Wind damage from hurricanes is a major yet underrecognized driver of climate losses in coastal Louisiana, where research and planning have traditionally centered on flooding. This study advances a high-resolution wind risk framework linking building-level hazard simulation, extreme-value modeling, and spatial statistical analysis to identify where wind losses are concentrated and which communities carry the greatest burden.

Using ASCE wind hazard datasets, 3-second gust speeds across multiple return periods, terrain roughness, and Gumbel distributions, we modeled 50,000 Monte Carlo simulations per structure across 708 census tracts to estimate Expected Annual Structural Damage (EASD) and Expected Annual Dollar Damage (EADD). Results reveal pronounced spatial clustering of elevated losses, with the highest expected annual damages concentrated in low-roughness coastal zones. In some tracts, expected annual losses exceed $3 million, reflecting both exposure to extreme wind hazards and structural fragility.

To understand the social landscape of wind vulnerability, we linked tract-level EASD and EADD with socioeconomic and demographic indicators from the 2018–2022 ACS and the 2020 DHC dataset. Higher wind losses were associated with higher-income coastal communities, tracts with larger shares of renters and rural residents, and tracts with higher representation of residents of “other” races. These patterns indicate distinct inequality pathways compared to hurricane-related flood losses.

By identifying who is most exposed, why losses are uneven, and where cross-community collaboration can generate the greatest resilience gains, this study reframes wind damage from isolated risk points to an opportunity for partnership-driven preparedness, targeted mitigation, and equitable resilience planning across southern Louisiana.