Abstract | The wind hazard is assessed for the Egnatia Odos highway in Greece by considering Climate Change effects via the Euro-CORDEX future climatic projections. The aim is to derive spatially correlated region-wide wind fields for a stochastic event set of thousands of storm realizations that are suitable for risk and resilience assessment of the entire highway network. The coarse spatial and temporal resolutions of the Euro-CORDEX wind projections prohibit their use as a direct input in weather-related risk and resilience assessment of highway structures that may measure down to a few meters in size and require at most 10-min average wind speeds. To improve the temporal scale resolution, we leverage machine learning tools and continuous measurements from National weather stations to generate composite “Frankenstein” days comprising 144 jigsaw pieces of actually measured 10-min wind time-histories that are scaled and matched together to form a continuous daily record. These point-estimates, valid only at the locations of the weather stations, are expanded spatially by employing high-fidelity Computational Fluid Dynamic simulations that take into account the topographic complexity of the site to simulate turbulent wind flows, thus generating spatially correlated wind fields of 10-min average wind speeds. These allow estimating load distribution and risk on (i) an event-by-event basis and (ii) in the long-term for an ensemble of spatially-distributed highway assets that are vulnerable to wind actions, such as signpost bridges and power network pylons.