Official URL: https://doi.org/10.1029/2025JC022808

Understanding projected changes in wave heights influenced by climate‐driven factors, such aswind, sea ice, and sea level are essential for mitigating risks and ensuring sustainable use of marine andcoastal resources, especially in a highly energetic wave region like the Northeast Atlantic (NEA). With aparticular focus on Ireland, wave climate in the Northeast Atlantic region is investigated using wave models,WAM (WAve Model) and SWAN (Simulating WAves Nearshore). These are driven by high‐resolutionsurrogate winds, incorporating sea ice and sea level as additional inputs. The surrogate wind data is created byan analog method using high‐resolution wind data from the ECMWF atmospheric reanalysis data set todownscale data from the low‐resolution Max‐Planck Institute of Earth System Model (MPI‐ESM‐LR). Thisstatistical approach provides computationally efficient and reliable wind inputs for wave modeling whilecapturing the temporal and spatial variability of present and future wind patterns. While the spatial distributionof significant wave height differences shows a north‐south gradient, with an increase in the northern NortheastAtlantic and a decrease in the south, regional variability is evident. Seasonal analysis indicates pronouncedincreases in wave heights during winter and summer, with the largest decrease observed in autumn. This studydemonstrates the efficiency of surrogate wind data for downscaling climate model outputs to supportnearshore wave modeling. The findings underscore the importance of considering both regional and seasonalvariability in wave cl