Wind information in urban areas is essential for many applications related to air pollution, urban climate and planning, safety of drone-related operations, and assessment of urban wind energy potential. These applications require accurate wind forecasts, and obtaining this information in an urban environment is challenging as the morphology of a city varies from street to street, altering the wind flow. Remote sensing techniques such as Doppler lidars (light detection and ranging) provide a unique opportunity for wind forecast verification as they can provide both the vertical profile of the horizontal wind and the spatial variation in the horizontal domain at high resolution. In this study, the performance of numerical weather prediction (NWP) models, analysis systems, and large-eddy simulation (LES) models have been analysed by comparing the modelled winds against Doppler lidar observations under various atmospheric conditions and from season to season, in the coastal environment of Helsinki, Finland. The long-term mean vertical profile of the modelled horizontal wind shows good agreement with observations; the NWP model and the analysis systems selected here exhibit different strengths and weaknesses depending on the atmospheric conditions but no significant diurnal variation in performance. However, both the model and analysis systems show differences in their spatially-averaged bias when investigating different wind directions. LES verification shows that these models can potentially provide winds down to Associated post doc with Vaisala through PoDoCo program.