudinal coherence of the wind, to LIDAR measurement simulations to create a more realistic measurement model. A simple model of wind evolution is applied to a frozen wind field used in previous studies to investigate the effects of varying the intensity of wind evolution. Simulation results show the combined effects of LIDAR errors and wind evolution for realistic turbine-mounted LIDAR measurement scenarios.Nomenclature a decay parameter for exponential coherence a l decrement parameter for transverse coherence (l ∈ {u, v, w}) b l offset parameter for transverse coherence (l ∈ {u, v, w}) D longitudinal distance between two points or measurement preview distance F focal distance f frequency (Hz) θ LIDAR measurement angle off of longitudinal direction k wind velocity wavenumber (m −1 ) λ wavelength (m) R range along LIDAR beam r scan radius for spinning LIDAR scenario r i,j distance between two points in the yz plane U mean wind speed (m/s) u i,j average mean wind speed between two points in the yz plane ψ azimuth angle in the rotor plane γ 2 xy (f ) Coherence between signals x and y